libROM

RESOURCE

Abstract

libROM is a collection of C++ classes that compute reduced order models and hyperreduced order models for systems of ordinary differential equations. libROM includes parallel, adaptive methods for proper orthogonal decomposition, and parallel, non-adaptive methods for hyperreduction using the discrete empirical interpolation method.
Developers:
Choi, Youngsoo [1] Arrighi, William [1] Copeland, Dylan [1] Anderson, Robert [1] Oxberry, Geoffrey [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Release Date:
2019-10-17
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Licenses:
MIT License
Sponsoring Org.:
Code ID:
24508
Site Accession Number:
LLNL-CODE-766763
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Country of Origin:
United States

RESOURCE

Citation Formats

Choi, Youngsoo, Arrighi, William J., Copeland, Dylan M., Anderson, Robert W., and Oxberry, Geoffrey M. libROM. Computer Software. https://github.com/LLNL/libROM. USDOE National Nuclear Security Administration (NNSA). 17 Oct. 2019. Web. doi:10.11578/dc.20190408.3.
Choi, Youngsoo, Arrighi, William J., Copeland, Dylan M., Anderson, Robert W., & Oxberry, Geoffrey M. (2019, October 17). libROM. [Computer software]. https://github.com/LLNL/libROM. https://doi.org/10.11578/dc.20190408.3.
Choi, Youngsoo, Arrighi, William J., Copeland, Dylan M., Anderson, Robert W., and Oxberry, Geoffrey M. "libROM." Computer software. October 17, 2019. https://github.com/LLNL/libROM. https://doi.org/10.11578/dc.20190408.3.
@misc{ doecode_24508,
title = {libROM},
author = {Choi, Youngsoo and Arrighi, William J. and Copeland, Dylan M. and Anderson, Robert W. and Oxberry, Geoffrey M.},
abstractNote = {libROM is a collection of C++ classes that compute reduced order models and hyperreduced order models for systems of ordinary differential equations. libROM includes parallel, adaptive methods for proper orthogonal decomposition, and parallel, non-adaptive methods for hyperreduction using the discrete empirical interpolation method.},
doi = {10.11578/dc.20190408.3},
url = {https://doi.org/10.11578/dc.20190408.3},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20190408.3}},
year = {2019},
month = {oct}
}