The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of low-precision special-function units designed for machine learning applications, the traditional numerical algorithms community urgently needs to reconsider the floating point formats used in the distinct operations to efficiently leverage the available compute power. In this study, we provide a comprehensive survey of mixed-precision numerical linear algebra routines, including the underlying concepts, theoretical background, and experimental results for both dense and sparse linear algebra problems.
Abdelfattah, Ahmad, et al. "A survey of numerical linear algebra methods utilizing mixed-precision arithmetic." International Journal of High Performance Computing Applications, vol. 35, no. 4, Mar. 2021. https://doi.org/10.1177/10943420211003313
Abdelfattah, Ahmad, Anzt, Hartwig, Boman, Erik G., et al., "A survey of numerical linear algebra methods utilizing mixed-precision arithmetic," International Journal of High Performance Computing Applications 35, no. 4 (2021), https://doi.org/10.1177/10943420211003313
@article{osti_1825849,
author = {Abdelfattah, Ahmad and Anzt, Hartwig and Boman, Erik G. and Carson, Erin and Cojean, Terry and Dongarra, Jack and Fox, Alyson and Gates, Mark and Higham, Nicholas J. and Li, Xiaoye S. and others},
title = {A survey of numerical linear algebra methods utilizing mixed-precision arithmetic},
annote = {The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of low-precision special-function units designed for machine learning applications, the traditional numerical algorithms community urgently needs to reconsider the floating point formats used in the distinct operations to efficiently leverage the available compute power. In this study, we provide a comprehensive survey of mixed-precision numerical linear algebra routines, including the underlying concepts, theoretical background, and experimental results for both dense and sparse linear algebra problems.},
doi = {10.1177/10943420211003313},
url = {https://www.osti.gov/biblio/1825849},
journal = {International Journal of High Performance Computing Applications},
issn = {ISSN 1094-3420},
number = {4},
volume = {35},
place = {United States},
publisher = {SAGE},
year = {2021},
month = {03}}
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
AC52-07NA27344
OSTI ID:
1825849
Report Number(s):
LLNL-JRNL--826451; 1041053
Journal Information:
International Journal of High Performance Computing Applications, Journal Name: International Journal of High Performance Computing Applications Journal Issue: 4 Vol. 35; ISSN 1094-3420
SC '17: The International Conference for High Performance Computing, Networking, Storage and Analysis, Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systemshttps://doi.org/10.1145/3148226.3148237