Abstract
FTTN is a test suite to evaluate the numerical behaviors of matrix accelerators of GPUs (NVIDIA Tensor
Cores and AMD Matrix Cores) in a quick and simple setting. Matrix accelerators are heavily used in
today's computationally intense applications to speed up matrix multiplications. This test suite provides a
comprehensive study on the numerical behaviors of these accelerators, including support for subnormals,
rounding modes, extra precision bits and FMA features.
Is there
- Developers:
-
Laguna Peralta, Ignacio [1] ; Gopalakrishnan, Ganesh [2] ; Li, Xinyi [2]
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- University of Utah
- Release Date:
- 2024-08-28
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Version:
- 0.1
- Licenses:
-
MIT License
- Sponsoring Org.:
-
USDOE National Nuclear Security Administration (NNSA)Primary Award/Contract Number:AC52-07NA27344
- Code ID:
- 145775
- Site Accession Number:
- LLNL-CODE-2000523
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Country of Origin:
- United States
Citation Formats
Laguna Peralta, Ignacio, Gopalakrishnan, Ganesh, and Li, Xinyi.
FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators.
Computer Software.
https://github.com/LLNL/FTTN.
USDOE National Nuclear Security Administration (NNSA).
28 Aug. 2024.
Web.
doi:10.11578/dc.20241018.1.
Laguna Peralta, Ignacio, Gopalakrishnan, Ganesh, & Li, Xinyi.
(2024, August 28).
FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators.
[Computer software].
https://github.com/LLNL/FTTN.
https://doi.org/10.11578/dc.20241018.1.
Laguna Peralta, Ignacio, Gopalakrishnan, Ganesh, and Li, Xinyi.
"FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators." Computer software.
August 28, 2024.
https://github.com/LLNL/FTTN.
https://doi.org/10.11578/dc.20241018.1.
@misc{
doecode_145775,
title = {FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators},
author = {Laguna Peralta, Ignacio and Gopalakrishnan, Ganesh and Li, Xinyi},
abstractNote = {FTTN is a test suite to evaluate the numerical behaviors of matrix accelerators of GPUs (NVIDIA Tensor
Cores and AMD Matrix Cores) in a quick and simple setting. Matrix accelerators are heavily used in
today's computationally intense applications to speed up matrix multiplications. This test suite provides a
comprehensive study on the numerical behaviors of these accelerators, including support for subnormals,
rounding modes, extra precision bits and FMA features.
Is there},
doi = {10.11578/dc.20241018.1},
url = {https://doi.org/10.11578/dc.20241018.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20241018.1}},
year = {2024},
month = {aug}
}