Matrix Product (GEMM) Performance Data from GPUs
Abstract
Timing data for mixed precision GEMM matrix product operations on several GPU models, including NVIDIA V100 and A100, AMD MI100 and Intel P580. Also data from machine learning model training on this data using Scikit-learn.
- Authors:
- Publication Date:
- DOE Contract Number:
- DE-AC05-00OR22725
- Research Org.:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
- Sponsoring Org.:
- USDOE Office of Science (SC); Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
- Subject:
- 97 MATHEMATICS AND COMPUTING
- Keywords:
- GEMM matrix product operations; computer system benchmarking; GPU Graphical Processing Units
- OSTI Identifier:
- 1819195
- DOI:
- https://doi.org/10.13139/OLCF/1819195
Citation Formats
Joubert, Wayne, and Palmer, Eric. Matrix Product (GEMM) Performance Data from GPUs. United States: N. p., 2021.
Web. doi:10.13139/OLCF/1819195.
Joubert, Wayne, & Palmer, Eric. Matrix Product (GEMM) Performance Data from GPUs. United States. doi:https://doi.org/10.13139/OLCF/1819195
Joubert, Wayne, and Palmer, Eric. 2021.
"Matrix Product (GEMM) Performance Data from GPUs". United States. doi:https://doi.org/10.13139/OLCF/1819195. https://www.osti.gov/servlets/purl/1819195. Pub date:Thu Sep 09 00:00:00 EDT 2021
@article{osti_1819195,
title = {Matrix Product (GEMM) Performance Data from GPUs},
author = {Joubert, Wayne and Palmer, Eric},
abstractNote = {Timing data for mixed precision GEMM matrix product operations on several GPU models, including NVIDIA V100 and A100, AMD MI100 and Intel P580. Also data from machine learning model training on this data using Scikit-learn.},
doi = {10.13139/OLCF/1819195},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2021},
month = {9}
}
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.