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Title: 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}
}