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Matrix Product (GEMM) Performance Data from GPUs

  • Joubert, Wayne | Oak Ridge National Laboratory
  • Palmer, Eric | Oak Ridge National Laboratory
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Overview

Description

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.

Funding Resources

DOE Contract Number

DE-AC05-00OR22725

Originating Research Organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization

Office of Science (SC);Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

Project Identifier

GEMM_Performance_Data

Details

DOI

10.13139/OLCF/1819195

Release Date

September 9, 2021

Dataset

Dataset Type

ND Numeric Data

Software

gzip; tar

Acknowledgements

Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:

This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

Category

  • 97 MATHEMATICS AND COMPUTING

Keywords

  • GEMM matrix product operations,
  • computer system benchmarking,
  • GPU Graphical Processing Units