Matrix Product (GEMM) Performance Data from GPUs
- Joubert, Wayne | Oak Ridge National Laboratory
- Palmer, Eric | Oak Ridge National Laboratory
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-AC05-00OR22725Originating 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)Details
DOI
10.13139/OLCF/1819195Release date
September 9, 2021Dataset
Dataset type
ND Numeric DataSoftware
gzip; tarAcknowledgements
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