Latency and Bandwidth Microbenchmarks of Six US Department of Energy Systems in the Top500

Carl Pearson, Christopher M. Siefert, Stephen L. Olivier, Andrey Prokopenko, Timothy J. Fuller, Jonathan J. Hu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Developers of portable high-performance computing applications are often concerned with basic performance properties across a variety of systems. Although supercomputing systems are comprehensively benchmarked during their acceptance testing process, results are not publicly disseminated and comparisons are typically restricted to immediate predecessor systems. This work presents selected single-node microbenchmarks of archetypal United States Department of Energy computers present in the June 2023 Top 500 list. These systems feature Intel or AMD CPUs, including Xeon Phi, and AMD or Nvidia GPUs, and provide a reasonable reference for what users can expect from these systems.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE International Conference on Cluster Computing Workshops and Posters, CLUSTER Workshops 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages52-53
Number of pages2
ISBN (Electronic)9798350370621
DOIs
StatePublished - 2023
Event25th IEEE International Conference on Cluster Computing Workshops, CLUSTER Workshops 2023 - Santa Fe, United States
Duration: Oct 31 2023Nov 3 2023

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
ISSN (Print)1552-5244

Conference

Conference25th IEEE International Conference on Cluster Computing Workshops, CLUSTER Workshops 2023
Country/TerritoryUnited States
CitySanta Fe
Period10/31/2311/3/23

Funding

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2023-09018C. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. This research used resources of the Los Alamos National Laboratory, supported by the US Department of Energy under contract No 89233218CNA000001 This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This research made use of Idaho National Laboratory computing resources which are supported by the Office of Nuclear Energy of the U.S. Department of Energy and the Nuclear Science User Facilities under Contract No. DE-AC07-05ID14517. This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the U.S. Department of Energy.

FundersFunder number
U.S. Department of EnergyDE-AC05-00OR22725, 89233218CNA000001, DE-AC02-05CH11231, DE-AC07-05ID14517
Office of Science
Office of Nuclear Energy
National Nuclear Security AdministrationDE-NA0003525, SAND2023-09018C
Los Alamos National Laboratory

    Keywords

    • Computer performance
    • Graphics processors
    • High performance computing
    • Software performance

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