Nek5000/RS performance on advanced GPU architectures

The authors explore performance scalability of the open-source thermal-fluids code, NekRS, on the U.S. Department of Energy's leadership computers, Crusher, Frontier, Summit, Perlmutter, and Polaris. Particular attention is given to analyzing performance and time-to-solution at the strong-scale limit for a target efficiency of 80%, which is typical for production runs on the DOE's high-performance computing systems. Several examples of anomalous behavior are also discussed and analyzed.

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Publication Details

Journal
Frontiers in High Performance Computing
Published
2025-02-21
DOI
https://doi.org/10.3389/fhpcp.2024.1303358
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
2.27

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article

Nek5000/RS performance on advanced GPU architectures

John Holmen, Misun Min, Paul Fischer, Yu-Hsiang Lan et al.
1 citations
Frontiers in High Performance Computing
Parallel Computing and Optimization Techniques
2.27
article

Nek5000/RS performance on advanced GPU architectures

John Holmen, Misun Min, Paul Fischer, Yu-Hsiang Lan, Thilina Rathnayake
article en
1 citations

Abstract

The authors explore performance scalability of the open-source thermal-fluids code, NekRS, on the U.S. Department of Energy's leadership computers, Crusher, Frontier, Summit, Perlmutter, and Polaris. Particular attention is given to analyzing performance and time-to-solution at the strong-scale limit for a target efficiency of 80%, which is typical for production runs on the DOE's high-performance computing systems. Several examples of anomalous behavior are also discussed and analyzed.

Frontiers in High Performance ComputingVol. 2
Argonne National Laboratory (US), Oak Ridge National Laboratory (US), University of Illinois Urbana-Champaign (US)
U.S. Department of Energy, National Energy Research Scientific Computing Center, Office of Science, Argonne National Laboratory, Oak Ridge National Laboratory
Openalex Percentile: Top 18%
Parallel Computing and Optimization Techniques
2.27
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