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Bibliographic Details
Main Authors: Alt, Christoph, Lanser, Martin, Plewinski, Jonas, Janki, Atin, Klawonn, Axel, Köstler, Harald, Selzer, Michael, Rüde, Ulrich
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.01579
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author Alt, Christoph
Lanser, Martin
Plewinski, Jonas
Janki, Atin
Klawonn, Axel
Köstler, Harald
Selzer, Michael
Rüde, Ulrich
author_facet Alt, Christoph
Lanser, Martin
Plewinski, Jonas
Janki, Atin
Klawonn, Axel
Köstler, Harald
Selzer, Michael
Rüde, Ulrich
contents For scientific software, especially those used for large-scale simulations, achieving good performance and efficiently using the available hardware resources is essential. It is important to regularly perform benchmarks to ensure the efficient use of hardware and software when systems are changing and the software evolves. However, this can become quickly very tedious when many options for parameters, solvers, and hardware architectures are available. We present a continuous benchmarking strategy that automates benchmarking new code changes on high-performance computing clusters. This makes it possible to track how each code change affects the performance and how it evolves.
format Preprint
id arxiv_https___arxiv_org_abs_2403_01579
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Continuous Benchmarking Infrastructure for High-Performance Computing Applications
Alt, Christoph
Lanser, Martin
Plewinski, Jonas
Janki, Atin
Klawonn, Axel
Köstler, Harald
Selzer, Michael
Rüde, Ulrich
Performance
For scientific software, especially those used for large-scale simulations, achieving good performance and efficiently using the available hardware resources is essential. It is important to regularly perform benchmarks to ensure the efficient use of hardware and software when systems are changing and the software evolves. However, this can become quickly very tedious when many options for parameters, solvers, and hardware architectures are available. We present a continuous benchmarking strategy that automates benchmarking new code changes on high-performance computing clusters. This makes it possible to track how each code change affects the performance and how it evolves.
title A Continuous Benchmarking Infrastructure for High-Performance Computing Applications
topic Performance
url https://arxiv.org/abs/2403.01579