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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.01579 |
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| _version_ | 1866917690378027008 |
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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 |