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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/2409.15859 |
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| _version_ | 1866916408716165120 |
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| author | Bull, J. Mark Coughtrie, Andrew Deeptimahanti, Deva Hedley, Mark Laoide-Kemp, Caoimhín Maynard, Christopher Shepherd, Harry van de Bund, Sebastiaan Weiland, Michèle Went, Benjamin |
| author_facet | Bull, J. Mark Coughtrie, Andrew Deeptimahanti, Deva Hedley, Mark Laoide-Kemp, Caoimhín Maynard, Christopher Shepherd, Harry van de Bund, Sebastiaan Weiland, Michèle Went, Benjamin |
| contents | This study presents scaling results and a performance analysis across different supercomputers and compilers for the Met Office weather and climate model, LFRic. The model is shown to scale to large numbers of nodes which meets the design criteria, that of exploitation of parallelism to achieve good scaling. The model is written in a Domain-Specific Language, embedded in modern Fortran and uses a Domain-Specific Compiler, PSyclone, to generate the parallel code. The performance analysis shows the effect of choice of algorithm, such as redundant computation and scaling with OpenMP threads. The analysis can be used to motivate a discussion of future work to improve the OpenMP performance of other parts of the code. Finally, an analysis of the performance tuning of the I/O server, XIOS is presented. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_15859 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers Bull, J. Mark Coughtrie, Andrew Deeptimahanti, Deva Hedley, Mark Laoide-Kemp, Caoimhín Maynard, Christopher Shepherd, Harry van de Bund, Sebastiaan Weiland, Michèle Went, Benjamin Distributed, Parallel, and Cluster Computing Performance This study presents scaling results and a performance analysis across different supercomputers and compilers for the Met Office weather and climate model, LFRic. The model is shown to scale to large numbers of nodes which meets the design criteria, that of exploitation of parallelism to achieve good scaling. The model is written in a Domain-Specific Language, embedded in modern Fortran and uses a Domain-Specific Compiler, PSyclone, to generate the parallel code. The performance analysis shows the effect of choice of algorithm, such as redundant computation and scaling with OpenMP threads. The analysis can be used to motivate a discussion of future work to improve the OpenMP performance of other parts of the code. Finally, an analysis of the performance tuning of the I/O server, XIOS is presented. |
| title | Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers |
| topic | Distributed, Parallel, and Cluster Computing Performance |
| url | https://arxiv.org/abs/2409.15859 |