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Main Authors: Bull, J. Mark, Coughtrie, Andrew, Deeptimahanti, Deva, Hedley, Mark, Laoide-Kemp, Caoimhín, Maynard, Christopher, Shepherd, Harry, van de Bund, Sebastiaan, Weiland, Michèle, Went, Benjamin
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2409.15859
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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