Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers

J. Mark Bull; Andrew Coughtrie; Deva Deeptimahanti; Mark Hedley; Caoimhín Laoide-Kemp; Christopher Maynard; Harry Shepherd; Sebastiaan van de Bund; Michèle Weiland; Benjamin Went

arXiv · 2409.15859

Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers

J. Mark Bull·Andrew Coughtrie·Deva Deeptimahanti·Mark Hedley·Caoimhín Laoide-Kemp·Christopher Maynard·Harry Shepherd·Sebastiaan van de Bund·Michèle Weiland·Benjamin Went

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Abstract

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.

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J. Mark Bull, Andrew Coughtrie, Deva Deeptimahanti, Mark Hedley, Caoimhín Laoide-Kemp, Christopher Maynard, Harry Shepherd, Sebastiaan van de Bund, Michèle Weiland, Benjamin Went. 2024-09-24. Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers. https://arxiv.org/abs/2409.15859

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