Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers
<|reference_start|>Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers: 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.<|reference_end|>
@article{bull2024performance,
    title={Performance and scaling of the LFRic weather and climate model on
  different generations of HPE Cray EX supercomputers},
    author={J. Mark Bull (1), Andrew Coughtrie (2), Deva Deeptimahanti (3), Mark
  Hedley (2), Caoimh'in Laoide-Kemp (1), Christopher Maynard (2), Harry
  Shepherd (2), Sebastiaan van de Bund (1), Mich`ele Weiland (2), Benjamin
  Went (2) ((1) EPCC University of Edinburgh, (2) Met Office, (3) Pawsey
  Supercomputing Research Centre)},
    journal={arXiv preprint arXiv:2409.15859},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.15859},
    primaryClass={cs.DC cs.PF}
}