Abstract
Communications in distributed memory supercomputers are still limiting scalability of geophysical models. Consid-ering the recent trends of the semiconductor industry, we think this problem is here to stay. We present the optimisations thathave been implemented in the actual 4.0 reference version of the ocean model NEMO 4.0 to improve its scalability. Thanksto the collaboration of oceanographers and HPC experts, we identified and removed the unnecessary communications in twobottleneck routines, the computation of free surface pressure gradient and the forcing in the straights or unstructured open5boundaries. Since a wrong parallel decomposition choice could undermine computing performance, we impose its automaticdefinition in all cases, including when subdomains containing land points only are excluded from the decomposition. For asmaller audience of developers and vendors, we propose a new benchmark configuration, easy to use while offering the fullcomplexity of operational versions.
Highlights
There is, hopefully, no more need to justify the importance of climate research for our societies (Masson-Delmotte et al, 2018)
This work must improve the performance while preserving the code accessibility by climate scientists who use it and develop it, and are not necessary experts in computing sciences. This optimization work lies within this framework and we gathered, in this study, authors with very complementary profiles: oceanographers, NEMO developers, specialized engineers in climate modelling 35 and frontier simulations and pure HPC engineers. This works complements the report of Maisonnave and Masson (2019) by presenting the new HPC optimisations that have been implemented in NEMO 4.0, the actual reference version of the code
The choice of the domain decomposition proposed by default in NEMO until version 3.6 was very basic as 2 was the only prime factor considered when looking at divisors of the number of MPI tasks! Tintó et al (2017) underlined this deficiency
Summary
There is, hopefully, no more need to justify the importance of climate research for our societies (Masson-Delmotte et al, 2018). This work must improve the performance while preserving the code accessibility by climate scientists who use it and develop it, and are not necessary experts in computing sciences This optimization work lies within this framework and we gathered, in this study, authors with very complementary profiles: oceanographers, NEMO developers, specialized engineers in climate modelling 35 and frontier simulations and pure HPC engineers. This works complements the report of Maisonnave and Masson (2019) by presenting the new HPC optimisations that have been implemented in NEMO 4.0, the actual reference version of the code. This second section of the paper details the code modifications introduced in NEMO 4.0 in order to provide a proper benchmarking environment aiming at facilitating numerical performance tests and optimizations
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