Articles | Volume 15, issue 4
https://doi.org/10.5194/gmd-15-1567-2022
https://doi.org/10.5194/gmd-15-1567-2022
Development and technical paper
 | 
22 Feb 2022
Development and technical paper |  | 22 Feb 2022

Improving ocean modeling software NEMO 4.0 benchmarking and communication efficiency

Gaston Irrmann, Sébastien Masson, Éric Maisonnave, David Guibert, and Erwan Raffin

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Cited articles

Debreu, L., Vouland, C., and Blayo, E.: AGRIF: Adaptive Grid Refinement In Fortran, Comput. Geosci., 34, 8–13, https://doi.org/10.1016/j.cageo.2007.01.009, 2008. a
Etiemble, D.: 45-year CPU evolution: one law and two equations, CoRR, abs/1803.00254, http://arxiv.org/abs/1803.00254 (last access: 1 March 2018), 2018. a
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S., Collins, W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.: Evaluation of Climate Models, book section 9, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 741–866, https://doi.org/10.1017/CBO9781107415324.020, 2013. a
Irrmann, G. and Jouanno, J.: West Atlantic simulation input files and run, Zenodo [data set], https://doi.org/10.5281/zenodo.6047624, 2022. a
Koldunov, N. V., Aizinger, V., Rakowsky, N., Scholz, P., Sidorenko, D., Danilov, S., and Jung, T.: Scalability and some optimization of the Finite-volumE Sea ice–Ocean Model, Version 2.0 (FESOM2), Geosci. Model Dev., 12, 3991–4012, https://doi.org/10.5194/gmd-12-3991-2019, 2019. a
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Short summary
To be efficient on supercomputers, software must be high-performance at computing many concurrent tasks. Communications between tasks is often necessary but time consuming, and ocean modelling software NEMO 4.0 is no exception. In this work we describe approaches enabling fewer communications, an optimization to share the workload more equally between tasks and a new flexible configuration to assess NEMO's performance easily.