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

Related authors

The ESCAPE project: Energy-efficient Scalable Algorithms for Weather Prediction at Exascale
Andreas Müller, Willem Deconinck, Christian Kühnlein, Gianmarco Mengaldo, Michael Lange, Nils Wedi, Peter Bauer, Piotr K. Smolarkiewicz, Michail Diamantakis, Sarah-Jane Lock, Mats Hamrud, Sami Saarinen, George Mozdzynski, Daniel Thiemert, Michael Glinton, Pierre Bénard, Fabrice Voitus, Charles Colavolpe, Philippe Marguinaud, Yongjun Zheng, Joris Van Bever, Daan Degrauwe, Geert Smet, Piet Termonia, Kristian P. Nielsen, Bent H. Sass, Jacob W. Poulsen, Per Berg, Carlos Osuna, Oliver Fuhrer, Valentin Clement, Michael Baldauf, Mike Gillard, Joanna Szmelter, Enda O'Brien, Alastair McKinstry, Oisín Robinson, Parijat Shukla, Michael Lysaght, Michał Kulczewski, Milosz Ciznicki, Wojciech Piątek, Sebastian Ciesielski, Marek Błażewicz, Krzysztof Kurowski, Marcin Procyk, Pawel Spychala, Bartosz Bosak, Zbigniew P. Piotrowski, Andrzej Wyszogrodzki, Erwan Raffin, Cyril Mazauric, David Guibert, Louis Douriez, Xavier Vigouroux, Alan Gray, Peter Messmer, Alexander J. Macfaden, and Nick New
Geosci. Model Dev., 12, 4425–4441, https://doi.org/10.5194/gmd-12-4425-2019,https://doi.org/10.5194/gmd-12-4425-2019, 2019
Short summary
The Louvain-La-Neuve sea ice model LIM3.6: global and regional capabilities
C. Rousset, M. Vancoppenolle, G. Madec, T. Fichefet, S. Flavoni, A. Barthélemy, R. Benshila, J. Chanut, C. Levy, S. Masson, and F. Vivier
Geosci. Model Dev., 8, 2991–3005, https://doi.org/10.5194/gmd-8-2991-2015,https://doi.org/10.5194/gmd-8-2991-2015, 2015
Short summary

Related subject area

Oceanography
A wave-resolving two-dimensional vertical Lagrangian approach to model microplastic transport in nearshore waters based on TrackMPD 3.0
Isabel Jalón-Rojas, Damien Sous, and Vincent Marieu
Geosci. Model Dev., 18, 319–336, https://doi.org/10.5194/gmd-18-319-2025,https://doi.org/10.5194/gmd-18-319-2025, 2025
Short summary
HOTSSea v1: a NEMO-based physical Hindcast of the Salish Sea (1980–2018) supporting ecosystem model development
Greig Oldford, Tereza Jarníková, Villy Christensen, and Michael Dunphy
Geosci. Model Dev., 18, 211–237, https://doi.org/10.5194/gmd-18-211-2025,https://doi.org/10.5194/gmd-18-211-2025, 2025
Short summary
DalROMS-NWA12 v1.0, a coupled circulation–ice–biogeochemistry modelling system for the northwest Atlantic Ocean: development and validation
Kyoko Ohashi, Arnaud Laurent, Christoph Renkl, Jinyu Sheng, Katja Fennel, and Eric Oliver
Geosci. Model Dev., 17, 8697–8733, https://doi.org/10.5194/gmd-17-8697-2024,https://doi.org/10.5194/gmd-17-8697-2024, 2024
Short summary
A revised ocean mixed layer model for better simulating the diurnal variation in ocean skin temperature
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024,https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Evaluating an accelerated forcing approach for improving computational efficiency in coupled ice sheet–ocean modelling
Qin Zhou, Chen Zhao, Rupert Gladstone, Tore Hattermann, David Gwyther, and Benjamin Galton-Fenzi
Geosci. Model Dev., 17, 8243–8265, https://doi.org/10.5194/gmd-17-8243-2024,https://doi.org/10.5194/gmd-17-8243-2024, 2024
Short summary

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
Download
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.