Optimizing domain decomposition in an ocean model: the case of NEMO
Earth System Models are critical tools for the study of our climate and its future trends. These models are in constant evolution and their growing complexity entails an incrementing demand of the resources they require. Since the cost of using these state-of-the-art models is huge, looking closely...
| Autores: | , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/113348 |
| Acceso en línea: | https://hdl.handle.net/2117/113348 https://dx.doi.org/10.1016/j.procs.2017.05.257 |
| Access Level: | acceso abierto |
| Palabra clave: | Seasonal prediction (Meteorology) Hearth System Models HPC Domain decomposition NEMO Previsió del temps Clima--Observacions Àrees temàtiques de la UPC::Energies |
| Sumario: | Earth System Models are critical tools for the study of our climate and its future trends. These models are in constant evolution and their growing complexity entails an incrementing demand of the resources they require. Since the cost of using these state-of-the-art models is huge, looking closely at the factors that are able to impact their computational performance is mandatory. In the case of the state-of-the-art ocean model NEMO (Nucleus for European Modelling of the Ocean), used in many projects around the world, not enough attention has been given to the domain decomposition. In this work we show the impact that the selection of a particular domain decomposition can have on computational performance and how the proposed methodology substantially improves it. |
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