Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project

Driven by the need to improve computational efficiency, the technique of reducing variable precision in model calculations has recently attracted a lot of attention, particularly in the field of weather and climate simulations models, where computational gains are crucial to produce operational resu...

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Detalles Bibliográficos
Autores: Paronuzzi Ticco, Stella Valentina, Utrera Iglesias, Gladys Miriam|||0000-0002-0637-1297, Acosta Cobos, Mario César
Tipo de recurso: artículo
Fecha de publicación:2025
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:2117/439220
Acceso en línea:https://hdl.handle.net/2117/439220
https://dx.doi.org/10.1016/j.cageo.2025.105989
Access Level:acceso abierto
Palabra clave:Climate models
High performance computing
Variable precision
Numerical simulation
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria
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spelling Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth projectParonuzzi Ticco, Stella ValentinaUtrera Iglesias, Gladys Miriam|||0000-0002-0637-1297Acosta Cobos, Mario CésarClimate modelsHigh performance computingVariable precisionNumerical simulationÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadorsÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeriaDriven by the need to improve computational efficiency, the technique of reducing variable precision in model calculations has recently attracted a lot of attention, particularly in the field of weather and climate simulations models, where computational gains are crucial to produce operational results faster and make better use of HPC resources. However, the source of computational improvements resulting from working in reduced precision, an aspect that could help facilitate the transition in many applications, has never been thoroughly explained. In this paper, we make a step in this direction, shedding light on how to efficiently apply variable precision reduction in chaotic applications, and presenting a computational study methodology to make this possible. For this purpose, we employ a tool for automatic porting of oceanographic code to mixed precision recently developed at the Barcelona Supercomputing Center and consider as case studies one of the most widely employed ocean models, NEMO, in one of the most ambitious initiatives to date, Destination Earth, because it aims at creating interactive digital replicas of the Earth with unprecedented precision, supporting real-time decision-making and long-term adaptation strategies, which also entails an unprecedented computational cost in terms of supercomputing. We analyze in depth the impact of mixed precision on the most representative functions of the model, providing a clear step forward in understanding where to focus efforts in precision reduction. These results can guide scientists in significantly speeding up weather and climate models using mixed precision by targeting computationally intensive functions and optimizing communications.This research was supported by the European High Performance Computing Joint Undertaking (EuroHPC JU) and the European Union (EU) through the ESiWACE3 project under grant agreement No. 101093054 and Destination Earth. Additional funding was provided by the National Research Agency through the OEMES project (PID2020- 116324RA-I00) and the GLORIA project (TED2021-129543B-I00).Peer Reviewed20252025-11-0120252025-07-23journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/439220https://dx.doi.org/10.1016/j.cageo.2025.105989reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4392202026-05-27T15:37:01Z
dc.title.none.fl_str_mv Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
title Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
spellingShingle Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
Paronuzzi Ticco, Stella Valentina
Climate models
High performance computing
Variable precision
Numerical simulation
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria
title_short Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
title_full Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
title_fullStr Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
title_full_unstemmed Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
title_sort Efficient variable precision reduction in chaotic climate models: Analysis of the NEMO case in the destination earth project
dc.creator.none.fl_str_mv Paronuzzi Ticco, Stella Valentina
Utrera Iglesias, Gladys Miriam|||0000-0002-0637-1297
Acosta Cobos, Mario César
author Paronuzzi Ticco, Stella Valentina
author_facet Paronuzzi Ticco, Stella Valentina
Utrera Iglesias, Gladys Miriam|||0000-0002-0637-1297
Acosta Cobos, Mario César
author_role author
author2 Utrera Iglesias, Gladys Miriam|||0000-0002-0637-1297
Acosta Cobos, Mario César
author2_role author
author
dc.subject.none.fl_str_mv Climate models
High performance computing
Variable precision
Numerical simulation
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria
topic Climate models
High performance computing
Variable precision
Numerical simulation
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Aplicacions informàtiques a la física i l‘enginyeria
description Driven by the need to improve computational efficiency, the technique of reducing variable precision in model calculations has recently attracted a lot of attention, particularly in the field of weather and climate simulations models, where computational gains are crucial to produce operational results faster and make better use of HPC resources. However, the source of computational improvements resulting from working in reduced precision, an aspect that could help facilitate the transition in many applications, has never been thoroughly explained. In this paper, we make a step in this direction, shedding light on how to efficiently apply variable precision reduction in chaotic applications, and presenting a computational study methodology to make this possible. For this purpose, we employ a tool for automatic porting of oceanographic code to mixed precision recently developed at the Barcelona Supercomputing Center and consider as case studies one of the most widely employed ocean models, NEMO, in one of the most ambitious initiatives to date, Destination Earth, because it aims at creating interactive digital replicas of the Earth with unprecedented precision, supporting real-time decision-making and long-term adaptation strategies, which also entails an unprecedented computational cost in terms of supercomputing. We analyze in depth the impact of mixed precision on the most representative functions of the model, providing a clear step forward in understanding where to focus efforts in precision reduction. These results can guide scientists in significantly speeding up weather and climate models using mixed precision by targeting computationally intensive functions and optimizing communications.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-11-01
2025
2025-07-23
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/439220
https://dx.doi.org/10.1016/j.cageo.2025.105989
url https://hdl.handle.net/2117/439220
https://dx.doi.org/10.1016/j.cageo.2025.105989
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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