2026-04-17T01:32:23Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/3459552026-02-07T05:20:25Zcom_2072_1033col_2072_452950

A generic performance analysis technique applied to different CFD methods for HPC Garcia Gasulla, Marta Banchelli Gracia, Fabio Peiró Conde, Kilian Ramírez Gargallo, Guillem Houzeaux, Guillaume Hassan Saïdi, Ismaïl Ben Tenaud, Christian Spisso, Ivan Mantovani, Filippo Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors Computational fluid dynamics Supercomputers Performance analysis MPI Efficiency Parallelisation CFD Finite element Finite volume MareNostrum4 Dinàmica de fluids Supercomputadors For complex engineering and scientific applications, Computational Fluid Dynamics (CFD) simulations require a huge amount of computational power. As such, it is of paramount importance to carefully assess the performance of CFD codes and to study them in depth for enabling optimisation and portability. In this paper, we study three complex CFD codes, OpenFOAM, Alya and CHORUS representing two numerical methods, namely the finite volume and finite-element methods, on both structured and unstructured meshes. To all codes, we apply a generic performance analysis method based on a set of metrics helping the code developer in spotting the critical points that can potentially limit the scalability of a parallel application. We show the root cause of the performance bottlenecks studying the three applications on the MareNostrum4 supercomputer. We conclude providing hints for improving the performance and the scalability of each application. This work is partially supported by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology (TIN2015-65316-P), by the Generalitat de Catalunya (2017-SGR-1414), and by the European POP CoE (GA n. 824080). Peer Reviewed Postprint (published version) 2020-07-16 Article https://www.tandfonline.com/doi/full/10.1080/10618562.2020.1778168?journalCode=gcfd20 info:eu-repo/grantAgreement/MINECO//TIN2015-65316-P/ES/COMPUTACION DE ALTAS PRESTACIONES VII/ info:eu-repo/grantAgreement/AGAUR/2017 SGR 1414 info:eu-repo/grantAgreement/EC/H2020/824080/EU/Performance Optimisation and Productivity 2/POP2 https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access Attribution-NonCommercial-NoDerivatives 4.0 International Taylor & Francis