Dynamic resource allocation for efficient parallel CFD simulations

CFD users of supercomputers usually resort to rule-of-thumb methods to select the number of subdomains (partitions) when relying on MPI-based parallelization. One common approach is to set a minimum number of elements or cells per subdomain, under which the parallel efficiency of the code is “known”...

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Detalles Bibliográficos
Autores: Houzeaux, Guillaume|||0000-0002-2592-1426, Badia Sala, Rosa Maria|||0000-0003-2941-5499, Borrell Pol, Ricard, Dosimont, Damien, Ejarque Artigas, Jorge, Garcia Gasulla, Marta|||0000-0003-3682-9905, López Herrero, Víctor
Tipo de recurso: artículo
Fecha de publicación:2022
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:2117/369349
Acceso en línea:https://hdl.handle.net/2117/369349
https://dx.doi.org/10.1016/j.compfluid.2022.105577
Access Level:acceso abierto
Palabra clave:Resource allocation
Computational fluid dynamics
Supercomputers
CFD
High performance computing
Elastic computing
Parallel efficiency
MPI
Assignació de recursos
Dinàmica de fluids computacional
Supercomputadors
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Descripción
Sumario:CFD users of supercomputers usually resort to rule-of-thumb methods to select the number of subdomains (partitions) when relying on MPI-based parallelization. One common approach is to set a minimum number of elements or cells per subdomain, under which the parallel efficiency of the code is “known” to fall below a subjective level, say 80%. The situation is even worse when the user is not aware of the “good” practices for the given code and a huge amount of resources can thus be wasted. This work presents an elastic computing methodology that adapts at runtime the resources allocated to a simulation automatically. The criterion to control the required resources is based on a runtime measure of the communication efficiency of the execution. According to some analytical estimates, the resources are then expanded or reduced to fulfill this criterion and eventually execute an efficient simulation.