Adaptive Plasma Physics Simulations: Dealing with Load Imbalance using Charm++

Diego Jiménez, Esteban Meneses, V. I. Vargas

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

High Performance Computing (HPC) is nearing the exascale era and several challenges have to be addressed in terms of application development. Future parallel programming models should not only help developers take full advantage of the underlying machine but they should also account for highly dynamic runtime conditions, including frequent hardware failures. In this paper, we analyze the porting process of a plasma confinement simulator from a traditional MPI+OpenMP approach to a parallel objects based model like Charm++ the main driver for this effort is the existence of load imbalanced input scenarios that pure OpenMP scheduling can not solve. By using Charm++ adaptive runtime and integrated balancing strategies, we were able to increase total CPU usage from 45.2% to 80.2%, achieving a 1.64 × acceleration, after load balancing, over the MPI+OpenMP implementation on a specific input scenario. Checkpointing was added to the simulator thanks to the pack-unpack interface implemented by Charm++, providing scientists with fault tolerance and split execution capabilities.

Idioma originalInglés
Título de la publicación alojadaPEARC 2021 - Practice and Experience in Advanced Research Computing 2021
Subtítulo de la publicación alojadaEvolution Across All Dimensions
EditorialAssociation for Computing Machinery
ISBN (versión digital)9781450382922
DOI
EstadoPublicada - 17 jul 2021
Evento5th Practice and Experience in Advanced Research Computing Conference: Evolution Across All Dimensions, PEARC 2021 - Virtual, Online, Estados Unidos
Duración: 19 jul 202122 jul 2021

Serie de la publicación

NombreACM International Conference Proceeding Series

Conferencia

Conferencia5th Practice and Experience in Advanced Research Computing Conference: Evolution Across All Dimensions, PEARC 2021
País/TerritorioEstados Unidos
CiudadVirtual, Online
Período19/07/2122/07/21

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