Task-Based Parallelization of the Fast Multipole Method on NVIDIA GPUs and Multicore Processors

Abstract : Fast Multipole Methods are a fundamental operation for the simulation of many physical problems. In this talk, we present a new approach for implementing these methods that achieves high performance across many different computer architectures. Our method consists of expressing the FMM algorithm as a task flow and employing a state-of-the-art runtime system, StarPU, to process the tasks on the different computing units.
Keywords : Runtime GPU HPC FMM
Type de document :
Communication dans un congrès
SIAM Conference on Computational Science and Engineering (SIAM CSE 2015), Mar 2015, Salt Lake City, United States. 2015, 〈http://www.siam.org/meetings/cse15/〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01135258
Contributeur : Bérenger Bramas <>
Soumis le : mercredi 25 mars 2015 - 09:57:44
Dernière modification le : jeudi 11 janvier 2018 - 06:22:35

Identifiants

  • HAL Id : hal-01135258, version 1

Citation

Emmanuel Agullo, Bérenger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, et al.. Task-Based Parallelization of the Fast Multipole Method on NVIDIA GPUs and Multicore Processors. SIAM Conference on Computational Science and Engineering (SIAM CSE 2015), Mar 2015, Salt Lake City, United States. 2015, 〈http://www.siam.org/meetings/cse15/〉. 〈hal-01135258〉

Partager

Métriques

Consultations de la notice

342