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
Complete list of metadatas

https://hal.inria.fr/hal-01135258
Contributor : Bérenger Bramas <>
Submitted on : Wednesday, March 25, 2015 - 9:57:44 AM
Last modification on : Thursday, January 11, 2018 - 6:22:35 AM

Identifiers

  • 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. ⟨hal-01135258⟩

Share

Metrics

Record views

370