English

Using Hierarchical Parallelism to Accelerate the Solution of Many Small Partial Differential Equations

Distributed, Parallel, and Cluster Computing 2023-05-15 v1 Mathematical Software

Abstract

This paper presents efforts to improve the hierarchical parallelism of a two scale simulation code. Two methods to improve the GPU parallel performance were developed and compared. The first used the NVIDIA Multi-Process Service and the second moved the entire sub-problem loop into a single kernel using Kokkos hierarchical parallelism and a PackedView data structure. Both approaches improved parallel performance with the second method providing the greatest improvements.

Keywords

Cite

@article{arxiv.2305.07030,
  title  = {Using Hierarchical Parallelism to Accelerate the Solution of Many Small Partial Differential Equations},
  author = {Jacob Merson and Mark S. Shephard},
  journal= {arXiv preprint arXiv:2305.07030},
  year   = {2023}
}

Comments

Originally presented at the HiPar workshop at The International Conference for High Performance Computing, Networking, Storage, and Analysis (2020)

R2 v1 2026-06-28T10:32:20.845Z