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An Efficient SIMD Implementation of Pseudo-Verlet Lists for Neighbour Interactions in Particle-Based Codes

Authors :
Willis, James S.
Schaller, Matthieu
Gonnet, Pedro
Bower, Richard G.
Draper, Peter W.
Source :
Advances in Parallel Computing, Volume 32: Parallel Computing is Everywhere (2018)
Publication Year :
2018

Abstract

In particle-based simulations, neighbour finding (i.e finding pairs of particles to interact within a given range) is the most time consuming part of the computation. One of the best such algorithms, which can be used for both Molecular Dynamics (MD) and Smoothed Particle Hydrodynamics (SPH) simulations, is the pseudo-Verlet list algorithm. This algorithm, however, does not vectorise trivially, and hence makes it difficult to exploit SIMD-parallel architectures. In this paper, we present several novel modifications as well as a vectorisation strategy for the algorithm which lead to overall speed-ups over the scalar version of the algorithm of 2.24x for the AVX instruction set (SIMD width of 8), 2.43x for AVX2, and 4.07x for AVX-512 (SIMD width of 16).<br />Comment: 10 pages, 3 figures. Proceedings of the ParCo 2017 conference, Bologna, Italy, September 12-15th, 2017

Details

Database :
arXiv
Journal :
Advances in Parallel Computing, Volume 32: Parallel Computing is Everywhere (2018)
Publication Type :
Report
Accession number :
edsarx.1804.06231
Document Type :
Working Paper
Full Text :
https://doi.org/10.3233/978-1-61499-843-3-507