This paper presents novel approaches to parallelizing particle interactions on a GPU when there are few particles per cell and the interactions are limited by a cutoff distance. The paper surveys classical algorithms and then introduces two alternatives that aim to utilize shared memory. The first approach copies the particles of a sub-box, while the second approach loads particles in a pencil along the X-axis. The different implementations are compared on three GPU models using Cuda and Hip. The results show that the X-pencil approach can provide a significant speedup but only in very specific cases.
@article{arxiv.2406.16091,
title = {Efficient GPU Implementation of Particle Interactions with Cutoff Radius and Few Particles per Cell},
author = {David Algis and Berenger Bramas and Emmanuelle Darles and Lilian Aveneau},
journal= {arXiv preprint arXiv:2406.16091},
year = {2024}
}