@inproceedings{10.1145/3394277.3401855,
author = {Cavelan, Aur\'{e}lien and Cabez\'{o}n, Rub\'{e}n M. and Grabarczyk, Michal and Ciorba, Florina M.},
title = {A Smoothed Particle Hydrodynamics Mini-App for Exascale},
year = {2020},
isbn = {9781450379939},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3394277.3401855},
doi = {10.1145/3394277.3401855},
abstract = {The Smoothed Particles Hydrodynamics (SPH) is a particle-based, meshfree, Lagrangian method used to simulate multidimensional fluids with arbitrary geometries, most commonly employed in astrophysics, cosmology, and computational fluid-dynamics (CFD). It is expected that these computationally-demanding numerical simulations will significantly benefit from the up-and-coming Exascale computing infrastructures, that will perform 1018 FLOP/s. In this work, we review the status of a novel SPH-EXA mini-app, which is the result of an interdisciplinary co-design project between the fields of astrophysics, fluid dynamics and computer science, whose goal is to enable SPH simulations to run on Exascale systems. The SPH-EXA mini-app merges the main characteristics of three state-of-the-art parent SPH codes (namely ChaNGa, SPH-flow, SPHYNX) with state-of-the-art (parallel) programming, optimization, and parallelization methods. The proposed SPH-EXA mini-app is a C++14 lightweight and flexible header-only code with no external software dependencies. Parallelism is expressed via multiple programming models, which can be chosen at compilation time with or without accelerator support, for a hybrid process+thread+accelerator configuration. Strong- and weak-scaling experiments on a production supercomputer show that the SPH-EXA mini-app can be efficiently executed with up 267 million particles and up to 65 billion particles in total on 2,048 hybrid CPU-GPU nodes.},
booktitle = {Proceedings of the Platform for Advanced Scientific Computing Conference},
articleno = {11},
numpages = {11},
keywords = {Exascale, SPH, performance, parallelization, mini-app, algorithms},
location = {Geneva, Switzerland},
series = {PASC '20}
}