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A Smoothed Particle Hydrodynamics Mini-App for Exascale
ConferencePaper (Artikel, die in Tagungsbänden erschienen sind)
 
ID 4616322
Author(s) Cavelan, Aurélien; Cabezón, Rubén M.; Grabarczyk, Michal; Ciorba, Florina M.
Author(s) at UniBasel Ciorba, Florina M.
Cavelan, Aurélien
Cabezon, Ruben
Year 2020
Title A Smoothed Particle Hydrodynamics Mini-App for Exascale
Book title (Conference Proceedings) PASC '20: Proceedings of the Platform for Advanced Scientific Computing Conference
Place of Conference Geneva, Switzerland
Year of Conference 2020
Publisher Association for Computing Machinery
Place of Publication New York
Pages 11
ISSN/ISBN 978-1-4503-7993-9
Keywords Exascale, SPH, performance, parallelization, mini-app, algorithms
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.
URL https://doi.org/10.1145/3394277.3401855
edoc-URL https://edoc.unibas.ch/81961/
Full Text on edoc No
Document type (ISI) inproceedings
Top-publication of... Ciorba, Florina M.
 
   

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