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A novel MPI-based parallel smoothed particle hydrodynamics framework with dynamic load balancing for free surface flow.

Authors :
Zhu, Guixun
Hughes, Jason
Zheng, Siming
Greaves, Deborah
Source :
Computer Physics Communications. Mar2023, Vol. 284, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

This paper presents a new Smoothed Particle Hydrodynamics (SPH) parallel framework, which is designed for free surface flows and is scalable on a High Performance Computer (HPC). The framework is accomplished by adopting a Message Passing Interface (MPI) approach with a domain partitioning strategy. A regular background grid is used to partition the entire computational domain and each subdomain is labelled using an index ordering method. Adjacent subdomains can be determined by the index list, and avoid global communications in the particle distribution process. Within the local grid, the grid is divided into an internal grid as well as an interactive grid to identify the particles for which information is to be transferred. The implementation of the dynamic loading balance strategy considers two different ways of determining loading: computation particle numbers and running time. The dynamic load balance strategy repositions neighbouring subdomains based on the local load imbalance between cores. To demonstrate the framework's capacity and distinctive properties, a variety of free surface flow benchmarks are studied. Intensive numerical experiments at various scales are used to assess the performance in detail. • We propose a new MPI-based parallel SPH framework for free-surface flow. • A dynamic load balance strategy is applied in the parallel SPH framework. • The SPH framework works well for free surface conditions with large deformation. • Time cost-based balancing strategy is more efficient than the particle number-based. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00104655
Volume :
284
Database :
Academic Search Index
Journal :
Computer Physics Communications
Publication Type :
Periodical
Accession number :
161120305
Full Text :
https://doi.org/10.1016/j.cpc.2022.108608