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A Hybrid Decomposition Parallel Algorithm for Multi-scale Simulation of Viscoelastic Fluids

Authors: Xiaowei Guo; Xinhai Xu; Qian Wang; Hao Li 0039; Xiaoguang Ren; Liyang Xu; Xuejun Yang;

A Hybrid Decomposition Parallel Algorithm for Multi-scale Simulation of Viscoelastic Fluids

Abstract

The method of Brownian configuration fields (BCF) is a promising multi-scale approach for the simulationof viscoelastic fluids, however, it is a computationally expensive method, which restricts its application in complex scenarios. Therefore, it is of great importance to optimize the parallel implementation in order to improve computational efficiency. In this paper we propose a hybrid decomposition parallel algorithm named: MCDPar, whichenables the simulation problem to bedecomposed simultaneously over mesh cells andthe Brownian configuration fields. Compution processes are split into multiple groups and Brownian configuration fields are equally associated with these groups. Meanwhile, within each group the processes are concurrently executed based on the traditional mesh decomposition approach. Finally we implemented the MCDPar algorithm in a micro-macro numerical solver based on OpenFOAM. Experimental results show that the micro-macro simulation time of viscoelastic fluids issignificantly reduced with improved scalability and parallel efficiency. In the test case with Nf = 2000 and Ncell = 262144, the speedup of the MCDParis up to 9.23x with a 7.5x increase in number of cores compared to the original parallel algorithm.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Average
Top 10%
Top 10%
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