Jisuanji kexue (Jun 2022)

Parallel Optimization Method of Unstructured-grid Computing in CFD for DomesticHeterogeneous Many-core Architecture

  • CHEN Xin, LI Fang, DING Hai-xin, SUN Wei-ze, LIU Xin, CHEN De-xun, YE Yue-jin, HE Xiang

DOI
https://doi.org/10.11896/jsjkx.210400157
Journal volume & issue
Vol. 49, no. 6
pp. 99 – 107

Abstract

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Sunway TaihuLight ranked first in the global supercomputer top 500 list 2016-2018 with a peak performance of 125.4 PFlops.Its computing power is mainly attributed to the domestic SW26010 many-core RISC processor.CFD unstructured-grid computing has always been a challenge for porting and optimizing in domestic many-core supercomputer,because of its complex topology,serious discrete memory access problems,and strongly correlated linear equation solution.In order to give fully play to the computing efficiency of domestic heterogeneous multi-core architecture,firstly,a data reconstruction model is proposed to improve the locality and parallelism of data,and the data structure is more suitable for the characteristics of multi-core architecture.Secondly,aiming at the discrete memory access problem caused by the disorder of unstructured-grid data storage,a discrete memory access optimization method based on prestorage of information relation is proposed,which transforms discrete memory access into continuous memory access.Finally,the pipeline parallelism mechanism in core array is introduced to realize many-core parallelism for solving linear equations with strong correlation.Experiments show that the overall performance of unstructured-grid computing in CFD is improved by more than 4 times,and is 1.2x faster than the general CPU.The computing cores scale to 624 000,and the parallelism efficiency is maintained at 64.5%.

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