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  • 标题:Scalable Parallel Algorithm of Multiple-Relaxation-Time Lattice Boltzmann Method with Large Eddy Simulation on Multi-GPUs
  • 本地全文:下载
  • 作者:Lei Xu ; Anping Song ; Wu Zhang
  • 期刊名称:Scientific Programming
  • 印刷版ISSN:1058-9244
  • 出版年度:2018
  • 卷号:2018
  • DOI:10.1155/2018/1298313
  • 出版社:Hindawi Publishing Corporation
  • 摘要:The lattice Boltzmann method (LBM) has become an attractive and promising approach in computational fluid dynamics (CFD). In this paper, parallel algorithm of D3Q19 multi-relaxation-time LBM with large eddy simulation (LES) is presented to simulate 3D flow past a sphere using multi-GPUs (graphic processing units). In order to deal with complex boundary, the judgement method of boundary lattice for complex boundary is devised. The 3D domain decomposition method is applied to improve the scalability for cluster, and the overlapping mode is introduced to hide the communication time by dividing the subdomain into two parts: inner part and outer part. Numerical results show good agreement with literature and the 12 Kepler K20M GPUs perform about 5100 million lattice updates per second, which indicates considerable scalability.
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