A parallel lattice Boltzmann method for large eddy simulation on multiple GPUs

被引:0
作者
Qinjian Li
Chengwen Zhong
Kai Li
Guangyong Zhang
Xiaowei Lu
Qing Zhang
Kaiyong Zhao
Xiaowen Chu
机构
[1] Northwestern Polytechnical University,School of Computer Science
[2] Northwestern Polytechnical University,National Key Laboratory of Science and Technology on Aerodynamics Design and Research
[3] National Key Laboratory for High-efficient Server and Storage Technology,Department of Computer Science
[4] Inspur,Institute of Computational and Theoretical Studies
[5] Hong Kong Baptist University,undefined
[6] Hong Kong Baptist University,undefined
来源
Computing | 2014年 / 96卷
关键词
Lattice Boltzmann method; GPU Computing; Large eddy simulation; CUDA; 76F65;
D O I
暂无
中图分类号
学科分类号
摘要
To improve the simulation efficiency of turbulent fluid flows at high Reynolds numbers with large eddy dynamics, a CUDA-based simulation solution of lattice Boltzmann method for large eddy simulation (LES) using multiple graphics processing units (GPUs) is proposed. Our solution adopts the “collision after propagation” lattice evolution way and puts the misaligned propagation phase at global memory read process. The latest GPU platform allows a single CPU thread to control up to four GPUs that run in parallel. In order to make use of multiple GPUs, the whole working set is evenly partitioned into sub-domains. We implement Smagorinsky model and Vreman model respectively to verify our multi-GPU solution. These two LES models have different relaxation time calculation behavior and lead to different CUDA implementation characteristics. The implementation based on Smagorinsky model achieves 190 times speedup over the sequential implementation on CPU, while the implementation based on Vreman model archives more than 90 times speedup. The experimental results show that the parallel performance of our multi-GPU solution scales very well on multiple GPUs. Therefore large-scale (up to 10,240 ×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document} 10,240 lattices) LES–LBM simulation becomes possible at a low cost, even using double-precision floating point calculation.
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页码:479 / 501
页数:22
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