Parallel Performance and Optimization of the Lattice Boltzmann Method Software Palabos Using CUDA

Bin Huang, Anjun Liu, Min Tian, Jingshan Pan, Yu Zhang
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引用次数: 1

Abstract

The open-source fluid dynamics software Palabos based on the Lattice Boltzmann Method (LBM) has been widely used in porous media, biological fluids, free interfaces and other physical problems. Palabos has excellent MPI parallel performance and can complete large scale computation of computational fluid dynamics. To realize the heterogeneous parallelism of Palabos, we test the performance of Palabos on a large-scale simulation on a general-purpose cluster at first. The experimental results show that Palabos has a good performance in 16000 MPI processes. Then, we designed a CUDA parallel optimization algorithm for the case of cavity flow according to address mapping and shared memory optimization. Numerical experiments results show that the speedup ratio can achieve about a 1.5x acceleration ratio when the number of the grid is 512×512×512.
基于CUDA的格子玻尔兹曼方法软件Palabos并行性能及优化
基于晶格玻尔兹曼方法(Lattice Boltzmann Method, LBM)的开源流体动力学软件Palabos已广泛应用于多孔介质、生物流体、自由界面等物理问题。Palabos具有优异的MPI并行性能,可以完成计算流体力学的大规模计算。为了实现Palabos的异构并行性,我们首先在一个通用集群上对Palabos进行了大规模仿真测试。实验结果表明,Palabos在16000 MPI过程中具有良好的性能。然后,基于地址映射和共享内存优化,设计了一种针对空腔流情况的CUDA并行优化算法。数值实验结果表明,当网格个数为512×512×512时,加速比可达到1.5倍左右的加速比。
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