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

机译:用于多GPU的大涡模拟的并行格子Boltzmann方法

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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 × 10,240 lattices) LES-LBM simulation becomes possible at a low cost, even using double-precision floating point calculation.
机译:为了提高高雷诺数,大涡流动力学的湍流流动仿真效率,提出了一种基于CUDA的多图形处理单元(GPU)的大涡模拟(LES)的格子Boltzmann方法仿真解决方案。我们的解决方案采用“传播后冲突”的格演化方法,并将未对齐的传播阶段置于全局存储器读取过程中。最新的GPU平台允许单个CPU线程控制最多四个并行运行的GPU。为了利用多个GPU,将整个工作集平均划分为多个子域。我们分别实现了Smagorinsky模型和Vreman模型,以验证我们的多GPU解决方案。这两个LES模型具有不同的弛豫时间计算行为,并导致不同的CUDA实现特征。基于Smagorinsky模型的实现比CPU上的顺序实现快190倍,而基于Vreman模型的实现实现了90倍以上的提速。实验结果表明,我们的多GPU解决方案的并行性能可在多个GPU上很好地扩展。因此,即使使用双精度浮点计算,也可以以低成本进行大规模(最多10,240×10,240格)的LES-LBM仿真。

著录项

  • 来源
    《Computing》 |2014年第6期|479-501|共23页
  • 作者单位

    School of Computer Science, Northwestern Polytechnical University, Xi'an, China;

    National Key Laboratory of Science and Technology on Aerodynamics Design and Research, Northwestern Polytechnical University, Xi'an, China;

    National Key Laboratory of Science and Technology on Aerodynamics Design and Research, Northwestern Polytechnical University, Xi'an, China;

    National Key Laboratory for High-efficient Server and Storage Technology, Inspur, Jinan, China;

    National Key Laboratory for High-efficient Server and Storage Technology, Inspur, Jinan, China;

    National Key Laboratory for High-efficient Server and Storage Technology, Inspur, Jinan, China;

    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China;

    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China,Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Hong Kong, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Lattice Boltzmann method; GPU Computing; Large eddy simulation; CUDA;

    机译:格子波尔兹曼法GPU计算大涡模拟;卡达;

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