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Accelerating Physical Simulations from a Multicomponent Lattice Boltzmann Method on a Single-Node Multi-GPU Architecture

机译:在单节点多GPU架构上通过多分量格子Boltzmann方法加速物理仿真

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In this paper, we introduce an efficient method to accelerate flow simulations for an isothermal multiphase and multicomponent (MPMC) Lattice Boltzmann method (LBM) on a single-node multi-GPU architecture. Our objective is to propose an efficient way to improve performance of multiphase and multicomponent Lattice Boltzmann simulations by the use of Nvidia GPUDirect technology and Peer-to-Peer (P2P) data transfers. Optimization of Peer-to-Peer communications is also studied in this work by the use of a clustering algorithm. Several simulations are shown and performance is discussed in order to validate the method.
机译:在本文中,我们介绍了一种在单节点多GPU架构上加速等温多相多组分(MPMC)格子Boltzmann方法(LBM)流动模拟的有效方法。我们的目标是通过使用Nvidia GPUDirect技术和点对点(P2P)数据传输,提出一种提高多相和多分量Lattice Boltzmann仿真性能的有效方法。在这项工作中,还通过使用聚类算法研究了对等通信的优化。为了验证该方法,显示了几个仿真并讨论了性能。

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