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Acceleration of Wind Simulation Using Locally Mesh-Refined Lattice Boltzmann Method on GPU-Rich Supercomputers

机译:在富含GPU的超级计算机上使用局部网格划分的格子Boltzmann方法加速风仿真

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A real-time simulation of the environmental dynamics of radioactive substances is very important from the viewpoint of nuclear security. Since airflows in large cities are turbulent with Reynolds numbers of several million, large-scale CFD simulations are needed. We developed a CFD code based on the adaptive mesh-refined Lattice Boltzmann Method (AMR-LBM). AMR method arranges fine grids in a necessary region, so that we can realize a high-resolution analysis including a global simulation area. The code is developed on the GPU-rich supercomputer TSUBAME3.0 at the Tokyo Tech, and the GPU kernel functions are tuned to achieve high performance on the Pascal GPU architecture. The code is validated against a wind tunnel experiment which was released from the National Institute of Advanced Industrial Science and Technology in Japan Thanks to the AMR method, the total number of grid points is reduced to less than 10% compared to the fine uniform grid system. The performances of weak scaling from 1 nodes to 36 nodes are examined. The GPUs (NVIDIA TESLA P100) achieved more than 10 times higher node performance than that of CPUs (Broadwell).
机译:从核安全的角度来看,放射性物质环境动力学的实时仿真非常重要。由于大城市的气流湍流,雷诺数为数百万,因此需要进行大规模CFD模拟。我们基于自适应网格细化的格子Boltzmann方法(AMR-LBM)开发了CFD代码。 AMR方法在必要的区域中排列精细的网格,从而可以实现包括全局模拟区域的高分辨率分析。该代码是在Tokyo Tech的具有丰富GPU的超级计算机TSUBAME3.0上开发的,并且对GPU内核功能进行了调整,以在Pascal GPU架构上实现高性能。该代码是根据日本国立先进工业科学技术研究所发布的风洞实验进行验证的。由于采用了AMR方法,与精细均匀的网格系统相比,网格点的总数减少到了不到10% 。研究了从1个节点到36个节点的弱缩放性能。 GPU(NVIDIA TESLA P100)的节点性能是CPU(Broadwell)的十倍以上。

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