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GPU accelerated three dimensional unstructured geometric multigrid solver

机译:GPU加速三维非结构化几何多重求解器

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Graphics processor units (GPUs) have started becoming an integral part of high performance computing. We develop a GPU based 3D-unstructured geometric multigrid solver, which is extensively used in Computational Fluid Dynamics (CFD) applications. Parallelization for GPUs is not straightforward because of the irregularity of the mesh. Using combination of graph coloring and greedy maximal independent set computations, we obtain significant performance improvements in the multigrid solver and its parallelization. We use NVIDIAs CUDA programming model for the implementation. In our experiments, we solve heat conduction problems on unstructured 3D meshes. Different schemes for implementing the multigrid algorithm are evaluated. For a mesh of size 1.6 million, our multigrid GPU implementation gives 24 times speed up compared to multigrid serial implementation and 1630 times speed up compared to non-multigrid serial implementation.
机译:图形处理器单元(GPU)已开始成为高性能计算的一个组成部分。我们开发基于GPU的3D非结构化几何多重求解器,其广泛用于计算流体动力学(CFD)应用。由于网眼的不规则性,GPU的并行化并不直接。使用图形着色和贪婪的最大独立设置计算的组合,我们在多重形求解器及其并行化中获得了显着的性能改进。我们使用NVIDIAS CUDA编程模型进行实现。在我们的实验中,我们解决了非结构化3D网格的热传导问题。评估用于实现多输入算法的不同方案。对于大小为160万的网格,我们的MultiGridGPU实现与Multigrid串行实现相比,与非多重资源串行实现相比,加速了24倍加速。

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