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Large-Scale CFD Parallel Computing Dealing with Massive Mesh

机译:处理大规模网格的大规模CFD并行计算

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In order to run CFD codes more efficiently on large scales, the parallel computing has to be employed. For example, in industrial scales, it usually uses tens of thousands of mesh cells to capture the details of complex geometries. How to distribute these mesh cells among the multiprocessors for obtaining a good parallel computing performance (HPC) is really a challenge. Due to dealing with the massive mesh cells, it is difficult for the CFD codes without parallel optimizations to handle this kind of large-scale computing. Some of the open source mesh partitioning software packages, such as Metis, ParMetis, Scotch, PT-Scotch, and Zoltan, are able to deal with the distribution of large number of mesh cells. Therefore they were employed as the parallel optimization tools ported into Code_Saturne, an open source CFD code, for testing if they can solve the issue of dealing with massive mesh cells for CFD codes. Through the studies, it was found that the mesh partitioning optimization software packages can help CFD codes not only deal with massive mesh cells but also have a good HPC.
机译:为了大规模高效地运行CFD代码,必须采用并行计算。例如,在工业规模中,它通常使用成千上万个网格单元来捕获复杂几何图形的细节。如何在多处理器之间分配这些网格单元以获得良好的并行计算性能(HPC)确实是一个挑战。由于要处理庞大的网格单元,没有并行优化的CFD代码很难处理这种大规模计算。一些开源网格划分软件包,例如Metis,ParMetis,Scotch,PT-Scotch和Zoltan,能够处理大量网格单元的分布。因此,它们被用作移植到开源CFD代码Code_Saturne中的并行优化工具,用于测试它们是否可以解决针对CFD代码处理大型网格单元的问题。通过研究发现,网格划分优化软件包不仅可以帮助CFD代码处理大量网格单元,而且还具有良好的HPC。

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