Parallel processing with the Wind CFD code at Boeing

Fisher, Mark; Mani, Mori; Stookesberry, D.

doi:10.1016/s0167-8191(00)00069-7

Cited by 6 publications

(1 citation statement)

References 2 publications

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“…Therefore the processor, which has the maximum number of cells, will spend a lot of time on the iteration computing, and the other processors have to wait for it with a long idle time. It is unacceptable especially for the large-scale high-performance parallel computing [20].…”

Section: Performance Dealing With Massive Mesh On Hpcmentioning

confidence: 99%

Large-Scale CFD Parallel Computing Dealing with Massive Mesh

Shang

2013

Journal of Engineering

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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.

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Section: Performance Dealing With Massive Mesh On Hpcmentioning

confidence: 99%