The Impact of the Mesh Partitioning Factors on CFD Simulation

  • Chen Cui
  • Juan Chen
  • Feihao Wu
  • Miao Wang
  • Yuyang Sun
  • Xinhai Xu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 768)

Abstract

Mesh partitioning plays an important role in Computational Fluid Dynamics (CFD) simulation. However, it is difficult to produce a good mesh partitioning to achieve a high performance simulation because it is a NP-complete problem to solve this problem. A good mesh partitioning may be determined by many factors. Nowadays, there is a lack of systematic guidelines and comprehensive analyses for how to produce a high quality mesh partitioning. Considering that it is difficult to break through in theory, we prefer to explore how the factors related to mesh partitioning influence CFD simulation based on a large amount of experimental analyses. In this paper, we evaluate the impact of changing the mesh partitioning factors on mesh partitioning quality and simulation performance according to the following five factors: the number of processor faces, subdomain aspect ratio, load, partitioning direction and mapping. We design a series of rules to make various and numerous mesh partitioning changes based on four commonly used methods (Simple, Metis, Scotch and Manual) in OpenFOAM. Furthermore, we conduct the parallel simulation for two representative cases (cavity case and damBreak case) in OpenFOAM framework. The experimental results certify that changing mesh partitioning factors really influences the simulation performance. Then we provide some analyses and advices, which will definitely be helpful to guide mesh partitioning in the future.

Keywords

Mesh partitioning CFD simulation Mesh partitioning quality Simulation performance 

Notes

Acknowledgements

The authors would like to thank to the funding from the National Natural Science Foundation of China under grant No.61221491, No.61303071, No.61303068, No.61303063, No.61303061 and No.61120106005, and Open Fund (No. 201402-01, No.201503-01 and No.201503-02) from State Key Laboratory of High Performance Computing.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Chen Cui
    • 1
  • Juan Chen
    • 1
  • Feihao Wu
    • 1
  • Miao Wang
    • 1
  • Yuyang Sun
    • 2
  • Xinhai Xu
    • 1
  1. 1.State Key Laboratory of High Performance Computing, College of ComputerNational University of Defense TechnologyChangshaChina
  2. 2.College of ComputerNational University of Defense TechnologyChangshaChina

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