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Parallel Computation of Meshfree Methods for Extremely Large Deformation Analysis

In: Current Trends in High Performance Computing and Its Applications

Author

Listed:
  • Jifa Zhang

    (Zhejiang University, Center for Engineering and Scientific Computation, and College of Computer Science)

  • Yao Zheng

    (Zhejiang University, Center for Engineering and Scientific Computation, and College of Computer Science)

Abstract

Due to the heavier computation requirement than other competitive techniques and the essence of applications that are usually highly complex and computationally intensive, parallel computing is especially attractive for these meshfree methods.We only focus on the Reproducing Kernel Particle Method (RKPM), one of the meshfree methods for large strain elasto-plastic analysis of solid and structures, in considering with its ability to accurately model extremely large deformations without mesh distortion problems, and its ease of adaptive modeling by simply changing particle definitions for desired refinement regions. The parallel procedure primarily consists of a mesh partitioning pre-analysis phase, and a parallel analysis phase that includes explicit message passing among partitions on individual processors. With redefinition techniques applied to the shared zones of different geometrical parts, the graph-based procedure Metis, which is quite popular for mesh-based analysis, is used for partitioning in this meshfree analysis. Parallel simulations have been conducted on an SGI Onyx3900 supercomputer with MPI message passing statements. The effectiveness and performance with different partitions has then been compared, and a comparison of the meshfree method with finite element methods is also presented.

Suggested Citation

  • Jifa Zhang & Yao Zheng, 2005. "Parallel Computation of Meshfree Methods for Extremely Large Deformation Analysis," Springer Books, in: Wu Zhang & Weiqin Tong & Zhangxin Chen & Roland Glowinski (ed.), Current Trends in High Performance Computing and Its Applications, pages 599-603, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-27912-9_84
    DOI: 10.1007/3-540-27912-1_84
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