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Parallel Computing for Linear Systems of Equations on Workstation Clusters

In: Current Trends in High Performance Computing and Its Applications

Author

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  • Chaojiang Fu

    (Shanghai University, School of Computer Engineering and Science
    Nanchang University, School of Architectural Engineering)

  • Wu Zhang

    (Shanghai University, School of Computer Engineering and Science)

  • Linfeng Yang

    (Shanghai University, School of Computer Engineering and Science)

Abstract

In this paper the parallel algorithm of preconditioned conjugate gradient method (PCGM) is presented and implemented on DELL workstation cluster. Optimization techniques for the sparse matrix vector multiplication are adopted in programming. The storage schemes are analyzed in detail. The numerical results show that the designed parallel algorithm has good parallel performance on the high performance workstation cluster. This illustrates the power of parallel computing in solving large-scale problems much faster than on a single processor.

Suggested Citation

  • Chaojiang Fu & Wu Zhang & Linfeng Yang, 2005. "Parallel Computing for Linear Systems of Equations on Workstation Clusters," Springer Books, in: Wu Zhang & Weiqin Tong & Zhangxin Chen & Roland Glowinski (ed.), Current Trends in High Performance Computing and Its Applications, pages 289-293, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-27912-9_33
    DOI: 10.1007/3-540-27912-1_33
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