Applied Mathematics and Mechanics (English Edition) ›› 2004, Vol. 25 ›› Issue (9): 1012-1021.

• 论文 • 上一篇    下一篇

AINV AND BILUM PRECONDITIONING TECHNIQUES

谷同祥1,2, 迟学斌2, 刘兴平1   

  1. 1. Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, P.O. Box 8009, Beijing 100088, P. R. China;
    2. Supercomputing Center of Computer Network Information Center, Chinese Academy of Science, P.O. Box 349, Beijing 100080, P. R. China
  • 收稿日期:2002-05-28 修回日期:2004-03-30 出版日期:2004-09-18 发布日期:2004-09-18
  • 基金资助:

    the National Natural Science Foundation of China(60373015);the State Hi Tech Research and Development Program of China(2001AA111043);the Foundation of State Key Labora tory of Computational Physics

AINV AND BILUM PRECONDITIONING TECHNIQUES

GU Tong-xiang1,2, CHI Xue-bin2, LIU Xing-ping1   

  1. 1. Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, P.O. Box 8009, Beijing 100088, P. R. China;
    2. Supercomputing Center of Computer Network Information Center, Chinese Academy of Science, P.O. Box 349, Beijing 100080, P. R. China
  • Received:2002-05-28 Revised:2004-03-30 Online:2004-09-18 Published:2004-09-18
  • Supported by:

    the National Natural Science Foundation of China(60373015);the State Hi Tech Research and Development Program of China(2001AA111043);the Foundation of State Key Labora tory of Computational Physics

摘要: It was proposed that a robust and efficient parallelizable preconditioner for solving general sparse linear systems of equations, in which the use of sparse approximate inverse (AINV) techniques in a multi-level block ILU (BILUM) preconditioner were investigated. The resulting preconditioner retains robustness of BILUM preconditioner and has two advantages over the standard BILUM preconditioner: the ability to control sparsity and increased parallelism. Numerical experiments are used to show the effectiveness and efficiency of the new preconditioner.

关键词: sparse matrix, preconditioning technique, BILUM, AINV, Krylov subspace method

Abstract: It was proposed that a robust and efficient parallelizable preconditioner for solving general sparse linear systems of equations, in which the use of sparse approximate inverse (AINV) techniques in a multi-level block ILU (BILUM) preconditioner were investigated. The resulting preconditioner retains robustness of BILUM preconditioner and has two advantages over the standard BILUM preconditioner: the ability to control sparsity and increased parallelism. Numerical experiments are used to show the effectiveness and efficiency of the new preconditioner.

Key words: sparse matrix, preconditioning technique, BILUM, AINV, Krylov subspace method

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