一种新版本共轭梯度法的并行实现

R. Bycul, A. Jordan, M. Cichomski
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引用次数: 13

摘要

在本文中,作者描述了在异构PC集群和超级计算机日立SR-2201上并行实现共轭梯度方法的思想。新版本的算法实现与之前使用的版本(Jordan and Bycul, 2002)不同,因为它使用了一种特殊的方法来存储稀疏系数矩阵:在计算过程中只存储和考虑非零元素,从而充分利用了系数矩阵的稀疏性。这篇文章对这两个版本进行了比较。在求解不同物理问题时,对系数矩阵的三种不同情况下并行算法的加速进行了检验。本文还研究了一种用系数矩阵的反对角线作为预处理矩阵的预处理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new version of conjugate gradient method parallel implementation
In the article the authors describe an idea of parallel implementation of a conjugate gradient method in a heterogeneous PC cluster and a supercomputer Hitachi SR-2201. The new version of algorithm implementation differs from the one applied earlier (Jordan and Bycul, 2002), because it uses a special method for storing sparse coefficient matrices: only non-zero elements are stored and taken into account during computations, so that the sparsity of the coefficient matrix is taken full advantage of. The article includes a comparison of the two versions. A speedup of the parallel algorithm has been examined for three different cases of coefficient matrices resulting in solving different physical problems. The authors have also investigated a preconditioning method, which uses the inversed diagonal of the coefficient matrix, as a preconditioning matrix.
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