求解线性系统的并行软件包

[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation Pub Date : 1992-10-19 DOI:10.1109/FMPC.1992.234934

C. D. Scarbnick, M. Chang, M. Schultz, A. B. Sherman

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引用次数: 2

摘要

科学计算中出现的一个问题是Ax=b的解，其中A是一个大的稀疏矩阵。求解上述方程的最鲁棒算法之一是共轭梯度法，特别是当与预条件结合使用时。作者讨论了一个新的软件包MP-PCGPAK2，它实现了多指令多数据(MIMD)消息传递体系结构的共轭梯度方法的并行版本。并行实现非常通用，可以应用于非对称或不确定系统(如GMRES、Bi-CGSTAB和QMR)的算法。作者介绍了在1024处理器nCUBE 2和128处理器iPSC/860上的结果，用于正定对称系统，范围从100万到超过1100万变量。

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A parallel software package for solving linear systems

A problem arising in scientific computation is the solution of Ax=b, where A is a large, sparse matrix. One of the most robust algorithms for solving the above equation is the conjugate gradient method, especially when combined with a preconditioner. The authors discuss a new software package, MP-PCGPAK2, that implements a parallel version of the conjugate gradient method for MIMD (multiple-instruction multiple-data), message passing architectures. The parallel implementation is quite general and can be applied to algorithms for nonsymmetric or indefinite systems such as GMRES, Bi-CGSTAB, and QMR. The authors present results on a 1024 processor nCUBE 2, and a 128 processor iPSC/860, for positive definite, symmetric systems ranging from one million to over 11 million variables.<>

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[Proceedings 1992] The Fourth Symposium on the Frontiers of Massively Parallel Computation

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