合并Jacobi和Gauss-Seidel方法求解计算机集群上的马尔可夫链

2008 International Multiconference on Computer Science and Information Technology Pub Date : 2008-10-01 DOI:10.1109/IMCSIT.2008.4747250

J. Bylina, B. Bylina

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引用次数: 10

摘要

作者考虑在计算机集群上使用并行迭代方法求解由马尔可夫链引起的大型稀疏线性方程组。在一个并行的版本中，研究了Jacobi和Gauss-Seidel迭代方法的组合。本文报道了由拥塞控制机制的马尔可夫模型得到的具有3 × 107个方程和2 × 108个非零的稀疏系统的一些实验结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Merging Jacobi and Gauss-Seidel methods for solving Markov chains on computer clusters

The authors consider the use of the parallel iterative methods for solving large sparse linear equation systems resulting from Markov chains-on a computer cluster. A combination of Jacobi and Gauss-Seidel iterative methods is examined in a parallel version. Some results of experiments for sparse systems with over 3 times 107 equations and about 2 times 108 nonzeros which we obtained from a Markovian model of a congestion control mechanism are reported.

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2008 International Multiconference on Computer Science and Information Technology

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