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Local block factorization and its parallelization to block tridiagonal matrices

机译:局部块分解及其并行化以阻止三角形矩阵

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A type of incomplete decomposition preconditioner based on local block factorization is considered, for the matrices derived from discreting 2-D or 3-D elliptic partial differential equations. We prove that the condition numbers of the preconditioned matrices are small, which means that the constructed preconditioners are effective. Further we consider an efficient parallel version of the preconditioner which depends only on a single integer argument. When its value is small, the iterations needed on multiple processors to converge is much more than on a single processor. But with the increase of this value, the difference decreases step by step. Finally, we have many experiments on a cluster of 6 PCs with main frequencies of 1.8GHz The results show that the local block factorizations constructed are efficient in serial implementation, f compared to some well-known effective preconditioners, and the parallel versions are efficient also.
机译:考虑基于局部块分子的基于局部块分子的非完全分解预处理器,对于来自离散的2-D或3-D椭圆部分微分方程的矩阵。我们证明预处理矩阵的条件数量很小,这意味着构造的预处理器是有效的。此外,我们考虑一个有效的precetitcher的并行版本,只依赖于单个整数参数。当其值很小时,多个处理器所需的迭代远远超过单个处理器。但随着这个值的增加,差异逐步减少。最后,我们在6个PC的集群中有许多实验,主频率为1.8GHz,结果表明,与某些众所周知的有效预处理器相比,构造的局部块因子在串行实现中是有效的,并且并行版本也很有效。

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