Gauss-Jordan inversion with pivoting on the Caltech Mark II hypercube

P. Hipes, A. Kuppermann
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引用次数: 20

Abstract

The performance of a parallel Gauss-Jordan matrix inversion1,2 algorithm on the Mark II hypercube3 at Caltech is discussed. We will show that parallel Gauss-Jordan inversion is superior to parallel Gaussian elimination for inversion, and discuss the reasons for this. Empirical and theoretical efficiencies for parallel Gauss-Jordan inversion as a function of matrix dimension for different numbers and configurations of processors are presented. The theoretical efficiencies are in quantitative agreement with the empirical efficiencies.
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Caltech Mark II超立方体上具有旋转的高斯-乔丹反演
讨论了一种并行高斯-乔丹矩阵反演算法在加州理工学院Mark II超立方体计算机上的性能。我们将证明并行高斯-乔丹反演优于并行高斯消去反演,并讨论其原因。给出了不同处理器数量和配置下并行高斯-约当反演的经验效率和理论效率与矩阵维数的关系。理论效率与实证效率在数量上是一致的。
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