Factorized Sparse Approximate Inverses for Preconditioning.

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Bibliographic Details
Title: Factorized Sparse Approximate Inverses for Preconditioning.
Authors: Huckle, Thomas1 huckle@in.tum.de
Source: Journal of Supercomputing. Jun2003, Vol. 25 Issue 2, p109-117. 9p.
Subjects: Sparse matrix software, Sparse matrices, Matrices (Mathematics), Algorithms
Abstract: In recent papers the use of sparse approximate inverses for the preconditioning of linear equations Ax=b is examined. The minimization of ||AM-I|| in the Frobenius norm generates good preconditioners without any a priori knowledge on the pattern of M. For symmetric positive definite A and a given a priori pattern there exist methods for computing factorized sparse approximate inverses L with LLT≈A-;1. Here, we want to modify these algorithms that they are able to capture automatically a promising pattern for L. We use these approximate inverses for solving linear equations with the cg-method. Furthermore we introduce and test modifications of this method for computing factorized sparse approximate inverses. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:In recent papers the use of sparse approximate inverses for the preconditioning of linear equations Ax=b is examined. The minimization of ||AM-I|| in the Frobenius norm generates good preconditioners without any a priori knowledge on the pattern of M. For symmetric positive definite A and a given a priori pattern there exist methods for computing factorized sparse approximate inverses L with LLT≈A-;1. Here, we want to modify these algorithms that they are able to capture automatically a promising pattern for L. We use these approximate inverses for solving linear equations with the cg-method. Furthermore we introduce and test modifications of this method for computing factorized sparse approximate inverses. [ABSTRACT FROM AUTHOR]
ISSN:09208542
DOI:10.1023/A:1023988426844