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Efficient computation of sparse approximate inverses

✍ Scribed by Thomas K. Huckle

Publisher: John Wiley and Sons
Year: 1998
Tongue: English
Weight: 101 KB
Volume: 5
Category: Article
ISSN: 1070-5325
DOI: 10.1002/(sici)1099-1506(199801/02)5:1<57::aid-nla129>3.0.co;2-c

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✦ Synopsis

We investigate different methods for computing a sparse approximate inverse M for a given sparse matrix A by minimizing AM -E in the Frobenius norm. Such methods are very useful for deriving preconditioners in iterative solvers, especially in a parallel environment. We compare different strategies for choosing the sparsity structure of M and different ways for solving the small least squares problem that are related to the computation of each column of M. Especially we show how we can take full advantage of the sparsity of A.

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