Parallel stochastic estimation method of eigenvalue distribution

Some kinds of eigensolver for large sparse matrices require specification of parameters that are based on rough estimates of the desired eigenvalues. In this paper, we propose a stochastic estimation method of eigenvalue distribution using the combination of a stochastic estimator of the matrix trac...

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Bibliographic Details
Published inJSIAM Letters Vol. 2; pp. 127 - 130
Main Authors Futamura, Yasunori, Tadano, Hiroto, Sakurai, Tetsuya
Format Journal Article
LanguageEnglish
Published The Japan Society for Industrial and Applied Mathematics 2010
Subjects
contour integration
eigenproblem
stochastic estimation
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Summary:Some kinds of eigensolver for large sparse matrices require specification of parameters that are based on rough estimates of the desired eigenvalues. In this paper, we propose a stochastic estimation method of eigenvalue distribution using the combination of a stochastic estimator of the matrix trace and contour integrations. The proposed method can be easily parallelized and applied to matrices for which factorization is infeasible. Numerical experiments are executed to show that the method can perform rough estimates at a low computational cost.
ISSN:1883-0609
1883-0617
DOI:10.14495/jsiaml.2.127