Numerical implementation of the QMR algorithm by using discrete stochastic arithmetic

In each step of the quasi-minimal residual (QMR) method which uses a look-ahead variant of the nonsymmetric Lanczos process to generate basis vectors for the Krylov subspaces induced byA, it is necessary to decide whether to construct the Lanczos vectorsvn+1 andwn+1 as regular or inner vectors. For...

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Veröffentlicht in:Journal of applied mathematics & computing Jg. 17; H. 1-2; S. 457 - 473
Hauptverfasser: Toutounian, Faezeh, Salkuyeh, Davod Khojasteh, Asadi, Bahram
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Dordrecht Springer Nature B.V 01.03.2005
Schlagworte:
Algorithms
Applied mathematics
Arithmetic
Computation
Floating point arithmetic
Mathematical analysis
Mathematical models
Stochastic models
Stochasticity
Studies
Subspaces
Tolerances
Vectors (mathematics)
ISSN:1598-5865, 1865-2085
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Zusammenfassung:In each step of the quasi-minimal residual (QMR) method which uses a look-ahead variant of the nonsymmetric Lanczos process to generate basis vectors for the Krylov subspaces induced byA, it is necessary to decide whether to construct the Lanczos vectorsvn+1 andwn+1 as regular or inner vectors. For a regular step it is necessary thatDk=WkTVk is nonsingular. Therefore, in the floating-point arithmetic, the smallest singular value of matrix Dk,σmin(Dk), is computed and an inner step is performed ifσmin(Dk)<∈, where ∈ is a suitably chosen tolerance. In practice it is absolutely impossible to choose correctly the value of the tolerance ∈. The subject of this paper is to show how discrete stochastic arithmetic remedies the problem of this tolerance, as well as the problem of the other tolerances which are needed in the other checks of the QMR method with the estimation of the accuracy of some intermediate results. Numerical examples are used to show the good numerical properties.
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ISSN:1598-5865
1865-2085
DOI:10.1007/BF02936068