Orthogonal reduction of dense matrices to bidiagonal form on computers with distributed memory architectures

In this paper, we describe a parallel implementation for the blocked reduction of dense matrices to bidiagonal form by Householder transformations. The method is based on the idea of using un-normed reflector vector. Results from experiments on the Intel Paragon are given. Comparison between the Sca...

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Published in:Parallel computing Vol. 24; no. 2; pp. 305 - 313
Main Author: Kuznetsov, S.V.
Format: Journal Article
Language:English
Published: Elsevier B.V 01.02.1998
Subjects:
ISSN:0167-8191, 1872-7336
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Abstract In this paper, we describe a parallel implementation for the blocked reduction of dense matrices to bidiagonal form by Householder transformations. The method is based on the idea of using un-normed reflector vector. Results from experiments on the Intel Paragon are given. Comparison between the ScaLapack bidiagonalization and the method proposed is provided.
AbstractList In this paper, we describe a parallel implementation for the blocked reduction of dense matrices to bidiagonal form by Householder transformations. The method is based on the idea of using un-normed reflector vector. Results from experiments on the Intel Paragon are given. Comparison between the ScaLapack bidiagonalization and the method proposed is provided.
Author Kuznetsov, S.V.
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Cites_doi 10.1007/3-540-60902-4_12
10.1137/0908009
10.1017/S096249290000235X
10.1007/978-94-011-1952-8
10.1016/0167-8191(92)90011-U
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Keywords Bidiagonal form
Distributed memory architecture
Linear algebra
Householder transformation
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Snippet In this paper, we describe a parallel implementation for the blocked reduction of dense matrices to bidiagonal form by Householder transformations. The method...
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SubjectTerms Bidiagonal form
Distributed memory architecture
Householder transformation
Linear algebra
Title Orthogonal reduction of dense matrices to bidiagonal form on computers with distributed memory architectures
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