A parallel QR factorization algorithm using local pivoting

This paper presents a new parallel version of the Householder algorithm with column pivoting for computing the QR factorization of a matrix. In contrast to the standard algorithm we employ a local pivoting scheme that allows for efficient implementation of the algorithm on a parallel machine, in par...

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Vydáno v:	Proceedings of the 1988 ACM/IEEE conference on Supercomputing s. 400 - 499
Hlavní autor:	Bischof, C. H.
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	Los Alamitos, CA, USA IEEE Computer Society Press 01.11.1988
Edice:	ACM Conferences
Témata:	Computer systems organization > Architectures > Parallel architectures > Systolic arrays Theory of computation > Design and analysis of algorithms
ISBN:	9780818608827, 081860882X
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Popis
Shrnutí:	This paper presents a new parallel version of the Householder algorithm with column pivoting for computing the QR factorization of a matrix. In contrast to the standard algorithm we employ a local pivoting scheme that allows for efficient implementation of the algorithm on a parallel machine, in particular one with a distributed architecture. An inexpensive but reliable incremental condition estimator is used to control the selection of pivot columns by obtaining cheap estimates for the smallest singular value of the currently created upper triangular matrix R. Numerical experiments show that the local pivoting strategy behaves about as well as the traditional global pivoting strategy. They also show the advantages of incorporating the controlled pivoting strategy into the traditional QR algorithm to guard against the known pathological cases.
Bibliografie:	SourceType-Conference Papers & Proceedings-1 ObjectType-Conference Paper-1 content type line 25
ISBN:	9780818608827 081860882X
DOI:	10.5555/62972.63023