Systolic givens factorization of dense rectangular matrices

Given an m by n dense matrix A(m≧n) we consider parallel algorithms to compute its orthogonal factorization via Givens rotations. First we describe an algorithm which is executed in m+n- 2 steps on a linear array of [m/2] processors, a step being the time necessary to achieve a Givens rotation. The...

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Veröffentlicht in:International journal of computer mathematics Jg. 25; H. 3-4; S. 287 - 298
Hauptverfasser: Cosnard, Michel, Robert, Yves
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Gordon and Breach Science Publishers 01.01.1988
Taylor and Francis
Taylor & Francis
Schlagworte:
Algorithmics. Computability. Computer arithmetics
Applied sciences
B.7.1 [Integrated circuits]
Computer Science
Computer science; control theory; systems
Distributed, Parallel, and Cluster Computing
Exact sciences and technology
F.2.1 [Analysis of algorithms and problem complexity]
F.l.l [Computation by abstract devices]
Givens rotations
linear least squares problems
Models fo Computation-Systolic array
Numerical algorithms and problems-QR decomposition of a dense matrix
QR factorization
Systolic algorithms
Theoretical computing
Types and design styles-Algorithms implemented in hardware
VLSI
VLSI architectures
Numerical analysis
VLSI circuit
Least squares method
Parallel processing
Systolic network
Algorithm
Factorization
Implementation
ISSN:0020-7160, 1029-0265
Online-Zugang:Volltext
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Zusammenfassung:Given an m by n dense matrix A(m≧n) we consider parallel algorithms to compute its orthogonal factorization via Givens rotations. First we describe an algorithm which is executed in m+n- 2 steps on a linear array of [m/2] processors, a step being the time necessary to achieve a Givens rotation. The pipelined version of the new algorithm leads to a systolic implementation whose area-time performances overcome those of the arrays of Bojanczyk, Brent and Kung [1] and Gentleman and Kung [5].
ISSN:0020-7160
1029-0265
DOI:10.1080/00207168808803674