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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/6402
Title: The Solution of Singular-Value and Symmetric Eigenvalue Problems on Multiprocessor Arrays
Authors: Brent, Richard P.
Luk, Franklin T.
Keywords: computer science
technical report
Issue Date: Jul-1983
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR83-562
Abstract: Parallel Jacobi-like algorithms are presented for computing a singular-value decomposition of an $mxn$ matrix $(m \geq n)$ and an eigenvalue decomposition of an $n x n$ symmetric matrix. A linear array of $O(n)$ processors is proposed for the singular-value problem and the associated algorithm requires time $O(mnS)$, where $S$ is the number of sweeps (typically $S \leq 10)$. A square array of $O(n^{2})$ processors with nearest-neighbor communication is proposed for the eigenvalue problem; the associated algorithm requires time $O(nS)$. Key Words And Phrases: Multiprocessor arrays, systolic arrays, singular-value decomposition, eigenvalue decomposition, real symmetric matrices, Hestenes method, Jacobi method, VLSI, real-time computation, parallel algorithms.
URI: http://hdl.handle.net/1813/6402
Appears in Collections:Computer Science Technical Reports

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