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Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/6364
Title: A Systolic Architecture for Almost Linear-Time Solution of the Symmetric Eigenvalue Problem
Authors: Brent, Richard P.
Luk, Franklin T.
Keywords: computer science
technical report
Issue Date: Aug-1982
Publisher: Cornell University
Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR82-525
Abstract: An algorithm is presented for computing the eigenvalues and eigenvectors of an n x n real symmetric matrix. The algorithm is essentially a Jacobi method implemented on a two-dimensional systolic array of $O(n^{2})$ processors with nearest-neighbor communication between processors. The speedup over the serial Jacobi method is $\Theta(n^{2})$, so the algorithm converges to working accuracy in time $O(nS))$, where $S$ is the number of sweeps (typically $S \leq 10)$. Key Words and Phrases: Eigenvalue decomposition, real symmetric matrices, Hermitian matrices, Jacobi method, linear-time computation, systolic arrays, VLSI, real-time computation.
URI: http://hdl.handle.net/1813/6364
Appears in Collections:Computer Science Technical Reports

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