By Topic

On the Schur Decomposition of a Matrix for Parallel Computation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Eberlein, P.J. ; Department of Computer Science, State University of New York

An algorithm to solve the eigenproblem for nonsymmetric matrices on an N × N array of mesh-connected processors, isomorphic to the architecture described by Brent and Luk for symmetric matrices, is presented. This algorithm is a generalization of the classical Jacobi method, and, as such, holds promise for parallel architectures. The rotational parameters for the nonsymmetric case are carefully analyzed; many examples of a working program, simulating the parallel architecture, are given with experimental evidence of quadratic convergence.

Published in:

Computers, IEEE Transactions on  (Volume:C-36 ,  Issue: 2 )