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A parallel algorithm for the eigenvalues and eigenvectors for a general complex matrixA new parallel Jacobi-like algorithm is developed for computing the eigenvalues of a general complex matrix. Most parallel methods for this parallel typically display only linear convergence. Sequential norm-reducing algorithms also exit and they display quadratic convergence in most cases. The new algorithm is a parallel form of the norm-reducing algorithm due to Eberlein. It is proven that the asymptotic convergence rate of this algorithm is quadratic. Numerical experiments are presented which demonstrate the quadratic convergence of the algorithm and certain situations where the convergence is slow are also identified. The algorithm promises to be very competitive on a variety of parallel architectures.
Document ID
19920002435
Acquisition Source
Legacy CDMS
Document Type
Contractor Report (CR)
Authors
Shroff, Gautam (Rensselaer Polytechnic Inst. Troy, NY., United States)
Date Acquired
September 6, 2013
Publication Date
June 1, 1989
Subject Category
Computer Programming And Software
Report/Patent Number
NAS 1.26:188854
NASA-CR-188854
RIACS-TR-89-35
Accession Number
92N11653
Funding Number(s)
CONTRACT_GRANT: NCC2-387
CONTRACT_GRANT: N00014-86-K-0610
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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