Finding eigenvalues and eigenvectors of unsymmetric matrices using a distributed-memory multiprocessor☆
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Cited by (11)
Parallel algorithms for reduction of a symmetric matrix to tridiagonal form on a shared memory multiprocessor
2005, Applied Mathematics and ComputationParallel algorithms for reduction of a general matrix to upper Hessenberg form on a shared memory multiprocessor
2005, Applied Mathematics and ComputationHigh performance parallelization scheme for the Hessenberg double shift QR algorithm
1999, Parallel ComputingReduction to condensed form for the Eigenvalue problem on distributed memory architectures
1992, Parallel ComputingA parallel implementation of the nonsymmetric QR algorithm for distributed memory architectures
2003, SIAM Journal on Scientific ComputingA novel parallel QR algorithm for hybrid distributed memory HPC systems
2010, SIAM Journal on Scientific Computing
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Research was supported by the Applied Mathematical Sciences Research Program of the Office of Energy Research, U.S. Department of Energy.
Copyright © 1990 Published by Elsevier B.V.