The Solution of Singular-Value and Symmetric Eigenvalue Problems on Multiprocessor Arrays | Zendy

Richard P. Brent | Zendy; Franklin T. Luk | Zendy

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The Solution of Singular-Value and Symmetric Eigenvalue Problems on Multiprocessor Arrays

Author(s) -

Richard P. Brent,

Franklin T. Luk

Publication year - 1985

Publication title -

siam journal on scientific and statistical computing

Language(s) - English

Resource type - Journals

eISSN - 2168-3417

pISSN - 0196-5204

DOI - 10.1137/0906007

Subject(s) - eigenvalues and eigenvectors , singular value decomposition , mathematics , singular value , multiprocessing , matrix (chemical analysis) , divide and conquer eigenvalue algorithm , square (algebra) , jacobi method , value (mathematics) , combinatorics , symmetric matrix , algorithm , parallel computing , computer science , geometry , physics , statistics , quantum mechanics , materials science , composite material

Parallel Jacobi-like algorithms are presented for computing a singular-value decomposition of an m ◊ n matrix (m n) and an eigenvalue decomposition of an n ◊ n symmetric matrix. A linear array of O(n) processors is proposed for the singular-value problem; the associated algorithm requires time O(mnS), where S is the number of sweeps (typically S 10). A square array of O(n2) processors with nearest-neighbour communication is proposed for the eigenvalue

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