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http://worldcat.org/entity/work/id/3417483

The solution of singular-value and symmetric eigenvalue problems on multiprocessor arrays

Parallel Jacobi-like algorithms are presented for computing a singular-value decomposition of an $mxn$ matrix $(m \geq n)$ and an eigenvalue decomposition of an $n x n$ symmetric matrix. A linear array of $O(n)$ processors is proposed for the singular-value problem and the associated algorithm requires time $O(mnS)$, where $S$ is the number of sweeps (typically $S \leq 10)$. A square array of $O(n[superscript]{2})$ processors with nearest-neighbor communication is proposed for the eigenvalue problem; the associated algorithm requires time $O(nS)$.

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  • "Parallel Jacobi-like algorithms are presented for computing a singular-value decomposition of an $mxn$ matrix $(m \geq n)$ and an eigenvalue decomposition of an $n x n$ symmetric matrix. A linear array of $O(n)$ processors is proposed for the singular-value problem and the associated algorithm requires time $O(mnS)$, where $S$ is the number of sweeps (typically $S \leq 10)$. A square array of $O(n[superscript]{2})$ processors with nearest-neighbor communication is proposed for the eigenvalue problem; the associated algorithm requires time $O(nS)$."@en
  • "Key Words And Phrases: Multiprocessor arrays, systolic arrays, singular-value decomposition, eigenvalue decomposition, real symmetric matrices, Hestenes method, Jacobi method, VLSI, real-time computation, parallel algorithms."@en

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  • "The solution of singular-value and symmetric eigenvalue problems on multiprocessor arrays"
  • "The solution of singular-value and symmetric eigenvalue problems on multiprocessor arrays"@en
  • "The solution of singular-value and symmetric Eigenvalue problems on multiprocessor arrays"

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