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Parallel Computation of the SVD of a Matrix Product

  • Josée M. Claver
  • Manuel Mollar
  • Vicente Hernández
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1697)

Abstract

In this paper we studya parallel algorithm for computing the singular value decomposition (SVD) of a product of two matrices on message passing multiprocessors. This algorithm is related to the classical Golub-Kahan method for computing the SVD of a single matrix and the recent work carried out byGolu b et al. for computing the SVD of a general matrix product/quotient. The experimental results of our parallel algorithm, obtained on a network of PCs and a SUN Enterprise 4000, show high performances and scalabilityfor large order matrices.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Josée M. Claver
    • 1
  • Manuel Mollar
    • 1
  • Vicente Hernández
    • 2
  1. 1.Dpto. de InformáticaUniv. Jaume ICastellónSpain
  2. 2.Dpto. de Sistemas Informáticos y ComputaciónUniversidad Politécnica de ValenciaValenciaSpain

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