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Parallel implementation of a symmetric eigensolver based on the Yau and Lu method

  • Stéphane Domas
  • Françoise Tisseur
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1215)

Abstract

In this paper, we present preliminary results on a complete eigensolver based on the Yau and Lu method. We first give an overview of this invariant subspace decomposition method for dense symmetric matrices followed by numerical results and work in progress of a distributed-memory implementation. We expect that the algorithm's heavy reliance on matrix-matrix multiplication, coupled with FFT should yield a highly parallelizable algorithm. We present performance results for the dominant computation kernel on the Intel Paragon.

Keywords

Invariant Subspace Triangular Part Parallel Level Symmetric Eigenvalue Problem Linear Algebra Library 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Stéphane Domas
    • 1
  • Françoise Tisseur
    • 2
  1. 1.Laboratoire de l'Informatique du ParallélismeURA 1398 du CNRS and INRIA Rhône-AlpesLyon Cedex 07France
  2. 2.Equipe d'Analyse Numérique de St-EtienneUMR 5585Saint-EtienneFrance

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