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Parallel Model Reduction of Large Linear Descriptor Systems via Balanced Truncation

  • Peter Benner
  • Enrique S. Quintana-Ortí
  • Gregorio Quintana-Ortí
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3402)

Abstract

In this paper we investigate the use of parallel computing to deal with the high computational cost of numerical algorithms for model reduction of large linear descriptor systems. The state-space truncation methods considered here are composed of iterative schemes which can be efficiently implemented on parallel architectures using existing parallel linear algebra libraries. Our experimental results on a cluster of Intel Pentium processors show the performance of the parallel algorithms.

Keywords

Model reduction balanced truncation linear descriptor systems parallel algorithms 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Peter Benner
    • 1
  • Enrique S. Quintana-Ortí
    • 2
  • Gregorio Quintana-Ortí
    • 2
  1. 1.Fakultät für MathematikTechnische Universität ChemnitzChemnitzGermany
  2. 2.Depto. de Ingeniería y Ciencia de ComputadoresUniversidad Jaume ICastellónSpain

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