Parallel Algorithms for Balanced Truncation Model Reduction of Sparse Systems

  • José M. Badía
  • Peter Benner
  • Rafael Mayo
  • Enrique S. Quintana-Ortí
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3732)

Abstract

We describe the parallelization of an efficient algorithm for balanced truncation that allows to reduce models with state-space dimension up to \(\mathcal{O}(10^5)\). The major computational task in this approach is the solution of two large-scale sparse Lyapunov equations, performed via a coupled LR-ADI iteration with (super-)linear convergence. Experimental results on a cluster of Intel Xeon processors illustrate the efficacy of our parallel model reduction algorithm.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

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

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