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Parallel Model Reduction of Large-Scale Linear Descriptor Systems via Balanced Truncation

Please always quote using this URN:urn:nbn:de:0296-matheon-642
  • 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.

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Metadaten
Author:Peter Benner, Enrique S. Quintana-Ortí, Gregorio Quintana-Ortí
URN:urn:nbn:de:0296-matheon-642
Referee:Volker Mehrmann
Document Type:Preprint, Research Center Matheon
Language:English
Date of first Publication:2004/01/28
Release Date:2004/01/28
Preprint Number:53
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