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.
Author: | Peter Benner, Enrique S. Quintana-Ortí, Gregorio Quintana-Ortí |
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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 |