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Remote Parallel Model Reduction of Linear Time-Invariant Systems Made Easy

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Book cover High Performance Computing for Computational Science — VECPAR 2002 (VECPAR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2565))

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Abstract

This paper describes a library for model reduction of largescale, dense linear time-invariant systems on parallel distributed-memory computers. Our library is enhanced with a mail service which serves as a demonstrator of the capabilities of the library. Remote requests submitted via e-mail are executed on a cluster composed of Intel Pentium-II nodes connected via a Myrinet switch. Experimental results show the numerical and parallel performances of our model reduction routines.

Supported by the Fundació Caixa-Castelló/Bancaixa PI-1B2001-14 and CICYT TIC2002-04400-C03-01.

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Author information

Authors and Affiliations

  1. Institut für Mathematik, Technische Universität Berlin, D-10623, Berlin, Germany

    Peter Benner

  2. Depto. de Ingeniería y Ciencia de Computadores, Universidad Jaume I, 12071, Castellón, Spain

    Rafael Mayo, Enrique S. Quintana-Ortí & Gregorio Quintana-Ortí

Authors
  1. Peter Benner
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  2. Rafael Mayo
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  3. Enrique S. Quintana-Ortí
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  4. Gregorio Quintana-Ortí
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Editor information

Editors and Affiliations

  1. Faculdade de Engenharia da, Universidade do Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    José M. L. M. Palma  & A. Augusto Sousa  & 

  2. Department of Computer Science, University of Tennessee, 37996-1301, Knoxville, TN, USA

    Jack Dongarra

  3. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera, s/n, Apartado 22012, 46020, Valencia, Spain

    Vicente Hernández

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© 2003 Springer-Verlag Berlin Heidelberg

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Benner, P., Mayo, R., Quintana-Ortí, E.S., Quintana-Ortí, G. (2003). Remote Parallel Model Reduction of Linear Time-Invariant Systems Made Easy. In: Palma, J.M.L.M., Sousa, A.A., Dongarra, J., Hernández, V. (eds) High Performance Computing for Computational Science — VECPAR 2002. VECPAR 2002. Lecture Notes in Computer Science, vol 2565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36569-9_16

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  • DOI: https://doi.org/10.1007/3-540-36569-9_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00852-1

  • Online ISBN: 978-3-540-36569-3

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