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Parallelization of Neural Networks Using PVM

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Book cover Recent Advances in Parallel Virtual Machine and Message Passing Interface (EuroPVM/MPI 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1908))

Abstract

We use Neural Networks (NN) in order to design control architectures for autonomous mobile robots. With PVM, it is possible to spawn different parts of a NN on different workstations. Specific message passing functions using PVM are included into the NN architecture. A graphical interface helps the user spawning the NN architecture and monitors the messages exchanged between the different subparts of the NN. The message passing mechanism is efficient for real time applications. We show an example of image processing used for robot control.

Current version used is PVM 3.4.3 for Solaris and Linux

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Author information

Authors and Affiliations

  1. Université de Cergy-Pontoise - ETIS, 6, av. du Ponceau, 95014, Cergy-Pontoise Cédex, France

    Mathias Quoy, Sorin Moga & Philippe Gaussier

  2. Ecole Nationale Supérieure de l’Electronique et de ses Applications - ETIS, France

    Arnaud Revel

Authors
  1. Mathias Quoy
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  2. Sorin Moga
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  3. Philippe Gaussier
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  4. Arnaud Revel
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Editor information

Editors and Affiliations

  1. Innovative Computing Lab., University of Tennessee, 104 Yres Hall, Knoxville, TN, 37996, USA

    Jack Dongarra

  2. MTA SZTAKI Computer and Automation Research Institute, P.O. Box 63, Budapest, 1518, Hungary

    Peter Kacsuk  & Norbert Podhorszki  & 

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© 2000 Springer-Verlag Berlin Heidelberg

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Quoy, M., Moga, S., Gaussier, P., Revel, A. (2000). Parallelization of Neural Networks Using PVM. In: Dongarra, J., Kacsuk, P., Podhorszki, N. (eds) Recent Advances in Parallel Virtual Machine and Message Passing Interface. EuroPVM/MPI 2000. Lecture Notes in Computer Science, vol 1908. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45255-9_40

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  • DOI: https://doi.org/10.1007/3-540-45255-9_40

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41010-2

  • Online ISBN: 978-3-540-45255-3

  • eBook Packages: Springer Book Archive

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