Parallelization of algorithms for neural networks

  • Beniamino Di Martino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1041)


In this paper we present the strategies adopted in the parallelization of two algorithms for the simulation of two classes of neural networks: the Hopfield Network and the Error BackPropagation Network.

Although the parallel algorithms have been developed within the (loosely synchronous) SPMD parallel programming model, the particular nature of the strategies adopted make the final parallel algorithms not expressible within the HPF-like programming paradigm; therefore a more flexible programming model, the message passing programming paradigm, has been adopted, and the final development has been carried out in the PVM environment.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Beniamino Di Martino
    • 1
  1. 1.Dipartimento di Informatica e SistemisticaUniversità di Napoli “Federico II”NapoliItaly

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