• DocumentCode
    1909683
  • Title

    Problems of massive parallelism in neural network simulation

  • Author

    Zell, Andreas ; Mache, N. ; Vogt, Michael ; Hüttel, Markus

  • Author_Institution
    Inst. for Parallel & Distributed High Performance Syst., Stuttgart Univ., Germany
  • fYear
    1993
  • fDate
    1993
  • Firstpage
    1890
  • Abstract
    Different massively parallel implementations of multilayer feedforward neural networks are presented and compared on a MasPar MP-1216, a parallel single instruction, multiple data (SIMD) computer with 16384 processors. For multilayer feedforward networks, sustained rates of up to 348 M CPS and 129 M CUPS with backpropagation are obtained, a high mark for general purpose SIMD computers. Emphasis is placed on the problems of mapping neural networks to parallel hardware, on implementation problems in obtaining high propagation rates on a SIMD machine, and on problems with the resulting learning algorithms
  • Keywords
    backpropagation; feedforward neural nets; parallel processing; virtual machines; MasPar MP-1216; SIMD; backpropagation; learning algorithms; mapping; massive parallelism; multilayer feedforward neural networks; neural network simulation; Backpropagation; Computational modeling; Computer aided instruction; Computer networks; Concurrent computing; Feedforward neural networks; Multi-layer neural network; Neural network hardware; Neural networks; Parallel processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1993., IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7803-0999-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1993.298845
  • Filename
    298845