• DocumentCode
    2616828
  • Title

    Scale invariance and the upper limits of interconnection complexity

  • Author

    Christie, Phillip ; Dorricott, Brian

  • Author_Institution
    Dept. of Electr. Eng., Delaware Univ., Newark, DE, USA
  • fYear
    1990
  • fDate
    1-3 May 1990
  • Firstpage
    192
  • Abstract
    A definition of interconnection complexity in terms of a constant scale-invariant dimensions of information flow is presented. The proposal that all interconnection networks must be characterized by a constant dimensionality if they are to interconnect an arbitrarily large processing system is discussed. This construction hypothesis is applied to neural networks. The results of a series of experiments to determine the optimum dimensionality are reported
  • Keywords
    circuit layout; fractals; multiprocessor interconnection networks; network topology; neural nets; parallel architectures; algorithms implementation; constant scale-invariant dimensions; fractal description; fractal neural array; information flow; interconnection complexity; interconnection networks; large processing system; neural networks; optimum dimensionality; placement algorithm; upper limits; Cooling; Equations; High performance computing; Logic; Mathematical model; Multiprocessor interconnection networks; Neural networks; Pathology; Power dissipation; Power system interconnection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1990., IEEE International Symposium on
  • Conference_Location
    New Orleans, LA
  • Type

    conf

  • DOI
    10.1109/ISCAS.1990.111965
  • Filename
    111965