• DocumentCode
    2956059
  • Title

    Realizing biological spiking network models in a configurable wafer-scale hardware system

  • Author

    Fieres, Johannes ; Schemmel, Johannes ; Meier, Karlheinz

  • Author_Institution
    Kirchhoff Inst. for Phys., Ruprecht-Karls Univ., Heidelberg
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    969
  • Lastpage
    976
  • Abstract
    An analog VLSI hardware architecture for the distributed simulation of large-scale spiking neural networks has been developed. Several hundred integrated computing nodes, each hosting up to 512 neurons, will be interconnected and operated on un-cut silicon wafers. The electro-technical aspects and the details of the hardware implementation are covered in a separate contribution to this conference. This paper focuses on the usability of the system by demonstrating that biologically relevant network models can in fact be mapped to this system. Different network configurations are established on the hardware by programmable switch matrices, repeaters, and address decoders. Systematic routing algorithms are presented to map a given network model to the hardware system. Routing is simulated for several network examples, proving the systempsilas practical applicability. Furthermore, the routing simulations are used to fix values for yet open hardware parameters.
  • Keywords
    analogue integrated circuits; decoding; neural nets; silicon; wafer-scale integration; address decoders; analog VLSI hardware architecture; biological spiking network models; configurable wafer-scale hardware system; distributed simulation; electro-technical aspects; large-scale spiking neural networks; programmable switch matrices; repeaters; silicon wafers; systematic routing algorithms; Biological system modeling; Computational modeling; Computer architecture; Large-scale systems; Neural network hardware; Neural networks; Routing; Semiconductor device modeling; Switches; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4633916
  • Filename
    4633916