• DocumentCode
    3564503
  • Title

    FPGA design of a multicore neuromorphic processing system

  • Author

    Yangjie Qi ; Bin Zhang ; Taha, Tarek M. ; Hua Chen ; Hasan, Raqibul

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Dayton, Dayton, OH, USA
  • fYear
    2014
  • Firstpage
    255
  • Lastpage
    258
  • Abstract
    The Interest in specialized neuromorphic computing architectures has been increasing recently, and several applications have been shown to be capable of being accelerated on such a platform. This paper describes the implementation of a multicore digital neuromorphic processing system on an Altera Quartus II FPGA. Static routing was used to allow communication between the cores on the FPGA. Two applications were mapped to the system: image edge detection and ECG. Compared to an Intel processor implementation of these applications, the FPGA based neural implementations provided about 3× and 127× speedup for the edge detection and ECG applications. Given that both applications were implemented with the same base Verilog code, with only a change in the synaptic weights and number of neurons utilized, the system has the capability to accelerate a broad range of applications.
  • Keywords
    field programmable gate arrays; multiprocessing systems; network routing; Altera Quartus II FPGA; ECG; FPGA design; Verilog code; image edge detection; multicore digital neuromorphic processing; neuromorphic computing architecture; neurons; static routing; synaptic weight; Biological neural networks; Field programmable gate arrays; Image edge detection; Multicore processing; Neuromorphics; Neurons; Routing; FPGA; multicore; neuromorphic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Aerospace and Electronics Conference, NAECON 2014 - IEEE National
  • Print_ISBN
    978-1-4799-4690-7
  • Type

    conf

  • DOI
    10.1109/NAECON.2014.7045812
  • Filename
    7045812