• DocumentCode
    3394660
  • Title

    An embedded global addressing technique for scalable neural architectures

  • Author

    Alhalabi, Bassem ; Bayoumi, Magdy

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Florida Atlantic Univ., Boca Raton, FL, USA
  • Volume
    2
  • fYear
    1997
  • fDate
    3-6 Aug. 1997
  • Firstpage
    1264
  • Abstract
    This paper proposes an embedded addressing technique suitable for chip-set based scalable neural network systems. A detailed hardware design and the corresponding algorithms are developed. The novel feature of the developed technique is that it effectively eliminates the need for all off-chip address decoding hardware, making the overall system self-contained. Moreover, this technique makes hardware scalability easier to implement than other standard addressing schemes.
  • Keywords
    feedforward neural nets; integrated circuit design; neural chips; chip-set based neural network systems; embedded global addressing technique; hardware design; hardware scalability; scalable neural architectures; self-contained system; Bandwidth; Computer architecture; Computer science; Decoding; Feedforward systems; Hardware; Neural networks; Neurons; Scalability; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1997. Proceedings of the 40th Midwest Symposium on
  • Print_ISBN
    0-7803-3694-1
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1997.662311
  • Filename
    662311