• DocumentCode
    2887604
  • Title

    A parallel min-cut technique for standard cell placement using a modified Hopfield neural network

  • Author

    Sriram, M. ; Kang, S.M.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana-Champaign, IL, USA
  • fYear
    1991
  • fDate
    16-17 Jun 1991
  • Firstpage
    894
  • Abstract
    The authors present a new min-cut technique for standard cell placement using a modified Hopfield neural network. The neural network has the advantage of a massively parallel architecture, which can drastically reduce computation time in a hardware implementation. It also allows all partitions at a given level of the hierarchical procedure to be performed in parallel, thus overcoming a common drawback of sequential min-cut procedures. The approach has produced very good results on a number of practical standard cell circuits
  • Keywords
    VLSI; application specific integrated circuits; circuit layout CAD; graph theory; integrated circuit technology; neural nets; parallel processing; ASIC; IC layout design; VLSI design; massively parallel architecture; modified Hopfield neural network; parallel min-cut technique; standard cell placement; Circuits; Computer networks; Concurrent computing; Costs; Hopfield neural networks; Joining processes; Neural network hardware; Neural networks; Neurons; Parallel architectures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1991. Conference Proceedings, China., 1991 International Conference on
  • Conference_Location
    Shenzhen
  • Type

    conf

  • DOI
    10.1109/CICCAS.1991.184506
  • Filename
    184506