• DocumentCode
    3247748
  • Title

    A neural network approach to the placement problem

  • Author

    Zamani, M. Saheb ; Hellestrand, G.R.

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Sydney Univ., NSW, Australia
  • fYear
    1995
  • fDate
    29 Aug-1 Sep 1995
  • Firstpage
    413
  • Lastpage
    416
  • Abstract
    In this paper, we introduce a new neural network approach to the placement of gate array designs. The network used is a Kohonen self-organising map. An abstract specification of the design is converted to a set of appropriate input vectors fed to the network at random. At the end of the process, the map shows a 2-dimensional plane of the design in which the modules with higher connectivity are placed adjacent to each other, hence minimising total connection length in the design. The approach can consider external connections and is able to place modules in a rectilinear boundary. These features makes the approach capable of being used in hierarchical floorplanning algorithms
  • Keywords
    circuit layout; circuit layout CAD; self-organising feature maps; Kohonen self-organising map; abstract specification; connectivity; external connections; floorplanning algorithms; gate array; neural network; neural network approach; placement problem; rectilinear boundary; Algorithm design and analysis; Circuits; Electronic mail; Neural networks; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design Automation Conference, 1995. Proceedings of the ASP-DAC '95/CHDL '95/VLSI '95., IFIP International Conference on Hardware Description Languages. IFIP International Conference on Very Large Scal
  • Conference_Location
    Chiba
  • Print_ISBN
    4-930813-67-0
  • Type

    conf

  • DOI
    10.1109/ASPDAC.1995.486253
  • Filename
    486253