• DocumentCode
    2732582
  • Title

    A VLSI routing algorithm based on improved DPSO

  • Author

    Dong, Chen ; Wang, Gaofeng ; Chen, Zhenyi ; Sun, Shilei ; Wang, Dingwen

  • Author_Institution
    Comput. Sch., Wuhan Univ., Wuhan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    20-22 Nov. 2009
  • Firstpage
    802
  • Lastpage
    805
  • Abstract
    The minimum rectilinear Steiner tree (MRST) problem is an NP-hard problem, which is one of the fundamental issues in electronic design automation (EDA). Particle swarm optimization (PSO) has been proved to be an efficient intelligent algorithm for optimization designs. This paper presents an application of discrete particle swarm optimization (DPSO) for resolving MRST in VLSI routing and proposes a routing algorithm based on improved DPSO (DPSO-RA in short). A novel encoding and several updating operations for DPSO are adopted respectively, according to the characteristics of discrete PSO. The parameters are adjusted to find out an MRST and, consequently, achieve interconnect of all destination nodes in VLSI. The experiments have been carried out to demonstrate the feasibility of DPSO-RA implement to VLSI routing. Moreover, the algorithm also shows good result in routing optimization.
  • Keywords
    VLSI; computational complexity; electronic design automation; microprocessor chips; network routing; particle swarm optimisation; DPSO-RA algorithm; NP-hard problem; VLSI routing algorithm; discrete particle swarm optimization; electronic design automation; minimum rectilinear Steiner tree problem; Algorithm design and analysis; Educational institutions; Electronic design automation and methodology; Information technology; Mathematics; Microelectronics; Particle swarm optimization; Routing; Switches; Very large scale integration; DPSO-RA; MRST; Routing; VLSI;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-4754-1
  • Electronic_ISBN
    978-1-4244-4738-1
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2009.5358030
  • Filename
    5358030