• DocumentCode
    3344731
  • Title

    A Technique for NoC Routing Based on Hybrid Particle Swarm Optimization Algorithm

  • Author

    Xu Chuan-pei ; Yan Xiao-feng ; Chen Yu-qian

  • Author_Institution
    Sch. of Electron. Eng., Guilin Univ. of Electron. Technol., Guilin, China
  • fYear
    2009
  • fDate
    14-17 Oct. 2009
  • Firstpage
    607
  • Lastpage
    610
  • Abstract
    Network-on-chip (NoC) has been proposed as a solution for the global communication challenges of system-on-chip (SoC) design in the nanoscale technologies. In this paper, a methodology is presented to develop an efficient routing algorithm for network-on-chip platforms that are specialized for an application or a set of concurrent applications. The proposed routing methodology, based on the hybrid particle swarm optimization (PSO) Algorithm, is applied on the 2D-mesh NoC platform to balance the link load. Experimental results show that this routing algorithm can efficiently assign deterministic, deadlock-free, minimal routing paths for traffic traces in a short period of time, and significantly guarantee the bandwidth requirement. In addition, the Hybrid PSO is combined with the operations of GA Algorithm, so that the algorithm achieves better performance.
  • Keywords
    network routing; network-on-chip; particle swarm optimisation; 2D-mesh NoC platform; NoC routing; hybrid particle swarm optimization algorithm; network-on-chip; Algorithm design and analysis; Bandwidth; Network topology; Network-on-a-chip; Particle swarm optimization; Quality of service; Routing; Switches; System-on-a-chip; Virtual colonoscopy; Network-on-chip (NoC); Particle Swarm Optimization (PSO) Algorithm; Quality of Service (QoS); routing algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
  • Conference_Location
    Guilin
  • Print_ISBN
    978-0-7695-3899-0
  • Type

    conf

  • DOI
    10.1109/WGEC.2009.42
  • Filename
    5402763