• DocumentCode
    3344661
  • Title

    Test Scheduling of SOC with Power Constraint Based on Particle Swarm Optimization Algorithm

  • Author

    Xu Chuan-pei ; Hu Hong-bo ; Niu Jun-hao

  • Author_Institution
    Sch. of Electron. Eng., Guilin Univ. of Electron. Technol., Guilin, China
  • fYear
    2009
  • fDate
    14-17 Oct. 2009
  • Firstpage
    611
  • Lastpage
    614
  • Abstract
    The rapid development of modern VLSI technology allows incorporating a complete system on a single chip using the system-on-chip (SoC) methodology. Test scheduling solution for SoC embedded IP cores is a very complex problem. It is necessary to test these cores in parallel for reducing test time. This paper presents an efficient approach based on particle swarm optimization (PSO) algorithm for the test scheduling problem of core-based SoCs with power constraint. PSO algorithm is improved on so that the algorithm can be used to optimize SoC testing. The cores are assigned to test access mechanism (TAM) of given widths such that the total test time is minimized. Experimental results for ITC´02 benchmarks demonstrate that the method has better performance and lower testing time compared to other heuristic algorithms in test scheduling of SoC.
  • Keywords
    VLSI; logic testing; particle swarm optimisation; scheduling; system-on-chip; PSO algorithm; SoC embedded IP cores; SoC test scheduling problem; VLSI technology; heuristic algorithms; particle swarm optimization algorithm; power constraint; system-on-chip methodology; test access mechanism; Energy consumption; Genetics; Job shop scheduling; Particle swarm optimization; Partitioning algorithms; Power engineering computing; Scheduling algorithm; System testing; System-on-a-chip; Very large scale integration; PSO Algorithm; SOC; power constraint; test scheduling;
  • 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.2009.61
  • Filename
    5402760