• DocumentCode
    1353844
  • Title

    FA-STAC: An Algorithmic Framework for Fast and Accurate Coupling Aware Static Timing Analysis

  • Author

    Das, Debasish ; Shebaita, Ahmed ; Zhou, Hai ; Ismail, Yehea ; Killpack, Kip

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL, USA
  • Volume
    19
  • Issue
    3
  • fYear
    2011
  • fDate
    3/1/2011 12:00:00 AM
  • Firstpage
    443
  • Lastpage
    456
  • Abstract
    This paper presents an algorithmic framework for fast and accurate static timing analysis considering coupling. With technology scaling to smaller dimensions, the impact of coupling induced delay variations can no longer be ignored. Timing analysis considering coupling is iterative, and can have considerably larger run-times than a single pass approach. We propose two different classes of coupling delay models: heuristic-based coupling model and current source-based coupling model, and present techniques to increase the convergence rate of timing analysis when such coupling models are employed. Our proposed coupling model show promising accuracy improvements compared to SPICE. Experimental results on ISCAS85 benchmarks validates the effec tiveness of our efficient iteration scheme. Our iteration algorithm obtained speedups of up to 62.1 % using a heuristic coupling model while 2.7 x using a current-based coupling model in comparison to traditional approaches.
  • Keywords
    iterative methods; network analysis; FA-STAC; convergence rate; coupling aware static timing analysis; coupling delay model; current source-based coupling model; current-based coupling model; heuristic coupling model; heuristic-based coupling model; iteration algorithm; Algorithm; crosstalk; mathematical modeling; signal integrity; timing analysis; timing verification;
  • fLanguage
    English
  • Journal_Title
    Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1063-8210
  • Type

    jour

  • DOI
    10.1109/TVLSI.2009.2035323
  • Filename
    5352252