• DocumentCode
    500821
  • Title

    PiCAP: A parallel and incremental capacitance extraction considering stochastic process variation

  • Author

    Gong, Fang ; Yu, Hao ; He, Lei

  • Author_Institution
    EE Dept., UCLA, Los Angeles, CA, USA
  • fYear
    2009
  • fDate
    26-31 July 2009
  • Firstpage
    764
  • Lastpage
    769
  • Abstract
    It is unknown how to include stochastic process variation into fast multipole method (FMM) for a full chip capacitance extraction. This paper presents a parallel FMM extraction using stochastic polynomial expanded geometrical moments. It utilizes multiprocessors to evaluate in parallel for the stochastic potential interaction and its matrix vector product (MVP) with charge. Moreover, a generalized minimal residual (GMRES) method with deflation is modified to incrementally consider the nominal value and the variance. The overall extraction flow is called piCAP. Experiments show that the parallel MVP in piCAP is up to 3X faster than the serial MVP, and the incremental GMRES in pi-CAP is up to 15X faster than non-incremental GMRES methods.
  • Keywords
    integrated circuit design; stochastic processes; GMRES method; expanded geometrical moment; generalized minimal residual method; incremental capacitance extraction; matrix vector product; multiprocessor system; nominal value; parallel FMM extraction; parallel capacitance extraction; parallel fast multipole method extraction; stochastic polynomial; stochastic potential interaction; stochastic process variation; Algorithm design and analysis; Capacitance; Computational efficiency; Design automation; Dielectrics; Helium; Matrix decomposition; Permission; Polynomials; Stochastic processes; Capacitance extraction; Incremental precondition; Parallel fast-multipole method; Stochastic geometrical moments;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design Automation Conference, 2009. DAC '09. 46th ACM/IEEE
  • Conference_Location
    San Francisco, CA
  • ISSN
    0738-100X
  • Print_ISBN
    978-1-6055-8497-3
  • Type

    conf

  • Filename
    5227077