• DocumentCode
    3193801
  • Title

    A Design Model for Random Process Variability

  • Author

    Wang, Victoria ; Agarwal, Kanak ; Nassif, Sani ; Nowka, Kevin ; Markovic, Dejan

  • Author_Institution
    Univ. of California, Los Angeles
  • fYear
    2008
  • fDate
    17-19 March 2008
  • Firstpage
    734
  • Lastpage
    737
  • Abstract
    A new approach to analyze process variation through measured current variation is introduced. The methodology concludes with a simple and convenient posynomial model for random process variability to bridge the gap between existing statistical methods and circuit design. The model contains only design variables: transistor sizes W and L, and operating points Vgs and Vds. Modeling random process variability in this way allows for adaptability to optimization problems, time efficient methods for gathering statistical information in comparison to Monte Carlo, and an alternative equation for hand analysis.
  • Keywords
    integrated circuit design; integrated circuit modelling; random processes; statistical analysis; Monte Carlo method; current variation; integrated circuit design; posynomial model; random process variability; statistical information; statistical methods; Bridge circuits; Circuit synthesis; Current distribution; Current measurement; Equations; Gaussian distribution; MOSFETs; Metrology; Random processes; Testing; current variation; modeling; principal component analysis; random process variability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Quality Electronic Design, 2008. ISQED 2008. 9th International Symposium on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-0-7695-3117-5
  • Type

    conf

  • DOI
    10.1109/ISQED.2008.4479829
  • Filename
    4479829