• DocumentCode
    1893152
  • Title

    A novel sample reuse methodology for fast statistical simulations with applications to manufacturing variability

  • Author

    Kanj, Rouwaida ; Joshi, Rajiv

  • Author_Institution
    IBM TJ Watson Labs., Yorktown Heights, NY, USA
  • fYear
    2012
  • fDate
    19-21 March 2012
  • Firstpage
    672
  • Lastpage
    678
  • Abstract
    In this paper we propose a highly efficient statistical simulation methodology based on sample reuse. In the event of design re-centering, multiple manufacturing variability corners, or statistical sensitivity analysis the methodology enables design yield estimations at no additional cost to the reference center analysis. Sample points from the reference center statistical simulation can be utilized to estimate the yield at multiple neighboring centers. The capabilities of the methodology are further extended by projecting the new center onto the critical fail/sampling direction of the reference simulation. This improves the accuracy of the estimate and widens the scope of application. Theoretical applications and analysis of state of the art memory designs indicate excellent yield estimate matching and several orders of magnitude of speedup due to sample reuse.
  • Keywords
    Monte Carlo methods; integrated circuit yield; integrated memory circuits; statistical analysis; design recentering; design yield estimations; fast statistical simulations; manufacturing variability corners; memory designs; neighboring centers; reference center analysis; reference simulation; sample reuse methodology; statistical sensitivity analysis; yield estimate matching; Computational modeling; Equations; Gaussian distribution; Mathematical model; Monte Carlo methods; Sensitivity; Yield estimation; Yield; memory; reuse; sample; simulation; statistical;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Quality Electronic Design (ISQED), 2012 13th International Symposium on
  • Conference_Location
    Santa Clara, CA
  • ISSN
    1948-3287
  • Print_ISBN
    978-1-4673-1034-5
  • Type

    conf

  • DOI
    10.1109/ISQED.2012.6187564
  • Filename
    6187564