• DocumentCode
    2260189
  • Title

    Statistical SRAM analysis for yield enhancement

  • Author

    Zuber, Paul ; Miranda, Miguel ; Dobrovolný, Petr ; Van der Zanden, Koen ; Jung, Jong-Hoon

  • Author_Institution
    Digital Components, IMEC-Belgium, Belgium
  • fYear
    2010
  • fDate
    8-12 March 2010
  • Firstpage
    57
  • Lastpage
    62
  • Abstract
    This paper presents an automated technique to perform SRAM wide statistical analysis in presence of process variability. The technique is implemented in a prototype tool and is demonstrated on several 45 and 32nm industry-grade SRAM vehicles. Selected case studies show how this approach successfully captures non-trivial statistical interactions between the cells and the periphery, which remain uncovered when only using statistical electrical simulations of the critical path or applying a digital corner approach. The presented tool provides the designer with valuable information on what performance metrics to expect, if manufactured. Since this feedback takes place in the design phase, a significant reduction in development time and cost can be achieved.
  • Keywords
    SRAM chips; integrated circuit design; integrated circuit modelling; integrated circuit yield; statistical analysis; digital corner approach; process variability; size 32 nm; size 45 nm; statistical SRAM analysis; statistical electrical simulation; yield enhancement; Analytical models; Circuit simulation; Monte Carlo methods; Performance analysis; Prototypes; Random access memory; Silicon; Statistical analysis; Testing; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design, Automation & Test in Europe Conference & Exhibition (DATE), 2010
  • Conference_Location
    Dresden
  • ISSN
    1530-1591
  • Print_ISBN
    978-1-4244-7054-9
  • Type

    conf

  • DOI
    10.1109/DATE.2010.5457235
  • Filename
    5457235