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Timing analysis with nonseparable statistical and deterministic variations

  • Vladimir Zolotov
  • , Debjit Sinha
  • , Jeffrey Hemmett
  • , Eric Foreman
  • , Chandu Visweswariah
  • , Jinjun Xiong
  • , Jeremy Leitzen
  • , Natesan Venkateswaran
  • IBM

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

Statistical static timing analysis (SSTA) is ideal for random variations but is not suitable for environmental variations like Vdd and temperature. SSTA uses statistical approximation, according to which circuit timing is predicted accurately only for highly probable combinations of variational parameters. SSTA is not able to handle accurately deterministic sources of variation like supply voltage. This paper presents a novel technique for modeling nonseparable deterministic and statistical variations in single timing run.

Original languageEnglish
Title of host publicationProceedings of the 49th Annual Design Automation Conference, DAC '12
Pages1061-1066
Number of pages6
DOIs
StatePublished - 2012
Event49th Annual Design Automation Conference, DAC '12 - San Francisco, CA, United States
Duration: Jun 3 2012Jun 7 2012

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Conference

Conference49th Annual Design Automation Conference, DAC '12
Country/TerritoryUnited States
CitySan Francisco, CA
Period06/3/1206/7/12

Keywords

  • static timing
  • statistical timing
  • variability

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