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Criticality computation in parameterized statistical timing

  • Jinjun Xiong
  • , Vladimir Zolotov
  • , Natesan Venkateswaran
  • , Chandu Visweswariah
  • IBM

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

51 Scopus citations

Abstract

Chips manufactured in 90 nm technology have shown large parametric variations, and a worsening trend is predicted. These parametric variations make circuit optimization difficult since different paths are frequency-limiting in different parts of the multi-dimensional process space. Therefore, it is desirable to have a new diagnostic metric for robust circuit optimization. This paper presents a novel algorithm to compute the criticality probability of every edge in the timing graph of a design with linear complexity in the circuit size. Using industrial benchmarks, we verify the correctness of our criticality computation via Monte Carlo simulation. We also show that for large industrial designs with 442,000 gates, our algorithm computes all edge criticalities in less than 160 seconds.

Original languageEnglish
Title of host publication2006 43rd ACM/IEEE Design Automation Conference, DAC'06
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages63-68
Number of pages6
ISBN (Print)1595933816, 1595933816, 9781595933812
DOIs
StatePublished - 2006
Event43rd Annual Design Automation Conference, DAC 2006 - San Francisco, CA, United States
Duration: Jul 24 2006Jul 28 2006

Publication series

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

Conference

Conference43rd Annual Design Automation Conference, DAC 2006
Country/TerritoryUnited States
CitySan Francisco, CA
Period07/24/0607/28/06

Keywords

  • Criticality probability
  • Parametric variation
  • Statistical timing

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