Skip to main navigation Skip to search Skip to main content

Path criticality computation in parameterized statistical timing analysis using a novel operator

  • Jaeyong Chung
  • , Jinjun Xiong
  • , Vladimir Zolotov
  • , Jacob A. Abraham
  • University of Texas at Austin
  • Synopsys Inc.
  • IBM

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

This paper presents a method to compute criticality probabilities of paths in parameterized statistical static timing analysis. We partition the set of all the paths into several groups and formulate the path criticality into a joint probability of inequalities. Before evaluating the joint probability directly, we simplify the inequalities through algebraic elimination, handling topological correlation. Our proposed method uses conditional probabilities to obtain the joint probability, and statistics of random variables representing process parameters are changed to take into account the conditions. To calculate the conditional statistics of the random variables, we derive analytic formulas by extending Clark's work. This allows us to obtain the conditional probability density function of a path delay, given the path is critical, as well as to compute criticality probabilities of paths. Our experimental results show that the proposed method provides 4.2X better accuracy on average in comparison to the state-of-art method.

Original languageEnglish
Article number6171046
Pages (from-to)497-508
Number of pages12
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume31
Issue number4
DOIs
StatePublished - Apr 2012

Keywords

  • Conditioning operation
  • criticality
  • statistical maximum
  • statistical timing analysis

Fingerprint

Dive into the research topics of 'Path criticality computation in parameterized statistical timing analysis using a novel operator'. Together they form a unique fingerprint.

Cite this