Interval-valued reduced order statistical interconnect modeling

James D. Ma, Rob A. Rutenbar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We show how recent advances in the handling of correlated interval representations of range uncertainty can be used to predict the impact of statistical manufacturing variations on linear interconnect. We represent correlated statistical variations in RLC parameters as sets of correlated intervals, and show how classical model order reduction methods - AWE and PRIMA - can be re-targeted to compute interval-valued, rather than scalar-valued reductions. By applying a statistical interpretation and sampling to the resulting compact interval-valued model, we can efficiently estimate the impact of variations on the original circuit. Results show the technique can predict mean delay with errors between 5-10%, for correlated RLC parameter variations up to 35%

Original languageEnglish (US)
Title of host publicationICCAD-2004 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers
Pages460-467
Number of pages8
DOIs
StatePublished - 2004
Externally publishedYes
EventICCAD-2004 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers - San Jose, CA, United States
Duration: Nov 7 2004Nov 11 2004

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
ISSN (Print)1092-3152

Other

OtherICCAD-2004 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers
Country/TerritoryUnited States
CitySan Jose, CA
Period11/7/0411/11/04

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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