Timing budgeting under arbitrary process variations

Ruiming Chen*, Hai Zhou

*Corresponding author for this work

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

Abstract

Timing budgeting under process variations is an important step in a statistical optimization flow. We propose a novel formulation of the problem where budgets are statistical instead of deterministic as in existing works. This new formulation considers the changes of both the means and variances of delays, and thus can reduce the timing violation introduced by ignoring the changes of variances. We transform the problem to a linear programming problem using a robust optimization technique. Our approach can be used in late-stage design where the detailed distribution information is known, and is most useful in early-stage design since our approach does not assume specific underlying distributions. In addition, with the help of block-level timing budgeting, our approach can reduce the timing pessimism. Our approach is applied to the leakage power minimization problem. The results demonstrate that our approach can reduce timing violation from 690ps to 0ps, and the worst total leakage power by 17.50% on average.

Original languageEnglish (US)
Title of host publication2007 IEEE/ACM International Conference on Computer-Aided Design, ICCAD
Pages344-349
Number of pages6
DOIs
StatePublished - Dec 1 2007
Event2007 IEEE/ACM International Conference on Computer-Aided Design, ICCAD - San Jose, CA, United States
Duration: Nov 4 2007Nov 8 2007

Publication series

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

Other

Other2007 IEEE/ACM International Conference on Computer-Aided Design, ICCAD
Country/TerritoryUnited States
CitySan Jose, CA
Period11/4/0711/8/07

ASJC Scopus subject areas

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

Fingerprint

Dive into the research topics of 'Timing budgeting under arbitrary process variations'. Together they form a unique fingerprint.

Cite this