Defining statistical sensitivity for timing optimization of logic circuits with large-scale process and environmental variations

Published

Conference Paper

The large-scale process and environmental variations for today's nanoscale ICs are requiring statistical approaches for timing analysis and optimization. Significant research has been recently focused on developing new statistical timing analysis algorithms, but often without consideration for how one should interpret the statistical timing results for optimization. In this paper [1] we demonstrate why the traditional concepts of slack and critical path become ineffective under large-scale variations, and we propose a novel sensitivity-based metric to assess the "criticality" of each path and/or arc in the statistical timing graph. We define the statistical sensitivities for both paths and arcs, and theoretically prove that our path sensitivity is equivalent to the probability that a path is critical, and our arc sensitivity is equivalent to the probability that an arc sits on the critical path. An efficient algorithm with incremental analysis capability is described for fast sensitivity computation that has a linear runtime complexity in circuit size. The efficacy of the proposed sensitivity analysis is demonstrated on both standard benchmark circuits and large industry examples. © 2005 IEEE.

Full Text

Duke Authors

Cited Authors

  • Li, X; Le, J; Celik, M; Pileggi, LT

Published Date

  • December 1, 2005

Published In

Volume / Issue

  • 2005 /

Start / End Page

  • 843 - 850

International Standard Serial Number (ISSN)

  • 1092-3152

International Standard Book Number 10 (ISBN-10)

  • 078039254X

International Standard Book Number 13 (ISBN-13)

  • 9780780392540

Digital Object Identifier (DOI)

  • 10.1109/ICCAD.2005.1560180

Citation Source

  • Scopus