Statistical performance modeling and optimization

Journal Article (Journal Article)

As IC technologies scale to finer feature sizes, it becomes increasingly difficult to control the relative process variations. The increasing fluctuations in manufacturing processes have introduced unavoidable and significant uncertainty in circuit performance; hence ensuring manufacturability has been identified as one of the top priorities of today's IC design problems. In this paper, we review various statistical methodologies that have been recently developed to model, analyze, and optimize performance variations at both transistor level and system level. The following topics will be discussed in detail: sources of process variations, variation characterization and modeling, Monte Carlo analysis, response surface modeling, statistical timing and leakage analysis, probability distribution extraction, parametric yield estimation and robust IC optimization. These techniques provide the necessary CAD infrastructure that facilitates the bold move from deterministic, corner-based IC design toward statistical and probabilistic design.

Full Text

Duke Authors

Cited Authors

  • Li, X; Le, J; Pileggi, LT

Published Date

  • December 1, 2006

Published In

Volume / Issue

  • 1 / 4

Start / End Page

  • 331 - 480

Electronic International Standard Serial Number (EISSN)

  • 1551-3947

International Standard Serial Number (ISSN)

  • 1551-3939

Digital Object Identifier (DOI)

  • 10.1561/1000000008

Citation Source

  • Scopus