Statistical Performance Modeling and Optimization

Author(s): Xin Li;Jiayong Le;Lawrence T Pileggi

Source:
    Journal:Foundations and Trends® in Econometrics
    ISSN Print:1551-3076,  ISSN Online:1551-3084
    Publisher:Now Publishers
    Volume 1 Number 4,

Document Type: Article
Pages: 150(331-480)
DOI: 10.1561/1000000008

Abstract: 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