From finance to flip flops: A study of fast Quasi-Monte Carlo methods from computational finance applied to statistical circuit analysis

Amith Singhee, Rob A. Rutenbar

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

Abstract

Problems in computational finance share many of the characteristics that challenge us in statistical circuit analysis: high dimensionality, profound nonlinearity, stringent accuracy requirements, and expensive sample simulation. We offer a detailed experimental study of how one celebrated technique from this domain - Quasi-Monte Carlo (QMC) analysis - can be used for fast statistical circuit analysis. In contrast with traditional pseudo-random Monte Carlo sampling, QMC substitutes a (shorter) sequence of deterministically chosen sample points. Across a set of digital and analog circuits, in 90nm and 45nm technologies, varying in size from 30 to 400 devices, we obtain speedups in parametric yield estimation from 2X to 50X.

Original languageEnglish (US)
Title of host publicationProceedings - Eighth International Symposium on Quality Electronic Design, ISQED 2007
Pages685-692
Number of pages8
DOIs
StatePublished - 2007
Event8th International Symposium on Quality Electronic Design, ISQED 2007 - San Jose, CA, United States
Duration: Mar 26 2007Mar 28 2007

Publication series

NameProceedings - Eighth International Symposium on Quality Electronic Design, ISQED 2007

Other

Other8th International Symposium on Quality Electronic Design, ISQED 2007
CountryUnited States
CitySan Jose, CA
Period3/26/073/28/07

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

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