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A fast non-Monte-Carlo yield analysis and optimization by stochastic orthogonal polynomials

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A fast non-Monte-Carlo yield analysis and optimization by stochastic orthogonal polynomials

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dc.contributor.author Gong, Fang
dc.contributor.author Liu, Xuexin
dc.contributor.author Yu, Hao
dc.contributor.author Tan, Sheldon X. D.
dc.contributor.author Ren, Junyan
dc.contributor.author He, Lei
dc.date.accessioned 2012-10-11T06:49:00Z
dc.date.available 2012-10-11T06:49:00Z
dc.date.copyright 2010
dc.date.issued 2012-10-11
dc.identifier.citation Gong, F., Liu, X., Yu, H., Tan, S. X. D., Ren, J., & He, L. (2012). A fast non-Monte-Carlo yield analysis and optimization by stochastic orthogonal polynomials. ACM Transactions on Design Automation of Electronic Systems, 17(1).
dc.identifier.issn 1084-4309
dc.identifier.uri http://hdl.handle.net/10220/8763
dc.description.abstract Performance failure has become a significant threat to the reliability and robustness of analog circuits. In this article, we first develop an efficient non-Monte-Carlo (NMC) transient mismatch analysis, where transient response is represented by stochastic orthogonal polynomial (SOP) expansion under PVT variations and probabilistic distribution of transient response is solved. We further define performance yield and derive stochastic sensitivity for yield within the framework of SOP, and finally develop a gradient-based multiobjective optimization to improve yield while satisfying other performance constraints. Extensive experiments show that compared to Monte Carlo-based yield estimation, our NMC method achieves up to 700X speedup and maintains 98% accuracy. Furthermore, multiobjective optimization not only improves yield by up to 95.3% with performance constraints, it also provides better efficiency than other existing methods.
dc.language.iso en
dc.relation.ispartofseries ACM transactions on design automation of electronic systems
dc.rights © 2012 ACM. This is the author created version of a work that has been peer reviewed and accepted for publication by ACM Transactions on Design Automation of Electronic Systems, ACM. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1145/2071356.2071366].
dc.subject DRNTU::Engineering::Electrical and electronic engineering.
dc.title A fast non-Monte-Carlo yield analysis and optimization by stochastic orthogonal polynomials
dc.type Journal Article
dc.contributor.school School of Electrical and Electronic Engineering
dc.identifier.doi http://dx.doi.org/10.1145/2071356.2071366
dc.description.version Accepted version
dc.identifier.rims 162550

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