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Fast statistical analysis of rare circuit failure events via Bayesian scaled-sigma sampling for high-dimensional variation space

Publication ,  Conference
Sun, S; Li, X
Published in: Proceedings of the Custom Integrated Circuits Conference
November 25, 2015

Accurately estimating the rare failure events of nanoscale ICs in a high-dimensional variation space is extremely challenging. In this paper, we propose a novel Bayesian scaled-sigma sampling (BSSS) technique to address this technical challenge. BSSS can be considered as an extension of the traditional scaled-sigma sampling (SSS) approach. The key idea is to explore the "similarity" between different SSS models fitted at different design stages and encode it as our prior knowledge. Bayesian model fusion is then adopted to fit the SSS model with consideration of the prior knowledge. A sense amplifier example designed in a 45 nm CMOS process is used to demonstrate the efficacy of BSSS. Experimental results demonstrate that BSSS achieves superior accuracy over the conventional SSS and minimum-norm importance sampling approaches when a few hundred random variables are used to model process variations.

Duke Scholars

Published In

Proceedings of the Custom Integrated Circuits Conference

DOI

ISSN

0886-5930

ISBN

9781479986828

Publication Date

November 25, 2015

Volume

2015-November
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Sun, S., & Li, X. (2015). Fast statistical analysis of rare circuit failure events via Bayesian scaled-sigma sampling for high-dimensional variation space. In Proceedings of the Custom Integrated Circuits Conference (Vol. 2015-November). https://doi.org/10.1109/CICC.2015.7338409
Sun, S., and X. Li. “Fast statistical analysis of rare circuit failure events via Bayesian scaled-sigma sampling for high-dimensional variation space.” In Proceedings of the Custom Integrated Circuits Conference, Vol. 2015-November, 2015. https://doi.org/10.1109/CICC.2015.7338409.
Sun, S., and X. Li. “Fast statistical analysis of rare circuit failure events via Bayesian scaled-sigma sampling for high-dimensional variation space.” Proceedings of the Custom Integrated Circuits Conference, vol. 2015-November, 2015. Scopus, doi:10.1109/CICC.2015.7338409.

Published In

Proceedings of the Custom Integrated Circuits Conference

DOI

ISSN

0886-5930

ISBN

9781479986828

Publication Date

November 25, 2015

Volume

2015-November