Non-Gaussian uncertainty propagation in statistical circuit simulation

Author

Tang, Qian Ying ; Spanos, Costas

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of California, Berkeley, CA, USA

fYear

2011

fDate

14-16 March 2011

Firstpage

1

Lastpage

8

Abstract

The combination of random and systematic variability in state of the art IC technologies often results in non-Gaussian distributions of key performance parameters. A Mixture of Gaussian (MOG) variance propagation scheme is proposed to estimate the transistor-level circuit performance distribution without costly Monte-Carlo simulations. In the proposed method, interval representations and moment matching algorithms are used to find the MOG of the circuit performance.

Keywords

Gaussian distribution; circuit simulation; integrated circuits; transistor circuits; IC technology; MOG variance propagation scheme; Monte-Carlo simulations; mixture of Gaussian variance propagation scheme; moment matching algorithms; nonGaussian distributions; nongaussian uncertainty propagation; statistical circuit simulation; transistor-level circuit performance distribution; Circuit simulation; Correlation; Equations; Logic gates; Mathematical model; Noise; Runtime; Mixture of Gaussian; Statistical circuit simulation; interval analyses; uncertainty propagation;

fLanguage

English

Publisher

ieee

Conference_Titel

Quality Electronic Design (ISQED), 2011 12th International Symposium on

Conference_Location

Santa Clara, CA

ISSN

1948-3287

Print_ISBN

978-1-61284-913-3

Type

conf

DOI

10.1109/ISQED.2011.5770760

Filename

5770760