DocumentCode :
3178453
Title :
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
Link To Document :
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