NDLI: Non-Gaussian statistical timing analysis using second-order polynomial fitting

Content Provider	IEEE Xplore Digital Library
Author	Lerong Cheng Jinjun Xiong Lei He
Copyright Year	2008
Description	Author affiliation: Univ. of California, Los Angeles (Lerong Cheng)
Abstract	In the nanometer manufacturing region, process variation causes significant uncertainty for circuit performance verification. Statistical static timing analysis (SSTA) is thus developed to estimate timing distribution under process variation. However, most of the existing SSTA techniques have difficulty in handling the non-Gaussian variation distribution and non-linear dependency of delay on variation sources. To solve such a problem, in this paper, we first propose a new method to approximate the max operation of two non- Gaussian random variables through second-order polynomial fitting. We then present new non-Gaussian SSTA algorithms under two types of variational delay models: quadratic model and semi-quadratic model (i.e., quadratic model without crossing terms). All atomic operations (such as max and sum) of our algorithms are performed by closed-form formulas, hence they scale well for large designs. Experimental results show that compared to the Monte-Carlo simulation, our approach predicts the mean, standard deviation, and skewness within 1%, 1%, and 5% error, respectively. Our approach is more accurate and also 20times faster than the most recent method for non-Gaussian and nonlinear SSTA.
Starting Page	298
Ending Page	303
File Size	281642
Page Count	6
File Format	PDF
ISBN	9781424419210
DOI	10.1109/ASPDAC.2008.4483962
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-21
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Timing Polynomials Random variables CMOS technology Delay lines Fitting Uncertainty Circuit optimization Integrated circuit technology Semiconductor process modeling
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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