NDLI: Adaptive Stochastic Collocation Method (ASCM) for Parameterized Statistical Timing Analysis with Quadratic Delay Model

Content Provider	IEEE Xplore Digital Library
Author	Yi Wang Xuan Zeng Jun Tao Hengliang Zhu Xu Luo Changhao Yan Wei Cai
Copyright Year	2008
Description	Author affiliation: Fudan Univ., Shanghai (Yi Wang; Xuan Zeng; Jun Tao; Hengliang Zhu; Xu Luo; Changhao Yan)
Abstract	In this paper, we propose an adaptive stochastic collocation method for block-based statistical static timing analysis (SSTA). A novel adaptive method is proposed to perform SSTA with delays of gates and interconnects modeled by quadratic polynomials based on homogeneous chaos expansion. In order to approximate the key atomic operator MAX in the full random space during timing analysis, the proposed method adaptively chooses the optimal algorithm from a set of stochastic collocation methods by considering different input conditions. Compared with the existing stochastic collocation methods, including the one using dimension reduction technique and the one using sparse grid technique, the proposed method has 10times improvements in the accuracy while using the same order of computation time. The proposed algorithm also show great improvement in accuracy compared with a moment matching method. Compared with the 10,000 Monte Carlo simulations on ISCAS85 benchmark circuits, the results of the proposed method show less than 1% error in the mean and variance, and nearly 100times speeds up.
Starting Page	62
Ending Page	67
File Size	419466
Page Count	6
File Format	PDF
ISBN	9780769531175
DOI	10.1109/ISQED.2008.4479699
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Timing Polynomials Propagation delay Integrated circuit interconnections Chaos Random variables Algorithm design and analysis Grid computing Performance analysis max adaptive stochastic collocation method statistical static timing analysis process variations
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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