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ABSTRACT
The impact of parameter variations on timing due to process and environmental variations has become significant in recent years. With each new technology node this variability is becoming more prominent. In this work, we present a general Statistical Timing Analysis (STA) framework that captures spatial correlations between gate delays. Our technique does not make any assumption about the distributions of the parameter variations, gate delay and arrival times. We propose a Taylor-series expansion based polynomial representation of gate delays and arrival times which is able to effectively capture the non-linear dependencies that arise due to increasing parameter variations. In order to reduce the computational complexity introduced due to polynomial modeling during STA, we propose an efficient linear-modeling driven polynomial STA scheme. On an average the degree-2 polynomial scheme had a 7.3x speedup as compared to Monte Carlo with 0.049 units of rms error w.r.t Monte Carlo. Our technique is generic and can be applied to arbitrary variations in the underlying parameters.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 22
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Anand Ramalingam , Gi-Joon Nam , Ashish Kumar Singh , Michael Orshansky , Sani R. Nassif , David Z. Pan, An accurate sparse matrix based framework for statistical static timing analysis, Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design, November 05-09, 2006, San Jose, California
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Vikram Iyengar , Jinjun Xiong , Subbayyan Venkatesan , Vladimir Zolotov , David Lackey , Peter Habitz , Chandu Visweswariah, Variation-aware performance verification using at-speed structural test and statistical timing, Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design, November 05-08, 2007, San Jose, California
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Amith Singhee , Sonia Singhal , Rob A. Rutenbar, Exploiting correlation kernels for efficient handling of intra-die spatial correlation, with application to statistical timing, Proceedings of the conference on Design, automation and test in Europe, March 10-14, 2008, Munich, Germany
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