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A general framework for accurate statistical timing analysis considering correlations
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 42nd annual Design Automation Conference table of contents
Anaheim, California, USA
SESSION: Statistical timing analysis table of contents
Pages: 89 - 94  
Year of Publication: 2005
ISBN:1-59593-058-2
Authors
Vishal Khandelwal  University of Maryland-College Park
Ankur Srivastava  University of Maryland-College Park
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 5,   Downloads (12 Months): 46,   Citation Count: 22
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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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A. Agarwal, V. Zolotov and D. Blaauw. "Statistical Timing Analysis Using Bounds and Selective Enumeration". In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol.22, Sept. 2003.
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C. E. Clark. "The Greates of a Finite Set of Random Variables". In Operations Research, pages 145--162, 1961.
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E.M. Sentovich, K.J. Singh, L. Lavagno, C. Moon, R. Murgai, A. Saldanha, H. Savoj, P.R. Stephan, R.K. Brayton, A.L. Sangiovanni-Vincentelli. SIS: A System for Sequential Circuit Synthesis. Memorandum No. UCB/ERL M92/41, Dept of EECS. UC Berkeley, May 1992.
 
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M. Cain. "The Moment Generating Function of the Minimum of Bivariate Normal Random Variables". In The American Statistician, pages 124--125, May 1994.
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CITED BY  22

Collaborative Colleagues:
Vishal Khandelwal: colleagues
Ankur Srivastava: colleagues