| Modeling and estimation of full-chip leakage current considering within-die correlation |
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Annual ACM IEEE Design Automation Conference
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Proceedings of the 44th annual Design Automation Conference
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San Diego, California
SESSION: Leakage power analysis and optimization
table of contents
Pages: 93 - 98
Year of Publication: 2007
ISBN ~ ISSN:0738-100X , 978-1-59593-627-1
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Downloads (6 Weeks): 7, Downloads (12 Months): 43, Citation Count: 3
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ABSTRACT
We present an efficient technique for finding the mean and variance of the full-chip leakage of a candidate design, while considering logic-structures and both die-to-die and within-die process variations, and taking into account the spatial correlation due to within-die variations. Our model uses a "random gate" concept to capture high-level characteristics of a candidate chip design, which are sufficient to determine its leakage. We show empirically that, for large gate count, the set of all chip designs that share the same high level characteristics have approximately the same leakage, with very small error. Therefore, our model can be used as either an early or a late estimator of leakage, with high accuracy. In its simplest form, we show that full-chip leakage estimation reduces to finding the area under a scaled version of the within-die channel length auto-correlation function, which can be done in constant time.
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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Siva Narendra , Vivek De , Shekhar Borkar , Dimitri Antoniadis , Anantha Chandrakasan, Full-chip sub-threshold leakage power prediction model for sub-0.18 μm CMOS, Proceedings of the 2002 international symposium on Low power electronics and design, August 12-14, 2002, Monterey, California, USA
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Ali Keshavarzi , Gerhard Schrom , Stephen Tang , Sean Ma , Keith Bowman , Sunit Tyagi , Kevin Zhang , Tom Linton , Nagib Hakim , Steven Duvall , John Brews , Vivek De, Measurements and modeling of intrinsic fluctuations in MOSFET threshold voltage, Proceedings of the 2005 international symposium on Low power electronics and design, August 08-10, 2005, San Diego, CA, USA
[doi> 10.1145/1077603.1077611]
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A. Papoulis. Probability, Random Variables, and Stochastic Processes. McGraw-Hill, New York, NY, 2nd edition, 1984.
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CITED BY 3
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Tao Li , Wenjun Zhang , Zhiping Yu, Full-chip leakage analysis in nano-scale technologies: mechanisms, variation sources, and verification, Proceedings of the 45th annual conference on Design automation, June 08-13, 2008, Anaheim, California
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Ruijing Shen , Ning Mi , Sheldon X.-D. Tan , Yici Cai , Xianlong Hong, Statistical modeling and analysis of chip-level leakage power by spectral stochastic method, Proceedings of the 2009 Conference on Asia and South Pacific Design Automation, January 19-22, 2009, Yokohama, Japan
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