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ABSTRACT
The correlation of a statistical analysis tool to hardware depends on the accuracy of underlying variation models. The models should represent actual process behavior as measured in silicon. In this paper, we present an overview of test structures for characterizing statistical variation of process parameters. We discuss the test structure design and characterization strategy for calibrating random and layout dependent systematic components of process variation. We also show measurement results from several fabricated structures in 65-nm CMOS technologies.
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CITED BY 8
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Shoaib Akram , Scott Cromar , Gregory Lucas , Alexandros Papakonstantinou , Deming Chen, VEBoC: variation and error-aware design for billions of devices on a chip, Proceedings of the 2008 conference on Asia and South Pacific design automation, January 21-24, 2008, Seoul, Korea
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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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P. B. Bacinschi , T. Murgan , K. Koch , M. Glesner, An analog on-chip adaptive body bias calibration for reducing mismatches in transistor pairs, Proceedings of the conference on Design, automation and test in Europe, March 10-14, 2008, Munich, Germany
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