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Modeling of intra-die process variations for accurate analysis and optimization of nano-scale circuits
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 43rd annual conference on Design automation table of contents
San Francisco, CA, USA
SESSION: Session 45: design/technology interaction table of contents
Pages: 791 - 796  
Year of Publication: 2006
ISBN:1-59593-381-6
Authors
Sarvesh Bhardwaj  Arizona State University, Tempe, AZ
Sarma Vrudhula  Arizona State University, Tempe, AZ
Praveen Ghanta  Arizona State University, Tempe, AZ
Yu Cao  Arizona State University, Tempe, AZ
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

This paper proposes the use of Karhunen-Loève Expansion (KLE) for accurate and efficient modeling of intra-die correlations in the semiconductor manufacturing process. We demonstrate that the KLE provides a significantly more accurate representation of the underlying stochastic process compared to the traditional approach of dividing the layout into grids and applying Principal Component Analysis (PCA). By comparing the results of leakage analysis using both KLE and the existing approaches, we show that using KLE can provide up to 4-5x reduction in the variability space (number of random variables) while maintaining the same accuracy. We also propose an efficient leakage minimization algorithm that maximizes the leakage yield while satisfying probabilistic constraints on the delay.


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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Collaborative Colleagues:
Sarvesh Bhardwaj: colleagues
Sarma Vrudhula: colleagues
Praveen Ghanta: colleagues
Yu Cao: colleagues