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A methodology to improve timing yield in the presence of process variations
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 41st annual Design Automation Conference table of contents
San Diego, CA, USA
SESSION: Yield estimation and optimization table of contents
Pages: 448 - 453  
Year of Publication: 2004
ISBN:1-58113-828-8
Authors
Sreeja Raj  University of Arizona, AZ
Sarma B. K. Vrudhula  University of Arizona, AZ
Janet Wang  University of Arizona, AZ
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 37,   Citation Count: 27
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ABSTRACT

The ability to control the variations in IC fabrication process is rapidly diminishing as feature sizes continue towards the sub-100 nm regime. As a result, there is an increasing uncertainty in the performance of CMOS circuits. Accounting for the worst case values of all parameters will result in an unacceptably low timing yield. Design for Variability, which involves designing to achieve a given level of confidence in the performance of ICs, is fast becoming an indispensable part of IC design methodology. This paper describes a method to identify certain paths in the circuit that are responsible for the spread of timing performance. The method is based on defining a disutility function of the gate and path delays, which includes both the means and variances of the delay random variables. Based on the moments of this disutility function, an algorithm is presented which selects a subset of paths (called undominated paths) as being most responsible for the variation in timing performance. Next, a statistical gate sizing algorithm is presented, which is aimed at minimizing the delay variability of the nodes in the selected paths subject to constraints on the critical path delay and the area penalty. Monte-Carlo simulations with ISCAS '85 benchmark circuits show that our statistical optimization approach results in significant improvements in timing yield over traditional deterministic sizing methods.


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  27

Collaborative Colleagues:
Sreeja Raj: colleagues
Sarma B. K. Vrudhula: colleagues
Janet Wang: colleagues