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Principle Hessian direction based parameter reduction with process variation
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Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design table of contents
San Jose, California
SESSION: Advances in model order reduction techniques for interconnect analysis table of contents
Pages 632-637  
Year of Publication: 2007
ISBN ~ ISSN:1092-3152 , 1-4244-1382-6
Authors
Alex Mitev  University of Arizona at Tucson, Tucson, AZ
Michael Marefat  University of Arizona at Tucson, Tucson, AZ
Dongsheng Ma  University of Arizona at Tucson, Tucson, AZ
Janet M. Wang  University of Arizona at Tucson, Tucson, AZ
Sponsors
: IEEE CASS/CANDE
SIGDA: ACM Special Interest Group on Design Automation
IEEE-CS\DATC : IEEE Computer Society
CEDA : Council on Electronic Design Automation
Publisher
IEEE Press  Piscataway, NJ, USA
Bibliometrics
Downloads (6 Weeks): 5,   Downloads (12 Months): 27,   Citation Count: 2
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ABSTRACT

As CMOS technology enters the nanometer regime, the increasing process variation is bringing manifest impact on circuit performance. In this paper, we propose a Principle Hessian Direction (PHD) based parameter reduction approach. This new approach relies on the impact of each parameter on circuit performance to decide whether keeping or reducing the parameter. Compared with the existing principle component analysis (PCA) method, this performance based property provides us a significantly smaller set of parameters after reduction. The experimental results also support our conclusions. In all cases, an average of 53% of reduction is observed with less than 3% error in the mean value and less than 8% error in the variation.


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:
Alex Mitev: colleagues
Michael Marefat: colleagues
Dongsheng Ma: colleagues
Janet M. Wang: colleagues