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A linear fractional transform (LFT) based model for interconnect parametric uncertainty
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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: Model order reduction and variational techniques for parasitic analysis table of contents
Pages: 375 - 380  
Year of Publication: 2004
ISBN:1-58113-828-8
Authors
Janet M. Wang  University of Arizona at Tucson, Tucson, AZ
Omar A. Hafiz  University of Arizona at Tucson, Tucson, AZ
Jun Li  ETOP Design Technology, Sunnyvale, CA
Sponsors
ACM: Association for Computing Machinery
SIGDA: ACM Special Interest Group on Design Automation
Publisher
ACM  New York, NY, USA
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ABSTRACT

As we scale toward nanometer technologies, the increase in interconnect parameter variations will bring significant performance variability. New design methodologies will emerge to facilitate construction of reliable systems from unreliable nanometer scale components. Such methodologies require new performance models which accurately capture the manufacturing realities. In this paper, we present a Linear Fractional Transform (LFT) based model for interconnect Parametric Uncertainty. This new model formulates the interconnect parameter uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) based on Linear Matrix Inequalities (LMI's), the new model reduces the order of the original interconnect network while preserves the stability. This paper also shows that the LFT based model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) which generalizes Lur'e equations.


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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K.J.Kerns, and A.T. Yang, "Stable and Efficient Reduction of Large Multiport RC Networks by Pole analysis via Congruence Transformations", IEEE Trans. CAD, Vol. 16, pp. 734--744, 1997.
 
3
A. Odabasioglu, M. Celik, L. Pileggi, "PRIMA: Passive Reduced-Order Interconnect Macromodeling Algorithm", IEEE Trans. CAD, vol. 17, No. 8, pp. 645--654, Aug. 1998.
 
4
C. Beck, J. Doyle, and K. Glover, "Model Reduction of Multidimensional and Uncertain Systems", IEEE Trans. Automatic Control, vol. 41, No. 10, pp. 1466--1477, October, 1996.
 
5
C. Beck, J. Doyle, "A Necessary and Sufficient Minimality Condition for Uncertain Systems", IEEE Trans. Automatic Control, vol. 44, No. 10, pp. 1802--1813, Oct. 1999.
 
6
 
7
J. Phillips, L. Daniel, L. Silveira, "Guaranteed Passive Balancing Transformations for Model Order Reduction", IEEE Trans. CAD, Vol. 22, No. 8, pp. 1--15, Aug. 2003.
 
8
P. Heydari, and M. Pedram, "Model Reduction of Variable-Geometry Interconnects Using Variational Spectrally-Weighted Balanced Truncation", Design Automation Conference 2001.
 
9
G. Golub, and C. Loan, "Matrix Computation", pp. 390--405, Johns Hopkins Univeristy Press, 1996.


Collaborative Colleagues:
Janet M. Wang: colleagues
Omar A. Hafiz: colleagues
Jun Li: colleagues