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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. The new model formulates the interconnect parametric uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) and Linear Matrix Inequalities (LMI's), the porposed model reduces the order of the original interconnect network while preserves the stability. The LFT based new model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) generated from Lur'e equations. In case of large number of uncertain parameters, the new model may be applied successively: the uncertain parameters are partitioned into groups, and with regard to each group, LFT based model is applied in turns.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E92-A No.4 pp.1148-1160

- Publication Date
- 2009/04/01

- Publicized

- Online ISSN
- 1745-1337

- DOI
- 10.1587/transfun.E92.A.1148

- Type of Manuscript
- PAPER

- Category
- VLSI Design Technology and CAD

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Omar HAFIZ, Alexander MITEV, Janet Meiling WANG, "A Linear Fractional Transform (LFT) Based Model for Interconnect Uncertainty" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 4, pp. 1148-1160, April 2009, doi: 10.1587/transfun.E92.A.1148.

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. The new model formulates the interconnect parametric uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) and Linear Matrix Inequalities (LMI's), the porposed model reduces the order of the original interconnect network while preserves the stability. The LFT based new model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) generated from Lur'e equations. In case of large number of uncertain parameters, the new model may be applied successively: the uncertain parameters are partitioned into groups, and with regard to each group, LFT based model is applied in turns.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1148/_p

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@ARTICLE{e92-a_4_1148,

author={Omar HAFIZ, Alexander MITEV, Janet Meiling WANG, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={A Linear Fractional Transform (LFT) Based Model for Interconnect Uncertainty},

year={2009},

volume={E92-A},

number={4},

pages={1148-1160},

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. The new model formulates the interconnect parametric uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) and Linear Matrix Inequalities (LMI's), the porposed model reduces the order of the original interconnect network while preserves the stability. The LFT based new model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) generated from Lur'e equations. In case of large number of uncertain parameters, the new model may be applied successively: the uncertain parameters are partitioned into groups, and with regard to each group, LFT based model is applied in turns.},

keywords={},

doi={10.1587/transfun.E92.A.1148},

ISSN={1745-1337},

month={April},}

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TY - JOUR

TI - A Linear Fractional Transform (LFT) Based Model for Interconnect Uncertainty

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 1148

EP - 1160

AU - Omar HAFIZ

AU - Alexander MITEV

AU - Janet Meiling WANG

PY - 2009

DO - 10.1587/transfun.E92.A.1148

JO - IEICE TRANSACTIONS on Fundamentals

SN - 1745-1337

VL - E92-A

IS - 4

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - April 2009

AB - 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. The new model formulates the interconnect parametric uncertainty as a repeated scalar uncertainty structure. With the help of generalized Balanced Truncation Realization (BTR) and Linear Matrix Inequalities (LMI's), the porposed model reduces the order of the original interconnect network while preserves the stability. The LFT based new model even guarantees passivity if the BTR reduction is based on solutions to a pair of Linear Matrix Inequalities (LMI's) generated from Lur'e equations. In case of large number of uncertain parameters, the new model may be applied successively: the uncertain parameters are partitioned into groups, and with regard to each group, LFT based model is applied in turns.

ER -