Statistical Modeling with the Virtual Source MOSFET Model
Author(s)Yu, Li; Wei, Lan; Elfadel, Ibrahim M.; Antoniadis, Dimitri A.; Boning, Duane S.
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A statistical extension of the ultra-compact Virtual Source (VS) MOSFET model is developed here for the first time. The characterization uses a statistical extraction technique based on the backward propagation of variance (BPV) with variability parameters derived directly from the nominal VS model. The resulting statistical VS model is extensively validated using Monte Carlo simulations, and the statistical distributions of several figures of merit for logic and memory cells are compared with those of a BSIM model from a 40-nm CMOS industrial design kit. The comparisons show almost identical distributions with distinct run time advantages for the statistical VS model. Additional simulations show that the statistical VS model accurately captures non-Gaussian features that are important for low-power designs.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Massachusetts Institute of Technology. Microsystems Technology Laboratories
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013
Institute of Electrical and Electronics Engineers (IEEE)
Yu, Li, Lan Wei, Dimitri Antoniadis, Ibrahim Elfadel, and Duane Boning. “Statistical Modeling with the Virtual Source MOSFET Model.” Design, Automation & Test in Europe Conference & Exhibition (DATE), 2013 (2013).