New Generation of Predictive Technology Model for Sub-45 nm Early Design Exploration

Abstract

A predictive MOSFET model is critical for early circuit design research. To accurately predict the characteristics of nanoscale CMOS, emerging physical effects, such as process variations and correlations among model parameters, must be included. In this paper, a new generation of predictive technology model (PTM) is developed to accomplish this goal. Based on physical models and early-stage silicon data, the PTM of bulk CMOS is successfully generated for 130- to 32-nm technology nodes, with an L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eff</sub> of as low as 13 nm. The accuracy of PTM predictions is comprehensively verified: The error of I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on</sub> is below 10% for both n-channel MOS and p-channel MOS. By tuning only ten primary parameters, the PTM can be easily customized to cover a wide range of process uncertainties. Furthermore, the new PTM correctly captures process sensitivities in the nanometer regime, particularly the interactions among L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eff</sub> , V <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sub> , mobility, and saturation velocity. A website has been established for the release of PTM: http://www.eas.asu.edu/~ptm