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

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
_eff
of as low as 13 nm. The accuracy of PTM predictions is comprehensively verified: The error of I
_on
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
_eff
, V
_th
, mobility, and saturation velocity. A website has been established for the release of PTM: http://www.eas.asu.edu/~ptm