Predictive technology model for nano-CMOS design exploration

  • Authors:
  • Wei Zhao;Yu Cao

  • Affiliations:
  • Arizona State University. Tempe, AZ;Arizona State University. Tempe, AZ

  • Venue:
  • ACM Journal on Emerging Technologies in Computing Systems (JETC)
  • Year:
  • 2007

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Abstract

A predictive MOSFET model is critical for early circuit design research. In this work, a new generation of Predictive Technology Model (PTM) is developed, covering emerging physical effects and alternative structures, such as the double-gate device (i.e., FinFET). Based on physical models and early stage silicon data, PTM of bulk and double-gate devices are successfully generated from 130nm to 32nm technology nodes, with effective channel length down to 13nm. By tuning only ten primary parameters, PTM can be easily customized to cover a wide range of process uncertainties. The accuracy of PTM predictions is comprehensively verified with published silicon data: the error of the current is below 10% for both NMOS and PMOS. Furthermore, the new PTM correctly captures process sensitivities in the nanometer regime. PTM is available online at http://www.eas.asu.edu/~ptm.