Predictive technology model for nano-CMOS design exploration

Wei Zhao, Yu Cao

Research output: Contribution to journalArticle

131 Citations (Scopus)

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.

Original languageEnglish (US)
Article number1
JournalACM Journal on Emerging Technologies in Computing Systems
Volume3
Issue number1
DOIs
StatePublished - Apr 1 2007

Fingerprint

Silicon
Tuning
Networks (circuits)
Uncertainty
FinFET

Keywords

  • Early design exploration
  • FinFET
  • Predictive modeling
  • Process variations
  • Technology scaling

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering

Cite this

Predictive technology model for nano-CMOS design exploration. / Zhao, Wei; Cao, Yu.

In: ACM Journal on Emerging Technologies in Computing Systems, Vol. 3, No. 1, 1, 01.04.2007.

Research output: Contribution to journalArticle

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