Impact of statistical parameter set selection on the statistical compact model accuracy: BSIM4 and PSP case study

Authors:
Negin Moezi;Daryoosh Dideban;Binjie Cheng;Scott Roy;Asen Asenov
Affiliations:
Device Modeling Group in School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;Device Modeling Group in School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;Device Modeling Group in School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;Device Modeling Group in School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;Device Modeling Group in School of Engineering, University of Glasgow, Glasgow G12 8LT, UK and Gold Standard Simulations Ltd, Rankine Building, Glasgow G12 8LT, UK
Venue:
Microelectronics Journal
Year:
2013

Citing 4
Cited 0

High-performance CMOS variability in the 65-nm regime and beyond

IBM Journal of Research and Development - Advanced silicon technology
Modeling Process Variability in Scaled CMOS Technology

IEEE Design & Test
Statistical-Variability Compact-Modeling Strategies for BSIM4 and PSP

IEEE Design & Test
Capturing intrinsic parameter fluctuations using the PSP compact model

Proceedings of the Conference on Design, Automation and Test in Europe

Quantified Score

Hi-index	0.00

Visualization

Abstract

Statistical compact modeling (SCM) is necessary for variability aware design at nanometer regime. An extensive study has been carried out to evaluate the impact of the statistical parameter set selection on the statistical accuracy of two widely used industry standard compact models: BSIM4 and PSP. Different statistical parameter generation strategies have been employed to examine the impact of different statistical parameter selection on both device and circuit simulation accuracy.