Abstract
Title: Interaction Between TCAD, Compact Models and Circuit Simulation to Support Statistical and Robust Design
Statistical variability, arising from the discreteness of charge and matter, poses increasing challenges to CMOS scaling and integration, and demands the introduction of statistical circuit and system design strategies and verification. It is very important to include accurate information about statistical variability associated with Random Discrete Dopants (RDD), Line Edge Roughness (LER), Poly Gate Granularity (PGG) and other dominant statistical variability sources in the preliminary design kit. Since at this stage the technology is not ready and the variability cannot be measured the statistical physical simulation of the MOSFET reliability becomes a necessity. Compact Models (CM) are the interface between technology and design and the statistical device variability that affects the circuit/system performance and yield must be accurately represented by the industry standard CM. Based on comprehensive statistical 3D simulation results of contemporary MOSFETs we compare different statistical CM parameter identification strategies for BSIM4 and PSP, providing critical information regarding their accuracy. Finally we illustrate the impact of different statistical compact model strategies on the accuracy of statistical circuit simulation.
Bios
Asen Asenov is a James Watt Professor in Electrical Engineering and a Leader of the Glasgow Device Modelling Group. He directs the development of 2D and 3D quantum mechanical, Monte Carlo and classical device simulators and their application in the design of advanced and novel CMOS devices. He has pioneered the simulations of statistical variability in nano-CMOS devices including random dopants, interface roughness and line edge roughness. He has over 530 publications and more than 160 invited talks in the above areas.
