IEEE Transactions on Electron Devices · 2014 · 66 citations · 17 references
EngineeringComputer EngineeringDesignDesign AutomationDesign OptimizationSimulation-based DesignCmos Circuit DesignDesign SimulationDesign Space ExplorationDevice ModelingDevice SimulationIntegrated Circuit DesignDevice VariabilityMetal-oxide-semiconductor Field-effect Transistor ModelingNoise Margin AnalysisProcess Variation AnalysisProcess Variation ToleranceStatic Noise MarginVariability AnalysisVariability Modeling
The study develops an automated 14 nm FinFET/SRAM DTCO flow that incorporates process‑induced and intrinsic statistical variabilities and evaluates static and write noise margin sensitivity to design parameters. The flow combines predictive TCAD and draft‑diffusion simulations calibrated to ensemble Monte Carlo results, a two‑stage compact model, and a 22 nm FinFET illustration to capture the interplay between process variations and statistical variability. Automation of the tool flow and dataset handling enabled a detailed examination of the interaction between process and statistical variability, revealing its impact on noise margin performance.
In this paper, we use an automated tool flow in a 14 nm CMOS fin-shaped field-effect transistor (FinFET)/ static random access memory (SRAM) simulation-based design-technology cooptimization (DTCO) including both process-induced and intrinsic statistical variabilities. A 22 nm FinFET CMOS technology is used to illustrate the sensitivity to process-induced fin shape variation and to motivate this paper. Predictive Technology Computer Aided Design (TCAD) simulations have been carried out to evaluate the transistor performance ahead of silicon. Draft-diffusion simulations calibrated to the ensemble Monte Carlo simulation results are used to explore the process and the statistical variability space. This has been enabled by the automation of the tool flow and the dataset handling. The interplay between the process and the statistical variability has been examined in details. A two-stage compact model strategy is used to capture the interplay between process and statistical variability. To close the DTCO loop, the static noise margin and write noise margin sensitivity to cell design parameters and variability in FinFET-based SRAM designs are studied in details.
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28nm FDSOI technology platform for high-speed low-voltage digital applications
N. Planes, O. Weber, V. Barral et al. · 2012 · 424 citations
Engineering, Computer Engineering, Electrical Engineering +16
Tejas Jhaveri, Vyacheslav Rovner, Lars W. Liebmann et al. · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems · 2010 · 98 citations
Engineering, Computer Engineering, Electrical Engineering +17