Presentation
A PCA and KDE Based Approach for Statistical CMOS Compact Model Parameter Generation
DescriptionLarge-scale integrated circuit simulations need statistical transistor compact models to reflect the influence of statistical variability when predicting circuit behavior. This paper proposes a novel compact model parameter generation approach based on Principal Component Analysis (PCA) and Kernel Density Estimation (KDE). This approach can generate infinite BSIM-CMG compact model parameters on a fly while following the original parameter distribution and maintaining correlations between different parameters. We introduce the methodology and use 1000 nanosheet devices from TCAD simulation under the influence of RDF and WFV for the final compact model parameter generation. Firstly, 1000 BSIM-CMG compact models are extracted against the TCAD data using our automatic parameter extraction platform. Then 10000 compact model parameters are generated using the generation method. The results show a good retention of the TCAD simulated electrical characteristics and give promising prospects for large-scale integrated circuit simulations.
Event Type
Networking
Work-in-Progress Poster
TimeMonday, June 236:00pm - 7:00pm PDT
LocationLevel 2 Lobby