[paper] Automatic Parameter Extraction of MOSFET Compact Models

Gazmend Alia^1,2, Andi Buzo¹, Hannes Maier-Flaig¹, Klaus-Willi Pieper¹, 

Linus Maurer²  and Georg Pelz¹

Automatic Parameter Extraction of MOSFET Compact Models using Differential Evolution with Population Prediction (DEpred)

6th EDTM; March 6 to 9, 2022 

   
1 Infineon Technologies AG, Munich (D)
2 Bundeswehr University Munich (D)

Abstract: Parameter extraction of MOSFET compact models with hundreds of parameters is not a trivial task. Differential evolution (DE) has proven to be very effective in such highly dimensional parameter spaces. However, DE needs a large number of iterations to converge. This paper proposes a novel method to accelerate the convergence of DE by predicting tens of iterations ahead where the population will be, based on the knowledge from the already finished iterations. The method is validated with BSIM4 and HiSIM-HV compact models, where up to 50% of the iterations are saved.

Fig: DE vs DEpred cost function for BSIM4 and HiSIM-HV models.
DEpred reaches the target 50% faster.