SAPOSM - AN OPTIMIZATION METHOD APPLIED TO PARAMETER EXTRACTION OF MOSFET MODELS

In this paper we present a novel optimization program called SaPOSM, a nd its applications to the MOSFET model parameter extraction problems. SaPOSM integrates an efficient deterministic optimization algorithm, called POSM, with the popular stochastic optimization paradigm simulat ed annealing (SA). It offers great promise for improving the optimizat ion results significantly while using only a moderate amount of comput ing time. Tested on a suite of multi-minima optimization benchmark pro blems, SaPOSM's performance rivals a recently reported fast simulated diffusion method. We used SaPOSM to extract the parameters of state-of -the-art submicron (0.3-mum channel length) MOSFET transistors, and ha ve obtained very favorable results. For a second difficult parameter e xtraction problem (18 parameters, five different channel lengths), sim ulation results indicate that SaPOSM achieves performance comparable t o the SA method. Specifically, both SA and SaPOSM are able to minimize the modeling error to several orders of magnitude small than that obt ained using POSM alone. At the same time, the computing time taken by SaPOSM is only a very small fraction of that taken by the SA method.