Points out that SaPOSM integrates an efficient deterministic optimization algorithm, called POSM, with the popular stochastic optimization paradigm simulated annealing (SA). It offers great promise for improving the optimization results significantly while using only a moderate amount of computing time. Tested on a suite of multi-minima optimization benchmark problems, SaPOSM's performance rivals a recently reported fast simulated diffusion method. SaPOSM was used to extract the parameters of state-of-the-art submicron (0.3- mu m channel length) MOSFET transistors, and very favorable results have been obtained. For a second difficult parameter extraction problem (18 parameters, five different channel lengths), simulation results indicate that SaPOSM achieves performance comparable to the SA method. Specifically, both SA and SaPOSM are able to minimize the modeling error to several orders of magnitude smaller than that obtained 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.>

An efficient optimization method for the statistical design of integrated circuits is presented. This method, called the pseudo yield function substitution (PYFS) algorithm, is developed to help a designer select design parameters to maximize the product yield. The design goal of PYFS is to use fewer simulation runs to reach a yield-optimized design. This is accomplished with the development of an improved response surface method for accurate estimation of the circuit response function, and the use of a novel PYFS method for yield maximization.>