In this paper, we describe a worst-case design optimization approach for statistical design of integrated circuits with a circuit performance model scheme. After formulating worst-case optimization to an unconstrained multi-objective function minimization problem, a new objective function is proposed to find an optimal point. Then, based on an interpolation model scheme of approximating circuit performance, realistic worst-case analysis can be easily done by Monte Carlo based method without increasing much the computational load. The effectiveness of the presented approach is demonstrated by a standard test function and a practical circuit design example.

This letter describes a semi-random searching algorithm for global optimization problems which can reduce the number of objective function evaluations significantly via a deterministic criterion and can find a global optimum via a stochastic criterion. The utility of this algorithm is demonstrated by several examples.

IC performance simulation for statistical purpose is usually very time-consuming since the scale and complexity of IC have increased greatly in recent years. A common approach for reduction of simulation cost is aimed at the nature of simple modeling instead of actual circuit performance simulations. In this paper,a stochastic interpolation model (SIM) scheme is proposed which overcomes the drawbacks of the existing polynomial-based approximation schemes. First,the dependence of the R2press statistic upon a parameter in SIM is taken into account and by maximizing R2press this enables SIM to achieve the best approximation accuracy in the given sample points without any assumption on the sample data. Next, a sequential sampling strategy based on variance analysis is described to effectively construct SIM during its update process. In each update step, a new sample point with a maximal value of variance is added to the former set of the sample points. The update process will be continued until the desired approximation accuracy is reached. This would eventually lead to the realization of SIM with a quite small number of sample points. Finally, the coefficient of variance is introduced as another criterion for approximation accuracy check other than the R2press statistic. The effectiveness of presented implementation scheme is demonstrated by several numerical examples as well as a statistical circuit analysis example.