Stochastic Interpolation Model Scheme and Its Application to Statistical Circuit Analysis (Special Section on the 6th Karuizawa Workshop on Circuits and Systems)

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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 R^<press> statistic upon a parameter in SIM is taken into account and by maximizing R^<press> 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 R^<press> statistic. The effectiveness of presented implementation scheme is demonstrated by several numerical examples as well as a statistical circuit analysis example.
社団法人電子情報通信学会の論文
1994-03-25

Stochastic Interpolation Model Scheme and Its Application to Statistical Circuit Analysis (Special Section on the 6th Karuizawa Workshop on Circuits and Systems)

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