STATISTICAL ESTIMATION OF AVERAGE POWER DISSIPATION USING NONPARAMETRIC TECHNIQUES

In this paper,(1) we present a new statistical technique for estimatio n of average power dissipation in digital circuits. The present parame tric statistical technique estimates the average power based on the as sumption that the power distribution can be characterized by a preassu med function. Large error can incur when the assumption is not met. On the other hand, the existing nonparametric technique, although accura te, is too conservative and requires a large sample size in order to a chieve convergence. For a good tradeoff between simulation accuracy an d computational efficiency, we propose a new nonparametric technique u sing the properties of the order statistics. It is generally applicabl e to any type of circuit irrespective of its power distribution functi on. Compared to the existing nonparametric technique, it is much more computationally efficient since it requires a much smaller sample size to achieve the same accuracy specification. This new technique is imp lemented in the distribution-independent power estimation tool (DIPE). DIPE is empirically demonstrated to be more robust and accurate than the parametric technique.