Prediction of leakage power under process uncertainties

In this article, we present a method to analyze the total leakage current of a circuit under process variations, considering interdie and intradie variations as well as the effect of the spatial correlations of intradie variations. The approach considers both the subthreshold and gate tunneling leakage power, as well as their interactions. With process variations, each leakage component is approximated by a lognormal distribution, and the total chip leakage is computed as a sum of the correlated lognormals. Since the lognormals to be summed are large in number and have complicated correlation structures due to both spatial correlations and the correlation among different leakage mechanisms, we propose an efficient method to reduce the number of correlated lognormals for summation to a manageable quantity. We do so by identifying dominant states of leakage currents and taking advantage of the spatial correlation model and input states at the gates. An improved approach utilizing the principal components computed from spatially correlated process parameters is also proposed to further improve runtime efficiency. We show that the proposed methods are effective in predicting the probability distribution of total chip leakage, and that ignoring spatial correlations can underestimate the standard deviation of full-chip leakage power.