Stratified random sampling for power estimation

In this paper, we present new statistical sampling techniques for performing power estimation at the circuit level. These techniques first transform the power estimation problem to a survey sampling problem, and then apply stratified random sampling to improve the efficiency of sampling. The stratification is based on a low-cost predictor, such as the zero-delay power estimate. We also propose a two-stage stratified sampling technique to handle very long initial sequences. Experimental results show that the efficiency of stratified random sampling and two-stage stratified sampling techniques are 3-10 times higher than that of simple random sampling and the Markov-based Monte Carlo simulation techniques.