Estimation of average switching power under accurate modeling of signal correlations

Abstract

This paper describes a technique to handle temporal signal correlations during estimation of average power in sequential circuits. A key feature of the approach is that it provides an efficient and accurate way to estimate average power using a Monte Carlo based method. Results on a large number of benchmark sequential circuits confirm that the technique runs efficiently (up to two orders of magnitude better than long run simulation) and yields accurate estimation of average power (on an average within 1% of long run simulation result). Results also indicate that if temporal correlations are ignored, the estimates of average power can be off by more than 55% for some benchmark circuits.