Accelerating Dynamic Peak Power Analysis Using An Essential-Signal-Based Methodology

Abstract

Accurate peak power measurement requires detailed switching and delay information for each signal over the entire simulation. Performing a full signal dump and power calculation for a long simulation run usually spends a large amount of time and disk space. In this paper, we propose an Essential-signal-based methodology which only performs power analysis over a small subset of the original simulation but still acquires the true peak power value. Experimental results show that the proposed methodology significantly decreases both time (about 18 X speedup) and disk space usage (about 87% reduction) against the traditional power analysis flow.