Incorporating temperature-leakage interdependency into dynamic voltage scaling for real-time systems

Energy efficiency is critical for many application specific real-time systems. Dynamic voltage scaling (DVS) is one of the most effective and well-studied techniques. In this paper, we study the interdependency of temperature and leakage and how it influences DVS. We derive an analytic temperature-leakage model, which has an average error of 0.5°K from the accurate numerical result. This temperature-leakage model enables us to perform temperature aware DVS for total energy minimization without using on-chip temperature sensors. We find that the most energy efficient way to complete a single task is, unlike the existing approaches that use high voltage to save leakage, to scale voltage down to the lowest level without missing the task´s deadline. Based on this new finding, we propose an online DVS algorithm to schedule multiple tasks on real-time system. Simulation results show that our algorithm can achieve total energy saving over a state-of-the-art leakage aware DVS approach by as high as 14% and more than 9% on average.