Energy optimization is a critical design concern for embedded systems. Combining DVFS+DPM is considered as one preferable technique to reduce energy consumption. There have been optimal DVFS+DPM algorithms for periodic independent tasks running on uniprocessor in the literature. Optimal combination of DVFS and DPM for periodic dependent tasks on multicore systems is however not yet reported. The challenge of this problem is that the idle intervals of cores are not easy to model. In this article, a novel technique is proposed to directly model the idle intervals of individual cores such that both DVFS and DPM can be optimized at the same time. Based on this technique, the energy optimization problem is formulated by means of mixed integrated linear programming. We also present techniques to prune the exploration space of the formulation. Experimental results using real-world benchmarks demonstrate the effectiveness of our approach compared to existing approaches.
Recently, the state-of-the-art work in REF introduced a key technique to model the idle interval of the cores by means of MILP.
Energy optimization for real-time multiprocessor system-on-chip with optimal DVFS and DPM combination
TECS
Computer Science