ISAECC: An Improved Scheduling Approach for Energy Consumption Constrained Parallel Applications on Heterogeneous Distributed Systems
Ting Ye, Zhijie Wang, Zhe Quan, Song Guo, Kenli Li, Keqin Li · 2018
Power-aware task scheduling on processors has been a hot topic. In this paper, we study the problem of minimizing the schedule length for energy consumption constrained parallel applications on heterogeneous distributed systems. Previous work (solving this problem) adopts a policy that preassigns the minimum energy consumption for each unassigned task. Nevertheless, our analysis reveals that such a preassignment policy could be unfair, and it may not achieve an optimistic schedule length. Motivated by this, we propose a new task scheduling algorithm that suggests a weight-based mechanism to preassign energy consumption for unassigned tasks. We theoretically prove that our preassignment mechanism can guarantee the energy consumption constraint. Also, we have conducted extensive experiments based on two real parallel applications. The results consistently demonstrate that, compared to state-of-the-art algorithms, our approach can achieve smaller schedule length while satisfying the energy consumption constraint.