A Heuristic Energy-aware Scheduling Algorithm for Heterogeneous Clusters

With the rapid development of supercomputers, the power consumption by large scale computer systems has become a big concern. How to reduce the power consumption is now a critical issue in designing high performance computers. Energy-aware scheduling for large scale clusters, especially the high performance heterogeneous ones, is one of the strategies for energy saving. Proposed in this paper is a novel energy-aware task scheduling algorithm (EAMM) for heterogeneous clusters, which is based on the general adaptive scheduling heuristics min-min algorithm. The algorithm is evaluated on a simulated heterogeneous cluster. The experiment results show that the new energy-aware algorithm can achieve a good time-energy trade-off and outperform the original min-min algorithm under various conditions.