Improving the Scheduler's Energy Saving Capability by Noting both Job and Resource Characteristics

Although the growth in the scale and complexity is the response of High Performance Computing (HPC) systems like computational grids to the ever-increasing demand for high processing capacity, it also makes these systems considerable energy consumers. In fact, high energy consumption is the new challenge in front of performance improvement of HPC systems and thus power management is now a necessity for them. One of the major components that can have a great role in the power-saving process is the scheduler. In this paper, a new power-aware scheduling algorithm is proposed by incorporating the characteristics of both job and resource into the job mapping and ordering, and frequency-setting decision steps. In addition to the analytical study, the proposed scheduler has been evaluated based on results obtained from experiments in different resources heterogeneity levels and workload conditions. The results show the greater capability of the proposed scheduling algorithm in comparison with other related approaches.