Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2010-11-13
Computer Science
Distributed, Parallel, and Cluster Computing
The 5th International Conference on Frontier of Computer Science and Technology (FCST), IEEE, Changchun, China, August 2010
Scientific paper
It is an increasingly important issue to reduce the energy consumption of computing systems. In this paper, we consider partition based energy-aware scheduling of periodic real-time tasks on multicore processors. The scheduling exploits dynamic voltage scaling (DVS) and core sleep scheduling to reduce both dynamic and leakage energy consumption. If the overhead of core state switching is non-negligible, however, the performance of this scheduling strategy in terms of energy efficiency might degrade. To achieve further energy saving, we extend the static task scheduling with run-time task reallocation. The basic idea is to aggregate idle time among cores so that as many cores as possible could be put into sleep in a way that the overall energy consumption is reduced. Simulation results show that the proposed approach results in up to 20% energy saving over traditional leakage-aware DVS.
Huang Hongtao
Lei Siyu
Wang Jijie
Wu Guowei
Xia Feng
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