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Cost-Aware Scheduling of Computation-Intensive Tasks on Multi-Core Server

  • Ding, Youwei (College of Information Technology, Nanjing University of Chinese Medicine) ;
  • Liu, Liang (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics) ;
  • Hu, Kongfa (College of Information Technology, Nanjing University of Chinese Medicine) ;
  • Dai, Caiyan (College of Information Technology, Nanjing University of Chinese Medicine)
  • Received : 2017.10.14
  • Accepted : 2018.05.08
  • Published : 2018.11.30

Abstract

Energy-efficient task scheduling on multi-core server is a fundamental issue in green cloud computing. Multi-core processors are widely used in mobile devices, personal computers, and servers. Existing energy efficient task scheduling methods chiefly focus on reducing the energy consumption of the processor itself, and assume that the cores of the processor are controlled independently. However, the cores of some processors in the market are divided into several voltage islands, in each of which the cores must operate on the same status, and the cost of the server includes not only energy cost of the processor but also the energy of other components of the server and the cost of user waiting time. In this paper, we propose a cost-aware scheduling algorithm ICAS for computation intensive tasks on multi-core server. Tasks are first allocated to cores, and optimal frequency of each core is computed, and the frequency of each voltage island is finally determined. The experiments' results show the cost of ICAS is much lower than the existing method.

Keywords

References

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