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CLC number: TP314

On-line Access: 2015-07-06

Received: 2014-11-24

Revision Accepted: 2015-04-30

Crosschecked: 2015-06-05

Cited: 2

Clicked: 6133

Citations:  Bibtex RefMan EndNote GB/T7714


Yong-xing Liu


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Frontiers of Information Technology & Electronic Engineering  2015 Vol.16 No.7 P.519-531


Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems

Author(s):  Yong-xing Liu, Ken-li Li, Zhuo Tang, Ke-qin Li

Affiliation(s):  College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China; more

Corresponding email(s):   yongxing510@126.com, lkl@hnu.edu.cn

Key Words:  Directed acyclic graph, Dynamic voltage scaling, Energy aware, Heterogeneous systems, Task scheduling

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Yong-xing Liu, Ken-li Li, Zhuo Tang, Ke-qin Li. Energy-aware scheduling with reconstruction and frequency equalization on heterogeneous systems[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(7): 519-531.

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With the increasing energy consumption of computing systems and the growing advocacy for green computing, energy efficiency has become one of the critical challenges in high-performance heterogeneous computing systems. Energy consumption can be reduced by not only hardware design but also software design. In this paper, we propose an energy-aware scheduling algorithm with equalized frequency, called EASEF, for parallel applications on heterogeneous computing systems. The EASEF approach aims to minimize the finish time and overall energy consumption. First, EASEF extracts the set of paths from an application. Then, it reconstructs the application based on the extracted set of paths to achieve a reasonable schedule. Finally, it adopts a progressive way to equalize the frequency of tasks to reduce the total energy consumption of systems. Randomly generated applications and two real-world applications are examined in our experiments. Experimental results show that the EASEF algorithm outperforms two existing algorithms in terms of makespan and energy consumption.

This paper proposes a scheduling method for the heterogeneous computing system to reduce the energy consumption, as called Heterogeneous Energy-Aware Scheduling (HEAS) algorithm, which consists of three stages: 1) generating the critical paths, 2) reconstructing the directed acyclic graph (DAG) and calculating task priority, and 3) scheduling the task with energy-awareness. Overall, the paper is well written and clearly organized.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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