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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: 2196

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yong-xing Liu

http://orcid.org/0000-0001-8935-9543

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

http://doi.org/10.1631/FITEE.1400399


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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Abstract: 
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.

面向异构系统的节能调度算法

目的:当前,异构计算系统面临能量消耗巨大的严峻问题,降低系统运行过程中能量消耗成为一个亟待解决的问题。任务调度作为计算系统中的核心部分,起着对计算资源进行全局管理和分配的关键作用。本文结合调度算法与动态电压调节技术来优化系统的总能量消耗。
创新点:本文用有向无环图来表示应用模型,并对其进行重构,使得应用能够被更加合理地调度和分配。在优化系统能量消耗的过程中,本文通过均衡两个任务间的处理器空闲时间来降低系统能量消耗,并以递进方式处理剩余任务。
方法:在建立计算系统模型和应用模型后,算法对应用中的路径集进行提取,并基于路径集对应用进行重构。为优化系统的总能量消耗,算法采取递进的方式来均衡任务的运行频率。最后用实验验证算法性能。
结论:针对异构系统环境,提出一个基于动态电压调节技术的节能调度算法。该算法通过优化任务分配来减少应用的完成时间,并通过均衡任务间的处理器空闲时间来降低系统的总能量消耗。文中通过大量的实验对算法的性能进行了评估,并分析了实验结果,实验结果证明了算法的有效性(图6-10)。

关键词:有向无环图;动态电压调节;节能调度;异构系统;任务调度

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

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