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Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks in a Cluster with DVFS

机译:面向具有DVFS的群集中优先约束的并行任务的能量感知调度

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Reducing energy consumption for high end computing can bring various benefits such as, reduce operating costs, increase system reliability, and environment respect. This paper aims to develop scheduling heuristics and to present application experience for reducing power consumption of parallel tasks in a cluster with the Dynamic Voltage Frequency Scaling (DVFS) technique. In this paper, formal models are presented for precedence-constrained parallel tasks, DVFS enabled clusters, and energy consumption. This paper studies the slack time for non-critical jobs, extends their execution time and reduces the energy consumption without increasing the taskȁ9;s execution time as a whole. Additionally, Green Service Level Agreement is also considered in this paper. By increasing task execution time within an affordable limit, this paper develops scheduling heuristics to reduce energy consumption of a tasks execution and discusses the relationship between energy consumption and task execution time. Models and scheduling heuristics are examined with a simulation study. Test results justify the design and implementation of proposed energy aware scheduling heuristics in the paper.
机译:减少高端计算的能耗可以带来各种好处,例如,降低运营成本,提高系统可靠性和对环境的尊重。本文旨在开发调度启发式方法,并介绍使用动态电压频率缩放(DVFS)技术减少群集中并行任务的功耗的应用经验。在本文中,为约束优先级的并行任务,启用DVFS的群集和能耗提供了正式模型。本文研究了非关键作业的松弛时间,延长了它们的执行时间,并减少了能源消耗,而总体上并没有增加任务9的执行时间。此外,本文还考虑了绿色服务水平协议。通过在负担得起的限度内增加任务执行时间,本文开发了调度启发法以减少任务执行的能耗,并讨论了能耗与任务执行时间之间的关系。通过仿真研究检查模型和调度启发式方法。测试结果证明了本文提出的能量感知调度启发式算法的设计和实现是合理的。

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