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首页> 外文期刊>Concurrency and computation: practice and experience >Energy-efficient scheduling algorithms for batch-of-tasks (BoT) applications on heterogeneous computing systems
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Energy-efficient scheduling algorithms for batch-of-tasks (BoT) applications on heterogeneous computing systems

机译：异构计算系统上的批处理任务（BoT）应用的节能调度算法

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摘要

One of the major design constraints of a heterogeneous computing system is optimal scheduling, that is, mapping of tasks on the processing nodes in order to optimize the QoS parameters. Because of the huge energy consumption by computing resources, negative environmental effects and reduced system reliability, energy has unavoidably been added as a new parameter to the list of QoS parameters. Energy optimization in scheduling strategies along with makespan makes it an even more challenging combinatorial optimization problem. This work proposes two energy-aware scheduling algorithms G1 and G2 to schedule a batch-of-tasks, made of a collection of independent tasks, on heterogeneous processors in order to minimize the makespan and the energy consumption. The proposed algorithms schedule tasks based on weighted aggregation cost function to the appropriate processors followed by task migration phase designed to further minimize the makespan and the energy consumption. The study evaluates the performance of the proposed algorithms with some of the peers, that is, MinMin, MINSuff on account of makespan, energy consumption, flowtime, and utilization. An experimental study reveals that the proposed algorithm (G2) consistently performs better under various test conditions. Copyright © 2015 John Wiley & Sons, Ltd.
机译：异构计算系统的主要设计约束之一是最优调度，即优化处理参数在处理节点上的映射。由于计算资源的巨大能耗，不利的环境影响和降低的系统可靠性，因此不可避免地将能量作为新参数添加到QoS参数列表中。调度策略中的能量优化以及makepan使它成为更具挑战性的组合优化问题。这项工作提出了两种能量感知调度算法G1和G2，以在异构处理器上调度由一组独立任务组成的一批任务，以最大程度地减少制造时间和能耗。所提出的算法将基于加权聚合成本函数的任务调度到适当的处理器，随后是任务迁移阶段，该任务迁移阶段旨在进一步最小化制造周期和能耗。这项研究与一些同行（即MinMin，MINSuff）一起评估了所提出算法的性能，这涉及到制造时间，能耗，流动时间和利用率。实验研究表明，所提出的算法（G2）在各种测试条件下始终具有更好的性能。版权所有©2015 John Wiley＆Sons，Ltd.

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