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Power Aware Job Scheduling with QoS Guarantees Based on Feedback Control

机译:基于反馈控制的具有QoS保证的电源感知作业调度

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With the scale of computing system increases, system performance and reliability, described by various Quality of Service(QoS) metrics, cannot be guaranteed if only the objective is to minimize the total power consumptions separately, despite of the violations of QoS. In this paper a feedback control based power aware job scheduling algorithm is proposed to minimize power consumption in computing system and to provide QoS guarantees. In the proposed algorithm, jobs are scheduled according to the real-time and historical power consumption as well as the QoS requirements. Simulations show that the proposed algorithm can reduce power consumptions significantly while still providing QoS guarantees and the performance degradation is acceptable. The results also show that fine-grained job-level power aware scheduling can achieve better power/performance balancing between multiple processors or cores than coarse-grained methods. And the results also suggest that conventional hardware based per-component and system-wide power management methods can save more power consumptions if they are in assistance with job-level adaptation.
机译:随着计算系统规模的扩大,尽管仅违反了QoS的规定,但仅以最小化总功耗为目标,却无法保证通过各种服务质量(QoS)指标描述的系统性能和可靠性。本文提出了一种基于反馈控制的功率感知作业调度算法,以最小化计算系统的功耗并提供QoS保证。在提出的算法中,作业是根据实时和历史功耗以及QoS要求进行调度的。仿真结果表明,该算法在保证QoS的同时,可以显着降低功耗,并且性能下降是可以接受的。结果还表明,与粗粒度方法相比,细粒度的作业级功耗感知调度可以在多个处理器或内核之间实现更好的功率/性能平衡。结果还表明,如果传统的基于硬件的按组件和全系统的电源管理方法可以帮助进行工作级适应,则可以节省更多的功耗。

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