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Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions

机译:不同操作条件下分布式计算系统的能源意识调度

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Traditionally, the primary performance goal of computer systems has focused on reducing the execution time of applications while increasing throughput. This performance goal has been mostly achieved by the development of high-density computer systems. As witnessed recently, these systems provide very powerful processing capability and capacity. They often consist of tens or hundreds of thousands of processors and other resource-hungry devices. The energy consumption of these systems has become a major concern. In this paper, we address the problem of scheduling precedence-constrained parallel applications on multiprocessor computer systems and present two energy-conscious scheduling algorithms using dynamic voltage scaling (DVS). A number of recent commodity processors are capable of DVS, which enables processors to operate at different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. To effectively balance these two performance goals, we have devised a novel objective function and a variant from that. The main difference between the two algorithms is in their measurement of energy consumption. The extensive comparative evaluations conducted as part of this work show that the performance of our algorithms is very compelling in terms of both application completion time and energy consumption.
机译:传统上,计算机系统的主要性能目标集中在减少应用程序的执行时间,同时提高吞吐量。该性能目标主要是通过开发高密度计算机系统来实现的。如最近所见证的,这些系统提供了非常强大的处理能力。它们通常由数以万计的处理器和其他占用大量资源的设备组成。这些系统的能耗已成为主要问题。在本文中,我们解决了在多处理器计算机系统上调度优先顺序受限的并行应用程序的问题,并提出了两种使用动态电压缩放(DVS)的节能意识调度算法。许多最新的商用处理器都具有DVS的功能,这使处理器能够以不同的电压供应水平工作,而以牺牲时钟频率为代价。在调度的上下文中,这种多电压功能意味着在调度的质量和能耗之间要进行权衡。为了有效地平衡这两个绩效目标,我们设计了一个新颖的目标函数和一个新的目标函数。两种算法之间的主要区别在于它们的能耗测量。作为这项工作的一部分,进行了广泛的比较评估,结果表明,就应用程序完成时间和能耗而言,我们算法的性能非常引人注目。

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