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Linear Combinations of DVFS-Enabled Processor Frequencies to Modify the Energy-Aware Scheduling Algorithms

机译:启用DVFS的处理器频率的线性组合,以修改能量敏感的调度算法

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The energy consumption issue in distributed computing systems has become quite critical due to environmental concerns. In response to this, many energy-aware scheduling algorithms have been developed primarily by using the dynamic voltage-frequency scaling (DVFS) capability incorporated in recent commodity processors. The majority of these algorithms involve two passes: schedule generation and slack reclamation. The latter is typically achieved by lowering processor frequency for tasks with slacks. In this paper, we revisit this energy reduction technique from a different perspective and propose a new slack reclamation algorithm which uses a linear combination of the maximum and minimum processor frequencies to decrease energy consumption. This algorithm has been evaluated based on results obtained from experiments with three different sets of task graphs: 1,500 randomly generated task graphs, and 300 task graphs of each of two real-world applications (Gauss-Jordan and LU decomposition). The results show that the amount of energy saved in the proposed algorithm is 13.5%, 25.5% and 0.11% for random, LU decomposition and Gauss-Jordan task graphs, respectively, these percentages for the reference DVFSbased algorithm are 12.4%, 24.6% and 0.1%, respectively.
机译:由于环境问题,分布式计算系统中的能耗问题变得非常关键。响应于此,主要通过使用结合在最近的商品处理器中的动态电压频率缩放(DVFS)功能,开发了许多能量感知调度算法。这些算法中的大多数涉及两步:调度生成和松弛回收。后者通常是通过降低具有松弛任务的处理器频率来实现的。在本文中,我们从不同的角度重新审视了这种节能技术,并提出了一种新的松弛回收算法,该算法使用最大和最小处理器频率的线性组合来降低能耗。该算法已基于使用三组不同的任务图进行实验获得的结果进行了评估:1,500个随机生成的任务图和两个实际应用程序(Gauss-Jordan和LU分解)中每个应用程序的300个任务图。结果表明,对于随机图,LU分解图和高斯-乔丹任务图,该算法节省的能量分别为13.5%,25.5%和0.11%,对于基于DVFS的参考算法,这些百分比分别为12.4%,24.6%和分别为0.1%。

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