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Discrete and continuous min-energy schedules for variable voltage processors

机译:可变电压处理器的离散和连续最小能量计划

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摘要

Current dynamic voltage scaling techniques allow the speed of processors to be set dynamically to save energy consumption, which is a major concern in microprocessor design. A theoretical model for min-energy job scheduling was first proposed a decade ago, and it was shown that for any convex energy function, the min-energy schedule for a set of n jobs has a unique characterization and is computable in O(n3) time. This algorithm has remained as the most efficient known despite many investigations of this model. In this work, we give an algorithm with running time O(n2 log n) for finding the min-energy schedule. In contrast to the previous algorithm, which outputs optimal speed levels from high to low iteratively, our algorithm is based on finding successive approximations to the optimal schedule. At the core of the approximation is an efficient partitioning of the job set into high and low speed subsets by any speed threshold, without computing the exact speed function.
机译:当前的动态电压缩放技术允许动态设置处理器的速度以节省能耗,这​​是微处理器设计中的主要问题。最小能量作业调度的理论模型是在十年前首次提出的,它表明对于任何凸能量函数,一组n个作业的最小能量调度都具有唯一的特征,并且可以在O(n < sup> 3 )时间。尽管对该模型进行了许多研究,但该算法仍然是已知的最有效算法。在这项工作中,我们给出了一种运行时间为O(n 2 log n)的算法来查找最小能量调度。与之前的算法迭代地从高到低输出最佳速度水平的算法不同,我们的算法基于找到最佳调度的逐次逼近。近似的核心是通过任何速度阈值将作业集有效划分为高速度和低速度子集,而无需计算确切的速度函数。

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