System-Level Energy Management for Periodic Real-Time Tasks

Hakan Aydin, V. Devadas, Dakai Zhu
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引用次数: 143

Abstract

In this paper, we consider the system-wide energy management problem for a set of periodic real-time tasks running on a DVS-enabled processor. Our solution uses a generalized power model, in which frequency-dependent and frequency-independent power components are explicitly considered. Further, variations in power dissipations and on-chip/off-chip access patterns of different tasks are encoded in the problem formulation. Using this generalized power model, we show that it is possible to obtain analytically the task-level energy-efficient speed below which DVS starts to affect overall energy consumption negatively. Then, we formulate the system-wide energy management problem as a non-linear optimization problem and provide a polynomial-time solution. We also provide a dynamic slack reclaiming extension which considers the effects of slow-down on the system-wide energy consumption. Our experimental evaluation shows that the optimal solution provides significant (up to 50%) gains over the previous solutions that focused on dynamic CPU power at the expense of ignoring other power components
周期性实时任务的系统级能量管理
在本文中,我们考虑了运行在支持dvs的处理器上的一组周期性实时任务的全系统能量管理问题。我们的解决方案使用广义功率模型,其中明确考虑了频率相关和频率无关的功率组件。此外,不同任务的功耗和片内/片外访问模式的变化被编码在问题公式中。使用这种广义功率模型,我们表明有可能解析地获得任务级节能速度,低于此速度,DVS开始对总体能耗产生负面影响。然后,我们将系统范围的能量管理问题表述为非线性优化问题,并提供了一个多项式时间解。我们还提供了一个动态松弛回收扩展,该扩展考虑了减速对整个系统能耗的影响。我们的实验评估表明,与之前专注于动态CPU功率的解决方案相比,最优解决方案提供了显著(高达50%)的增益,而忽略了其他功率组件
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