实时系统温度功耗管理的优化方法研究

Optimization Research on Thermal and Power Management for Real-Time Systems

实时系统的能量受限特性、峰值温度约束以及实时任务的时间约束使其能耗问题备受学术界和工业界的关注,目前已有很多相关功耗管理研究.不考虑温度因素的传统功耗管理大多仅通过动态电压调节技术(dynamic voltage scaling,DVS)方法调度处理器的状态实现,然而随着芯片尺寸的不断缩减,处理器的功耗密度越来越大,温度与功耗之间的相互影响已不容忽视,由此在传统管理研究的基础上又衍生出了很多温度感知的新方法.1)对实时系统温度功耗管理依托的3个模型(任务模型、热模型和功耗模型)进行总结整理;2)根据是否考虑温度因素将现有研究分为温度无关的和温度感知的2类进行综述,后者又按面向单任务/面向多任务进行分类;3)从具体机制、优化目标、优化效果以及调度时间等方面进行比较,分析现有研究的优缺点;4)指出未来研究方向.

Power consumption issue of real‐time system has been paid much attention to by both academia and industry due to its constraints on energy ,peak temperature and deadline of real‐time task . Up to now , there have been many related researches . Temperature‐unaware traditional researches usually adopt DVS to scale processor states for optimal power management . However , with the increasing power density of processors due to the continuous shrinking of chip size ,the mutual effect between temperature and power has become unignorably .As a consequence ,many new temperature‐aware optimization approaches have derived based on the traditional methods .This paper firstly makes an overview of the three models （task ,thermal and power） this research bases on ;secondly ,this paper divides existing researches into two categories ：temperature‐unaware traditional researches and temperature‐aware optimization researches ,and the latter one is further divided as single task optimization and multi‐task scheduling ;thirdly , this paper makes a comparison of the researches from mechanism ,optimization goal and effect ,and scheduling time etc .,analyzing their advantages and disadvantages ;finally ,this paper points out the future research directions .