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计算机工程 ›› 2019, Vol. 45 ›› Issue (7): 60-65. doi: 10.19678/j.issn.1000-3428.0052735

• 体系结构与软件技术 • 上一篇    下一篇

基于big.LITTLE架构的多目标功耗自适应控制方法

冯国富1,2,3, 舒玉娟1,3, 陈明1,3, 董立夫1,3   

  1. 1. 上海海洋大学 信息学院, 上海 201306;
    2. 江苏中洋集团股份有限公司, 江苏 南通 226600;
    3. 农业部渔业信息重点实验室, 上海 201306
  • 收稿日期:2018-09-25 修回日期:2018-10-24 出版日期:2019-07-15 发布日期:2019-07-23
  • 作者简介:冯国富(1971-),男,副教授,主研方向为高性能计算机系统结构、物联网、嵌入式技术;舒玉娟,硕士研究生;陈明,教授、博士生导师;董立夫,硕士研究生。
  • 基金资助:
    上海市科技创新行动计划项目“小龙虾生态化智能化设施养殖关键技术研究与应用”(16391902900)。

Multi-objective Self-adative Power Consumption Control Method Based on big.LITTLE Architecture

FENG Guofu1,2,3, SHU Yujuan1,3, CHEN Ming1,3, DONG Lifu1,3   

  1. 1. College of Information Technology, Shanghai Ocean University, Shanghai 201306, China;
    2. Jiangsu Zhongyang Group Co., Ltd., Nantong, Jiangsu 226600, China;
    3. Key Laboratory of Fishery Information under Ministry of Agriculture, Shanghai 201306, China
  • Received:2018-09-25 Revised:2018-10-24 Online:2019-07-15 Published:2019-07-23

摘要: 针对移动计算系统功耗约束条件时常变动,以及动态电压频率调节无法有效克服静态功耗导致的能量损失等问题,提出一种多目标功耗自适应控制方法。根据实时功耗约束制定调核策略,确定处理器核类型及数量,结合操作系统线程亲和性、进程迁移与处理器热插拔完成处理器核的开启、关闭及负荷管理,实现功耗自适应。在典型多核应用MapReduce模型Phoenix与可变形部件模型上的实验结果表明,该方法能够按需调度核类型及数量来完成计算任务,与传统功率恒定系统相比,执行时间与能耗平均减少60.91%和48.54%,有效提高目标系统能效。

关键词: big.LITTLE架构, 功耗约束, 静态功耗, 多核处理器, 自适应控制

Abstract: To address the frequent changes of power consumption constraints in mobile computing systems and the energy loss caused by the inability of Dynamic Voltage and Frequency Scaling(DVFS) to effectively overcome the static power consumption,this paper proposes a multi-objective self-adaptive power consumption control method.According to the real-time power consumption constraints,this method formulates the core adjustment strategy to determine the type and number of processor cores,and combines Operating System(OS) thread affinity,process migration and CPU hot-plugging to complete the opening and closing of cores and load management,achieving self-adaptive power consumption.Experimental results on the typical multi-core application MapReduce model Phoenix and Deformable Parts Model(DPM) show that the proposed method can schedule the cores of the suitable type and quantity to complete calculation tasks on demand.Compared with the traditional constant-power system,the execution time and energy consumption are reduced by 60.91% and 48.54% on average,which means the proposed method effectively improves the energy efficiency of the target system.

Key words: big.LITTLE architecture, power consumption constraint, static power consumption, multi-core processor, self-adaptive control

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