基于动态电压调节技术的系统功耗优化

分析了现有动态电压调节算法，提出了改进算法的频率设置部分，以提高算法的性能，并在Linux系统上实现了这些算法。经过在物理平台上的测试，表明改进算法能够在不影响性能的情况下减少系统能量消耗。     

RTLPoWer：一个实时动态电压调节低功耗系统

功耗问题是计算机系统发展亟待解决的问题,硬件和软件在解决功耗问题上都有重要的作用.尽管有许多工具可用于低功耗硬件的开发,但支持软件技术开发的低功耗工具并不多见.我们基于ARM的指令集开发了一个实时动态电压调节低功耗系统RTLPower.RTLPower综合了编译指导的动态电压调节和程序的性能功耗模拟,该系统能够有效支持编译指导的动态电压调节技术的研究开发.     

针对离散电压处理器的动态电压调节策略

嵌入式系统设计者在以往设计过程中,通常只考虑到系统的稳定性、实时性等,但现在却面临着一个新的挑战降低系统的功耗.基于LP线性规划模型,针对具有离散工作电压模式的处理器提出了一种动态电压调节策略LPBVSP(LP based voltage scaling policy).LPBVSP能够根据工作负载的需求变化实现处理器...     

基于语法树的实时动态电压调节低功耗算法

动态电压调节是一种有效的低功耗技术.使用这种技术,编译器指导的动态电压调节能够有效地降低系统功耗.提出了基于语言语法树的实时动态电压调节低功耗算法.该算法在静态程序最差时间分析方法的辅助下,通过在程序内部自动插入电压调节代码来实现电压调节.在RTLPower(real-time low-power)实时低功耗系统上完成了算法的实现,对嵌入式测试,程序集的初步测试证明该算法最大可节省50%的能量消耗.     

嵌入式系统动态电压调节设计技术

嵌入式系统的重要特点之一就是工作负载的不均匀性以及动态变化性,可以通过动态关闭设备或者动态调节处理器的工作电压来取得系统性能和功耗之间的平衡。目前已经在系统的多个层次提出了动态电源管理和动态电压调节技术,而且这两种技术已经成为动态低功耗设计过程中的主流技术。本论文则重点阐述动态电压调节设计技术的基本原理和策略模型。     

动态电压调节技术在高性能计算领域的能效研究

功耗问题是未来高性能计算机系统性能提高面临的最突出问题之一,本文调查典型的低功耗技术动态电压调节应用于高性能计算机系统的有效性。建立了动态电压调节技术在高性能计算领域的能耗模型,提出了程序运行时钟能耗和真实能耗的概念。在三种典型的计算机系统上,使用智能功率仪表测试使用动态电压调节技术后的系统能耗,说明了动态电压调节技术在高性能计算领域节能降耗的有效性。     

基于动态电压调节的低功耗视频解码技术研究

讨论在嵌入式系统中使用动态电压调节技术降低视频解码功耗。提出一种基于动态电压调节的低功耗解码技术。该方法采用移动平均法预测帧的解码时间,依据预测的结果动态地调节解码过程中微处理器的工作电压,降低能量消耗。实验结果表明,基于动态电压调节的视频解码器比常规解码器减少10%￣30%的能量消耗。     

基于Markov模型的动态电压调节策略

基于Markov模型,针对具有离散工作电压模式的处理器提出了一种动态电压调节策略MKBVSP（Markov based voltage scaling policy）。MKBVSP能够根据工作负载的需求变化实现处理器工作模式的动态切换,达到系统性能与能耗之间的平衡。实验结果表明,MKBVSP策略能够在更大程度上降低系统平均能耗,最大比率可达58%。     

基于周期性模式匹配的动态电压调节预测算法

zengyi2008@163.com 1 概述 随着计算机在嵌入式、微型化和便携应用等方面的发展,功耗成为重要指标。对于整个计算机系统来说,降低功耗的设计主要从逻辑层、物理层和系统层3个层面来进行。其中,在针对处理器的功耗调节算法中,动态电压调节(Dynamic Voltage Scaling, DVS)[1]被认为是目前最有效的算法。它根据 CPU的负载状况对处理器的供电电压和运行频率进行动态调节,在保证性能需求的前提下降低能量消耗。其算法主要分为2类：基于时间间隔的DVS算法,基于任务的DVS算法。 近些年来,为支持DVS算法降低处理器的运行能耗,不同硬件制造厂商在逻辑电路设计方面相继公布了各种技术,如Intel的speedstep技术,AMD的PowerNow及Cool’n’Quiet技术。然而,实际应用中的动态电压调节算法或多或少会影响系统的性能,主要原因是DVS算法对下一时间片的任务量预测不够准确,难以适应系统需求。 本文在对现有DVS算法分析的基础上,针对past算法预测准确率低的现象进行了改进,在past预测方法中加入周期性模式匹配(Cycle Mode Matching, CMM)预测方式。并对改进算法进行了仿真对比,结果表明改进算法在用户干预少的情况下能有效提高预测的准确性。 2 相关工作 文献[1]给出了3种经典的电压调节算法：opt, past, future。opt和future算法假设可以看到将来一段时间内的CPU使用情况,降低工作频率将运行时间延伸以填补所有的空闲时间周期,从而减少能耗;past算法则将future算法向前看一个时间片改为往后看一个时间片,并假设前后2个时间片内处理器的工作量不变,从而预测出下一时间片处理器的工作量,调节频率以适应当前工作量,达到能耗的节省。     

一种基于混合任务集的高能效调度算法

动态电源与频率调整技术能够帮助实时系统显著减少能耗,之前的研究大多聚焦于基于周期性任务的线程调度算法,却很少考虑周期性与非周期性任务混合的模型。同时,尽管基于CPU利用率的DVS算法可以从系统级上减少能耗,但不能保证实时性。本文提出一种新的算法,它结合减慢因子的DVFS调度算法与系统级的DVS技术,融合PID控制器与自适应的权衡策略为软实时系统提供更好的能耗减少方法。该算法的能耗在服务器利用率低于25%的情况下比加州大学提出的算法下降了14.2%²5.9%,周期性任务超过时限率低于3%。     

一个基于资源操作的强实时动态调压算法

动态调压算法能够降低系统功耗，可用来降低CPU发热量、延长电池供电系统的工作时间．然而，现有动态调压算法均不允许进程进行资源操作（申请或释放资源），这在实际应用中是难以满足的．因此，现有算法不便于实际应用,本文提出了一种新的强实时动态调压算法．该算法允许进程进行资源操作，并且功耗低于现有算法；该算法还能避免死锁．该算法易于应用到实际系统中．     

嵌入式系统中的动态电压调节策略仿真研究

移动式嵌入式系统一般由电池供电,针对高效地利用有限的能量是需要解决的供电问题.分析了现有的动态电压调节策略存在的不足,结合电池放电特性,提出了一种基于电池模型的动态电压调节策略,根据Petri网理论,建立了新的系统能耗模型,并进行了仿真实验.仿真结果分析表明,在满足系统性能的前提下,策略可以使系统能耗最小化的最优频率序列,能很好地降低嵌入式系统能量消耗.为嵌入式系统低功耗策略的研究和应用提供了参考.     

一种基于程序段的动态电压缩放算法

动态电压缩放技术是一种能有效优化处理器能耗的方法,它允许处理器在运行时动态地改变其时钟频率和供电电压.针对处理器提出了一种基于程序段的动态电压缩放算法PBVSA,该算法使用建立在指令工作集签名基础上的程序段监测状态机来判断程序段是否发生变化,并作出CPU电压和频率调整决定,在程序段内,通过计算该段的频率缩放因子β(片外工作时间与片上工作时间的比例关系)来设定CPU的电压和频率,在sim-panalyzer模拟器上完成了算法的实现,通过对Mibench测试程序集的测试表明:该算法平均降低了处理器29%的能耗,而性能损失平均为5.3%.     

Feedback EDF Scheduling of Real-Time Tasks Exploiting Dynamic Voltage Scaling

Many embedded systems are constrained by limits on power consumption, which are reflected in the design and implementation for conserving their energy utilization. Dynamic voltage scaling (DVS) has become a promising method for embedded systems to exploit multiple voltage and frequency levels and to prolong their battery life. However, pure DVS techniques do not perform well for systems with dynamic workloads where the job execution times vary significantly. In this paper, we present a novel approach combining feedback control with DVS schemes targeting hard real-time systems with dynamic workloads. Our method relies strictly on operating system support by integrating a DVS scheduler and a feedback controller within the earliest-deadline-first (EDF) scheduling algorithm. Each task is divided into two portions. The objective within the first portion is to exploit frequency scaling for the average execution time. Static and dynamic slack is accumulated for each task with slack-passing and preemption handling schemes. The objective within the second portion is to meet the hard real-time deadline requirements up to the worst-case execution time following a last-chance approach. Feedback control techniques make the system capable of selecting the right frequency and voltage settings for the first portion, as well as guaranteeing hard real-time requirements for the overall task. A feedback control model is given to describe our feedback DVS scheduler, which is used to analyze the system's stability. Simulation experiments demonstrate the ability of our algorithm to save up to 29% more energy than previous work for task sets with different dynamic workload characteristics. This work was supported in part by NSF grants CCR-0208581, CCR-0310860 and CCR-0312695. Preliminary versions of parts of this work appeared in the ACM SIGPLAN Joint Conference Languages, Compilers, and Tools for Embedded Systems (LCTES'02) and Software and Compilers for Embedded Systems (SCOPES'02) (Dudani et al., 2002), in the Workshop on Compilers and Operating Systems for Low Power 2002 (Zhu and Mueller, 2002) and in the IEEE Real-Time Embedded Technology and Applications Symposium 2004 (Zhu and Mueller, 2004a).     

Toward the Optimal Configuration of Dynamic Voltage Scaling Points in Real-Time Applications

In real-time applications, compiler-directed dynamic voltage scaling （DVS） could reduce energy consumption efficiently, where compiler put voltage scaling points in the proper places, and the supply voltage and clock frequency were adjusted to the relationship between the reduced time and the reduced workload. This paper presents the optimal configuration of dynamic voltage scaling points without voltage scaling overhead, which minimizes energy consumption. The conclusion is proved theoretically. Finally, it is confirmed by simulations with equally-spaced voltage scaling configuration.     

一种动态可重构系统的实时任务调度算法

硬件任务的软实时调度是影响动态可重构系统性能的关键因素之一。本文提出了一种基于顶点链表的硬件任务间最小空间调度算法MSSA,该算法将硬件任务按照长、宽及调度时间构成一个三维资源模型,以到达任务与已放置任务在三维空间的邻接度来构建代价函数,获取具有最大代价函数值的放置位置和启动时间,可使任务安排得更紧凑,减小对系统资源的浪费,提高并行度。仿真实验表明,与MSG-4V和Stuffing算法相比,本文算法具有更高的芯片利用率和任务接受率。     

Dynamic Voltage Scaling for Digital Control System Implementation

For real-time computer-controlled systems, control performances of tasks as well as energy consumption of overall system must be optimized. A control task does not have a fixed period but a range of periods in which the control performance varies. Hence, when more than one control tasks are scheduled on a single processor, an optimization problem appears. Furthermore, when an energy saving technique such as dynamic voltage scaling is used, its properties affect the control performance.Using a performance index that involves control performance and energy consumption, a static solution is proposed to obtain the optimal processor speed and a set of periods for given control tasks in O(k). Also a dynamic solution is proposed to utilize system services of real-time operating systems to overcome unavoidable deficiencies of the static solution and to further reduce the energy consumption of the overall system. The performances of proposed solutions are revealed via simulation studies.Hyung Sun Lee received his B.S. and M.S. degrees in electronics engineering from Korea Advanced Institute of Science and Technology (KAIST) in 2000 and 2002, respectively. He is currently a Ph.D. student in the Department of Electrical Engineering and Computer Science (EECS) at KAIST. His research interests include real-time control and power-aware real-time embedded systems.Byung Kook Kim received his B.S. degree in Electronics Engineering from Seoul National University in 1975, and his M.S. and Ph.D. degrees from KAIST in 1977 and 1981, respectively. Dr. Kim was a manager and founder of the Calibration Laboratory, Woojin Instrument Co. Ltd, in 1981. He performed his postdoctoral research at the University of Michigan, Ann Arbor, Michigan, from 1982 to 1983. He returned to Woojin Instruments as a chief researcher of the R&D Department from 1984 to 1986. He joined the faculty of the Department of Electrical Engineering at KAIST in 1986, where he is currently a professor. His research interests include real-time systems, parallel and distributed systems, fault-tolerant computing, mobile robot sensing and navigation, and manipulator control.     

多核系统中基于动态电压频率调节的实时节能调度研究

在实时嵌入式领域,特别是无线移动和便携式计算领域,能耗是首要考虑的因素,这也是多核处理器尚未在嵌入式领域全面展开应用的首要因素。目前针对多核系统的实时应用,基于动态电压频率调节(DVFS)的实时节能调度技术研究得较少,还有许多问题亟待解决。本文介绍了多核系统中动态电压频率调节技术,分析讨论了当前多核系统中实时调度研究进展,主要针对同构多核、异构多核、并行任务模型和弱硬实时模型等方面,深入探讨了多核系统中基于DVFS的实时节能调度。本文结合多核系统、电压频率动态调节节能和实时调度,探索了多核系统中的实时节能调度,奠定了理论和技术基础,具有重大的理论意义和现实应用价值。