基于电源管理技术降低嵌入式系统功耗的研究

嵌入式处理器产品既要求提高其性能又要求降低功耗,这是互相矛盾的两个方面。但是,高性能处理必须增加计算复杂度并加快时钟速率,如果采用权宜之计的节省功耗设计方案,是很难实现的。介绍利用B lackfin数字信号处理器系列产品固有的动态电源管理方法来管理功耗,以便在具体的嵌入式应用中优化性能与功耗的关系,较好地解决降低嵌入式系统功耗问题。     

动态电源管理技术优化嵌入式应用性能与功耗比

消费者对采用多媒体嵌入式处理器产品的需求迅速增长,这既要求提高性能又要求降低功耗.但是高性能处理必须增加计算复杂度并加快时钟速率,如果采用权宜之计的节省功耗设计方案,是很难实现的.我们需要的是一种具有战略意义的方法来管理功耗,以便在具体的嵌入式应用中优化性能与功耗的关系.利用Blackfin数字信号处理器(DSP)系列产品固有的动态电源管理能力,可以实现这样的方法.     

低功耗SOC的动态时钟管理

介绍了一种系统级设计的时钟管理方案以及功耗管理模块的实现;分析了该方案在实现中可能存在的问题,并给出解决方法。此方案可以显著地降低时钟网络的动态功耗,弥补了现有工具只能在设计后期才能发挥作用的不足,达到了降低整个SOC芯片功耗的目的;引用具体设计项目,说明系统如何动态地调节时钟频率。     

一种带植入式数字信号处理器的新型人工耳蜗系统

提出了一种带植入式数字信号处理器的人工耳蜗系统.该系统只需在无线通道中传输低码率的语音信号,不存在数据码率受限的问题,有利于人工耳蜗未来的发展.通过优化语音处理算法和数字信号处理器硬件设计,植入式的处理器可以在3MHz的时钟频率下执行连续相间采样(CIS)算法,功耗仅为1.91mW.根据理论分析得到的无线能量传输效率(40%),可以推算出由于处理器植入所增加的功耗是2.87mW,与现有的商用人工耳蜗系统整机功耗(几十毫瓦)相比微乎其微.由于处理器的植入,新系统可以很容易扩展成全植入式人工耳蜗系统.     

一种带植入式数字信号处理器的新型人工耳蜗系统

提出了一种带植入式数字信号处理器的人工耳蜗系统. 该系统只需在无线通道中传输低码率的语音信号,不存在数据码率受限的问题,有利于人工耳蜗未来的发展. 通过优化语音处理算法和数字信号处理器硬件设计,植入式的处理器可以在3MHz的时钟频率下执行连续相间采样（CIS）算法,功耗仅为1.91mW. 根据理论分析得到的无线能量传输效率（40%) ,可以推算出由于处理器植入所增加的功耗是2.87mW,与现有的商用人工耳蜗系统整机功耗（几十毫瓦）相比微乎其微. 由于处理器的植入,新系统可以很容易扩展成全植入式人工耳蜗系统.     

TMS320C6711的硬件设计与应用

TMS320C6711是美国TI公司生产的一种高性能浮点数字信号处理器。本文介绍了TMS320C6711数字信号处理器的硬件设计与应用，包括电源系统的设计、上电加载方式、时钟的设计、通信接口的设计等等，并介绍了一个应用实例。     

一款低功耗SoC芯片的时钟管理策略

文章提出一种系统级和RTL级协同设计的时钟管理策略，显著地降低了时钟网络的动态功耗，弥补了现有工具只能在设计后期才能发挥作用的不足，达到降低整个SoC芯片功耗的目的；同时，分析该方案实现中可能存在的问题．并给出解决方案。     

一种新型高速低成本可重构FFT处理器结构

文中提出了一种基于FPGA的高速可重构FFT处理器结构.该结构采用精简控制算法[1]可针对从32点到1024点等不同点数数字信号进行FFT处理,并且在Xilinx公司Virtex2p系列FPGA上进行了综合及后仿真.结果表明该可重构结构相比Xilinx IP core而言资源占用减少16%~21%(slice),最高时钟频率提高了10%~30%,输入输出延时减少了56~116个时钟周期,运算效率明显提高,而功耗相当.可适用于低成本高速数字信号处理系统.     

一种手持嵌入式设备的系统级功耗管理方案

针对一种手持式设备,本文给出了一种在系统层次上降低功耗的软件功耗管理方案。文中简述了系统中Garfield处理器的基本特性,详细介绍了其功耗管理模块的结构和工作原理,在定义处理器工作模式和外围设备模块工作模式的基础上,重点讲述了系统功耗状态的定义,状态之间的转换过程和转换策略,同时对设备功耗管理策略及其实现方法作了详实的阐述。方案利用实时操作系统ASIXOS中的软件定时器功能实现所制定的策略,并通过在实际系统中测试,验证了方案的效果。     

无线传感网络中低功耗处理器的设计和优化

采用90nm工艺设计实现了应用于无线传感网络中的低功耗处理器. 为了减小功耗，采用了以下两种方法： (1）采用门控时钟技术来降低动态功耗； (2）采用多阈值电压单元库来减小漏电功耗. 通过比较给出了设计优化结果.     

一种自适应的动态功耗管理预测策略

动态功耗管理通过关闭空闲的系统部件来减小电子系统的功耗。如何提高预测的准确度是当前基于预测动态功耗管理（DPM）研究的主要问题。基于预测的DPM策略假设系统部件访问时间具有关联性,当前应用最为广泛的是指数滑动平均方法,但其应对突发事件的能力不强。本文基于指数滑动平均改进模型,对突发事件进行数学定义,提出一种自适应的DPM预测策略,在面对突发的长延时或短延时情况下,系统都能自适应调整,提高了预测的准确度,优于现有策略。     

Hierarchical power management of a system with autonomously power-managed components using reinforcement learning

This paper presents a hierarchical dynamic power management (DPM) framework based on reinforcement learning (RL) technique, which aims at power savings in a computer system with multiple I/O devices running a number of heterogeneous applications. The proposed framework interacts with the CPU scheduler to perform effective application-level scheduling, thereby enabling further power savings. Moreover, it considers non-stationary workloads and differentiates between the service request generation rates of various software application. The online adaptive DPM technique consists of two layers: component-level local power manager and system-level global power manager. The component-level PM policy is pre-specified and fixed whereas the system-level PM employs temporal difference learning on semi-Markov decision process as the model-free RL technique, and it is specifically optimized for a heterogeneous application pool. Experiments show that the proposed approach considerably enhances power savings while maintaining good performance levels. In comparison with other reference systems, the proposed RL-based DPM approach, further enhances power savings, performs well under various workloads, can simultaneously consider power and performance, and achieves wide and deep power-performance tradeoff curves. Experiments conducted with multiple service providers confirm that up to 63% maximum energy saving per service provider can be achieved.     

Performance analysis of an improved dynamic power management model in wireless sensor node

The energy consumption in the wireless sensor networks is a very critical issue which attracts immediate attention for the sake of the growing demand of the billion dollar market in future. The Dynamic Power Management (DPM) technique is a way of controlling and saving the energy usage in a sensor node. Previously, researchers have proposed lifetime improving stochastic models for wireless sensor networks and limited work has been done focusing on the wireless sensor node. This paper proposes an analyser based Semi-Markov model for DPM in the event-driven sensor node. The power consumption comparison with previously proposed models without this analyser shows the analyser significant contributes to lifetime improvement. The improved model is more power efficient, presents how the DPM model observes the input event arrival and power states of the sensor node components, and then dynamically manages the power consumption of the overall system. Further, to observe the effect of event arrival, missed events, waiting time, processor utilization on the power consumption and lifetime, the proposed DPM system with the single server queuing model is developed.     

A survey of design techniques for system-level dynamic powermanagement

Dynamic power management (DPM) is a design methodology for dynamically reconfiguring systems to provide the requested services and performance levels with a minimum number of active components or a minimum load on such components. DPM encompasses a set of techniques that achieves energy-efficient computation by selectively turning off (or reducing the performance of) system components when they are idle (or partially unexploited). In this paper, we survey several approaches to system-level dynamic power management. We first describe how systems employ power-manageable components and how the use of dynamic reconfiguration can impact the overall power consumption. We then analyze DPM implementation issues in electronic systems, and we survey recent initiatives in standardizing the hardware/software interface to enable software-controlled power management of hardware components     

针对电压可调处理器的低功耗设计策略

在便携式系统的低功耗设计中，动态电源管理（Dynamic Power Management，DPM）和动态电压调节（Dynamic Voltage Scaling，DVS）已经成为比较通用的技术，并且很多实验数据表明DVS省电性能比DPM更为优越。本文针对电压可调的处理器，在理论证明的基础上提出了一种能够跟踪工作负载需求变化，在保证给定任务组中所有任务性能的同时实现系统能耗最优化的电压调节策略EOVSP（Energy Optimal Voltage Scaling Policy）。实验结果也表明，该策略在满足系统性能要求的前提下具有比一般DPM策略更好的省电性能。     

PBALT动态电源管理策略

在嵌入式和便携式系统的低功耗设计中，动态电源管理（Dynamic Power Management，DPM）是一个非常重要的技术。DPM本质上是一种“在线”问题，因为PM（Power Management）策略必须在系统所有输入信息可用之前就能够对系统资源的使用情况做出正确的判断。本文在对自适应学习树（Adaptive Learning Tree，ALT）不足之处进行分析的基础上，提出了一种新颖的DPM策略——PBALT（Probability-Based ALT）。实验结果表明，PBALT具有很强的稳定性；而且在对空闲时段的预测准确性方面，PBALT比ALT具有更高的命中率。     

Dynamic Power Optimization Targeting User Delays in Interactive Systems

Power has become a major concern for mobile computing systems such as laptops and handhelds, on which a significant fraction of software usage is interactive instead of compute-intensive. For interactive systems, an analysis shows that more than 90 percent of system energy and time is spent waiting for user input. Such idle periods provide vast opportunities for dynamic power management (DPM) and voltage scaling (DVS) techniques to reduce system energy. In this work, we propose to utilize user interface information to predict user delays based on human-computer interaction history and theories from the field of psychology. We show that such a delay prediction can be combined with DPM/DVS for aggressive power optimization. We verify the effectiveness of our methodologies with usage traces collected on a personal digital assistant (PDA) and a system power model based on accurate measurements. Experiments show that using predicted user delays for DPM/DVS achieves an average of 21.9 percent system energy reduction with little sacrifice in user productivity or satisfaction     

A low-complexity port selection and power allocation scheme in distribution MIMO systems

Information theoretical results have shown that Distributed Antenna Systems (DAS) can obtain higher capacity than Co-located Antenna Systems (CAS). In this paper, we investigate a downlink port selection and power allocation scheme in Distributed Multiple-Input Multiple-Output (D-MIMO) systems, where Distributed Antenna (DA) ports randomly locate in the cell. The contribution of this paper can be summarized as two parts. Firstly, we analyze how antenna correlation affects power allocation in D-MIMO systems. Secondly, based on large scale fading and antenna correlation, a low-complexity port selection and power allocation scheme is proposed. In the proposed scheme, we take both large scale fading and antenna correlation into consideration. Moreover, User Equipment (UE) only needs to feedback the rank of transmit antenna correlation matrix, which will not increase system complexity too much. Simulation results verify the capacity improvement based on the proposed power allocation scheme.     

动态电压调整多处理器实时系统任务调度

动态电压调整DVS（Dynamic Voltage Scaling）是根据处理器电压（速度）降低之后，能量消耗平方级的减少这一原理提出的。文章通过DVS机制在多处理器实时系统中进行任务调度．通过对任务调度中的静态能量管理进行分析，在此基础上提出了一种新的基于DVS的适用于多处理器实时系统中的调度算法。这种新的调度算法是通过对贪婪法调度进行研究，发现其不足．并以此为基础进行改进。结合了动态电压调整的多处理器实时系统任务调度的能量消耗比普通的任务调度能量消耗有了很大的改善。     

Combined Fuzzy-based Rate Management and Selective Power Control for Multimedia CDMA Cellular Systems

Power control mechanisms are essential for CDMA wireless communication systems to enhance user capacity. In this paper, we propose a novel power control scheme which combines transmission rate management with power adjustments for multimedia CDMA cellular systems. In the proposed scheme, a fuzzy logic controller (FLC) is first used to dynamically infer a suitable transmission rate for each service. Then a selective power control (SPC) scheme is used to adjust the transmission power for each service in order to maintain an acceptable signal-to-interference ratio (SIR). Numerical results show that the proposed scheme outperforms the original SPC and the Lagrangian relaxation technique and power control (LRPC) methods in outage probability, average transmission rate, probability of unsuccessful transmission, and probability of changes in transmission rates.