可靠电压频率岛感知的异步片上网络能耗优化

针对采用2D-Torus拓扑结构且支持电压频率岛（VFI）的异步片上网络能耗优化问题,提出了具有可靠性的、基于电压频率岛的划分和分配及片上网络任务映射的能耗优化方法．该方法采用递进优化的方式,根据IP核的动态处理能耗,不同电压频率岛之间的转换能耗和可靠性带来的能耗开销定义了IP核在电压频率岛之间移动的阈值函数,并通过对阈值函数进行判断完成电压频率岛的划分和分配,应用基于三元相关性量子粒子群优化算法完成处理单元到资源节点的映射,在映射中考虑保证系统可靠性的通信开销,对异步片上网络系统的可靠性进行优化．实验结果表明,该算法可以在不过多消耗能耗的情况下显著的改善片上网络系统的可靠性,且可有效降低NOC系统的能耗.     

基于遗传算法的特定应用片上网络映射研究

片上网络是片上系统SoC通信问题的一种最有效解决方法,如何把知识产权核映射到网格之格件映射问题是NoC设计的关键问题之一。映射问题本质上是一种二次分配的NP难问题,遗传算法能够有效地求解问题的近似最优解。提出一种基于遗传的IP映射算法,实验结果表明,遗传算法能够在几分钟内求得最小能耗的映射。     

一种基于电压岛的NoC低能耗路由算法

针对基于电压频率岛的片上网络路由算法通信能耗高的问题,提出一种确定性路由算法.应用遗传算法综合考虑电压岛的电压和频率对能耗与延迟的影响,在满足时延约束的条件下得到能耗较低的确定性路由路径,降低通信能耗.通过对遗传算法罚函数的改进,减少通信热点.实验结果表明,与已有算法相比,该算法以少量的硬件开销为代价,可得到通信能耗和通信热点两方面的优化.     

基于电压岛的能量和可靠性感知NoC映射

面向支持电压岛的NoC平台,定义了可靠性约束下的能量感知NoC映射问题,提出一种基于禁忌搜索的优化方法.设计了一种新的能效变化率驱动的启发式算法,嵌套于NoC设计空间的搜索过程中,在IP核映射解的基础上实现各电压岛的电压映射.实验结果表明,本文算法可显著降低NoC能耗,并高效地确保NoC通信的可靠性要求.     

一种基于遗传算法的片上网络映射算法

片上网络NoC以其高可扩展性成为片上多核的互连解决方案。IP核到NoC结点的映射是片上网络设计的重要阶段。映射对芯片的性能和功耗有重要的影响。本文详细阐述了映射算法的研究现状,给出了映射算法的分类方法,并且分析各种方法的特点。最后,给出一种采用顺序表示的基于遗传算法的NoC映射算法。实验结果表明,该映射算法能够取得较好的准确性和较高的效率。     

异构多核协作系统的混沌离散粒子群NoC映射算法

针对异构多核片上网络(NoO的任务映射问题,根据IP核的选择以及IP核向NoC平台中位置映射的两个阶段的不同特点,分别提出能耗和延时的粗略估算模型和精确计算模型。为避免离散空间搜索解落入局部最优,设计了混沌扰动机制。提出了带混沌扰动机制的改进型离散粒子群优化算法,以搜索能耗和延时优化的多目标NoC映射方案,该算法比传统优化算法在能耗和延时上有显著的性能提高。     

保证QoS的片上网络低能耗映射与路由方法

为解决二维mesh片上网络的服务质量和低能耗问题，提出基于最优化搜索的拓扑映射与路由方法Q-LEMR．该方法以降低芯片通信能耗为目标，在保证系统延迟与带宽的服务质量的前提下，自动将给定应用的IP核映射到片上网络结构上，并为通信踪迹定制设计确定的、非死锁的最短路径路由；同时通过加速策略使映射和路由的计算在可接受的时间范围内完成．实验结果表明，Q—LEMR较现有工作平均降低通信能耗28．8％，并满足服务质量要求．     

面向测试优化的片上网络映射算法

针对复杂片上系统(SoC)芯片的片上网络(NoC）映射方案未考虑测试需求的问题,提出了一种面向测试优化的NoC映射算法,兼顾了可测性的提升和映射开销的最小化。该映射方案首先依据特定的测试结构,使用划分算法进行片上系统所有IP核的测试分组,其优化目标为测试时间最短;之后,再基于分组内IP核之间的通信量,应用遗传算法实现NoC映射,其优化目标是在测试优化的基础上实现映射开销最小。通过多个ITC'02测试基准电路进行的实验结果表明:应用该方案后,测试时间平均减少12.67%;与随机任务映射相比,映射代价平均减少24.5%。     

基于遗传算法的片上系统IP核映射方法

片上系统SoC是指在单个芯片上集成了专用处理器、通用处理器、DSP、共享内存块、专用内存块、I/O部件等多个IP核的复杂的系统。规则拓扑的Mesh网格具有布线工整等优点,利用Mesh网格可以很方便地实现复杂的片上系统SoC。知识产权核(Intellectual Property Cores,IP核)到Mesh格件的映射问题是SOC设计的关键问题之一,其本质上是一种二次分配问题的NP难问题,目前没有多项式时间的求优方法。而遗传算法能够有效地求解问题的近似最优解。提出一种基于遗传的映射算法能够在几分钟内求得最小通信能耗的映射。     

基于IP核的PSTN短消息终端SoC软硬件协同设计

介绍在基于微控制器IP核的PSTN短消息终端SoC设计当中,如何合理划分硬件和软件的功能;从对微控制器IP核的配置与扩展、片上外设在SFR总线上的映射、存储空间的划分与映射等三个方面,详细讲述SoC的软硬件协同设计。     

TSGA:新型的片上网络低功耗映射算法

针对如何将越来越复杂的应用任务有效地映射到片上网络处理单元上,达到以更少的能耗完成任务的目的,提出了一种遗传算法和禁忌搜索算法相融合的新型片上网路低功耗映射算法。该方法充分利用遗传算法强大的全局搜索能力,融合禁忌搜索的局部搜索能力和突出的翻山特性来弥补遗传算法的局部搜索能力弱和早熟的缺陷,取得了更好的片上网络低功耗效果。实验结果表明,在同样的实验平台和功耗模型下,禁忌搜索遗传算法相比于早期的遗传算法能耗降低显著,相比于后来改进的MGA、AGA算法也有能效优势。     

基于改进遗传算法的片上网络低功耗映射方法

针对规模庞大的应用如何在NoC平台上低功耗地运行,本文提出了一种基于改进遗传算法的片上网络低功耗映射方法。该方法利用任务节点的通信权重和映射平台的结构特征,对任务节点进行优先级划分并根据任务节点优先级及其连接关系获取较优初始映射解集。在此基础上,在遗传操作中加入轮盘转赌、最优邻居选择、进化逆转等操作,同时每次迭代中都以一定的概率选择初始解,防止算法停滞。实验结果表明,在相同任务模型和映射平台下,改进遗传算法对比于传统遗传算法和随机映射方法,都大幅度降低了功耗。     

Dynamic energy management for chip multi-processors under performance constraints

We introduce a novel algorithm for dynamic energy management (DEM) under performance constraints in chip multi-processors (CMPs). Using the novel concept of delayed instructions count, performance loss estimations are calculated at the end of each control period for each core. In addition, a Kalman filtering based approach is employed to predict workload in the next control period for which voltage-frequency pairs must be selected. This selection is done with a novel dynamic voltage and frequency scaling (DVFS) algorithm whose objective is to reduce energy consumption but without degrading performance beyond the user set threshold. Using our customized Sniper based CMP system simulation framework, we demonstrate the effectiveness of the proposed algorithm for a variety of benchmarks for 16 core and 64 core network-on-chip based CMP architectures. Simulation results show consistent energy savings across the board. We present our work as an investigation of the tradeoff between the achievable energy reduction via DVFS when predictions are done using the effective Kalman filter for different performance penalty thresholds.     

一种基于离散Hopfield神经网络的RTOS功耗优化方法

RTOS(Real-Time Operating System,实时操作系统)是SoC(System-on-a-Chip,系统芯片或片上系统)的一个重要组成部分,其功耗一般约占整个系统功耗30～40%的比例,而基于软/硬件划分的RTOS功耗优化方法(简称RTOS-Power划分)能够明显地减少SoC的功耗.因此,文中首先引入了RTOS-Power划分问题的一个新模型,这有助于理解RTOS-Power划分的本质.然后,提出了一种基于离散Hopfield神经网络的RTOS-Power划分方法,重新定义了神经网络的神经元表示、能量函数、运行方程和系数.最后,对该方法进行了仿真实验,并同遗传算法和蚂蚁算法进行了性能比较.实验结果表明:该文提出的方法能够以相对较小的代价(FPGA开销小于4K个可编程逻辑块)取得高达60%的功耗节省,同时,与纯软件实现的RTOS相比,系统性能也得到了相应的提高.     

Mapping multiple applications onto 3D NoC-based MPSoCs supporting wireless links

Three-dimensional integrated circuits (3D ICs) are suitable alternatives to traditional two-dimensional (2D) ICs by leveraging its advantage of better performance and packaging; therefore, they have been highly considered by researchers. On the other hand, emerging network-on-chip (NoC) based many-core chips provides great potential for running multiple applications simultaneously. However, using this approach leads to the increase of the interference between applications, resulting in lowering the performance of each application. Hence, mapping tasks belonging to various applications onto the nodes of an architecture is a very important issue. In this study, based on partitioning concept, a novel methodology for mapping of multiple applications at run-time onto an irregular wireless 3D NoC-based multiprocessor system-on-chip (MPSoC) platform in which more than one task can be supported by each processing element (PE) was presented. In the second algorithm (enhanced irregular-partitioning best neighbor), according to the number of applications running simultaneously, the partitioning of network will be dynamically changed to minimize the communication overhead and congestion on the NoC that leads to more efficient task mapping. The simulation results reveal that the second proposed algorithm (enhanced IPBN) in comparison with NPBN (non-partitioning best neighbor) algorithm and our first proposed algorithm (basic IPBN) enhances the performance by decreasing the total execution time, average hop count, average channel load and energy consumption.     

微电网经济运行的分布式二次电压–频率恢复控制

由于传统下垂控制的特点,微电网中分布式能源的输出电压和频率易受负荷变化的影响.为此,本文提出了分布式二次电压–频率恢复控制算法,在二次控制层实现电压–频率恢复与同步的同时,提高微电网系统运行的经济性,并减少由于运行时间尺度不一致造成的供需不匹配.此外,本文提出的控制算法能实现孤岛模式向并网模式转变的无缝切换,能有效应对通讯故障,在极端情况下系统仍能保持稳定.最后,本文对所提出的算法进行了稳定性证明,并利用仿真和实验验证该算法的有效性和可靠性.     

不规则IP模块到2维NoC结构的映射方法研究

提出了一种新的基于NoC(Network on Chip)的不规则IP模块映射方法.其基本思想是把较大的IP模块分解成几个小的IP虚模型,或把几个较小的IP模块组合成一个IP虚模型,使得每个IP虚模型能映射到NoC结构的一个资源节点上.通过计算曼哈顿距离和输入/输出度,可以确定每个通信节点中缓冲区的大小.根据计算的通信代价可以对初始映射结果进行调整,从而可以避免通信拥塞,降低系统的功耗.     

Energy-aware mixed partitioning scheduling in standby-sparing systems

Previous standby-sparing techniques assume that all tasks don't access to shared resources. In addition, primary tasks and backup tasks are allocated to the primary processor and spare processor respectively. Spare processor schedules tasks with maximum processor speed. Unlike previous techniques, we have studied the problem of minimizing energy consumption and preserving the original reliability for dynamic-priority real-time task set with shared resources in a standby-sparing system. We propose a novel energy-aware mixed partitioning scheduling algorithm (EAMPSA). Earliest deadline first/dynamic deadline modification (EDF/DDM) scheduling scheme is used to ensure that the shared resources can be accessed in a mutual exclusive manner. Uniformly speed is used to the primary processor and the spare processor. In addition, we use the mixed mapping partitioning of primary and backup tasks method to map tasks. A novel method of mapping task is proposed i.e. the tasks which need to access to shared resources are mapped into the primary processor and the tasks which have no resource requirements are mapped into the spare processor. Furthermore, DVS and DPM techniques are used for both primary and backup tasks to save energy. The experimental results show that the EAMPSA algorithm consumes average 55.43% less energy than that of the SSPT algorithm.