GPU平台上面向性能和功耗的分支优化

强大的计算能力使得GPGPU在通用计算领域得到了广泛的应用。然而,GPGPU的SIMT(Single Instruction Multiple Threads)工作方式,使其执行效率受到应用中不一致分支行为(Branch Divergence)的严重影响。虽然人们提出了线程交换方法来减小分支带来的性能损失,但这种方法往往会引入额外的访存操作,不仅在一定程度上减少了线程交换优化的性能收益,还增加了功耗。首先举例说明线程交换范围对程序性能和功耗的影响;然后提出了一种减少线程交换所引入的额外访存操作的方法。实验表明,对于Reduction程序,当交换范围为256时,在性能平均损失为4%的情况下功耗降低幅度最大为7%;而对于Bitonic程序,当交换范围为256和512时,在没有功耗开销的情况下,性能分别最大提升了6.4%和5.3%。     

面向Cassandra数据库的高效动态数据管理机制

Cassandra数据库是当前通用的数据库之一,同时也被Apache列为重点发展的顶级项目。针对Cassandra分布式数据库系统而言,大量的写请求会造成过多分散的SStable结构以及过高的数据冗余度,进而造成用户读取请求响应速度下降。该问题可以通过系统自动触发的局部数据合并机制或人为干预的整体数据合并机制来解决。然而,不合时机的系统自动局部合并过程会严重降低用户正在执行的读取操作的性能,而过长时间的人为整体数据合并过程又会长时间地占用系统资源,严重制约系统的整体性能。针对此问题,提出了一种面向Cassandra数据库的动态数据管理机制。首先,实时监测系统环境,将数据按照写入时间和大小进行分层分级管理,对合并的时机、参与合并的文件及合并过程分别制定相应的执行策略;其次,通过特定优化手段减少数据的合并时间,以降低合并过程对系统性能的影响。测试结果表明,该管理机制优化了Cassandra数据库的合并过程,提升了系统整体的读取响应速度。     

Weighted principal component analysis-based service selection method for multimedia services in cloud

Cloud computing has rendered its ever-increasing advantages in flexible service provisions, which attracts the attentions from large-scale enterprise applications to small-scale smart uses. For example, more and more multimedia services are moving towards cloud to better accommodate people’s daily uses on various smart devices that support cloud, some of which are similar or equivalent in their functionality (e.g., more than 1,000 video services that share similar “video-play” functionality are present in APP Store). In this situation, it is necessary to discriminate these functional-equivalent multimedia services, based on their Quality of Service (QoS) information. However, due to the abundant information of multimedia content, dozens of QoS criteria are often needed to evaluate a multimedia service, which places a heavy burden on users’ multimedia service selection. Besides, the QoS criteria of multimedia services are usually not independent, but correlated, which cannot be accommodated very well by the traditional selection methods, e.g., traditional simple weighting methods. In view of these challenges, we put forward a multimedia service selection method based on weighted Principal Component Analysis (PCA), i.e., Weighted PCA-based Multimedia Service Selection Method (W_PCA_MSSM). The advantage of our proposal is two-fold. First, weighted PCA could reduce the number of QoS criteria for evaluation, by which the service selection process is simplified. Second, PCA could eliminate the correlations between different QoS criteria, which may bring a more accurate service selection result. Finally, the feasibility of W_PCA_MSSM is validated, by a set of experiments deployed on real-world service quality set QWS Dataset.     

基于CNN的监控视频事件检测

复杂监控视频中事件检测是一个具有挑战性的难题, 而TRECVID-SED评测使用的数据集取自机场的实际监控视频,以高难度著称. 针对TRECVID-SED评测集, 提出了一种基于卷积神经网络(Convolutional neural network, CNN)级联网络和轨迹分析的监控视频事件检测综合方案. 在该方案中, 引入级联CNN网络在拥挤场景中准确地检测行人, 为跟踪行人奠定了基础; 采用CNN网络检测具有关键姿态的个体事件, 引入轨迹分析方法检测群体事件. 该方案在国际评测中取得了很好的评测排名: 在6个事件检测的评测中, 3个事件检测排名第一.     

An ACO-based online routing method for multiple order pickers with congestion consideration in warehouse

One of the challenging problems in order picking is how to deal with the congestion happens in warehouse with multiple pickers. In this paper, we consider an ant colony optimization (ACO)-based online routing method to find picking routes for multiple order pickers under nondeterministic picking time. Here, a default route is formed by ACO for each single picker. Then, we coordinate these routes to alleviate congestion by dedicated rules based on indoor positioning and information sharing technologies, during order pickers serve the picking task. Our results indicate that the proposed method can achieve a reduction in the order service time primarily by coping with the congestion. We conclude that the new method is particularly effective in multiple-block picker-to-parts warehouses.     

一种基于高阶特征表示的图像分类方法

传统高阶特征构建方法需对局部特征进行两两匹配,随着阶数的增加,从而导致组合爆炸问题。为此,提出一种高阶特征组合表示方法。将图像划分为多个网格,每个网格内的尺度不变特征转换组合成高阶特征组合。同一个网格内tf-idf值最大的特征作为主特征,其余特征作为子特征,将主特征与子特征之间的夹角作为特征空间信息。通过高阶特征组合的视觉距离和几何距离匹配高阶特征,并结合支持向量机进行图像分类实验,结果表明,该方法分类准确率提高了约4%,可有效避免组合爆炸问题。     

基于模糊神经网络优化扩展卡尔曼滤波的锂离子电池荷电状态估计

电池荷电状态(state of charge,SOC)的精确估计是判断电池是否过充或过放的重要依据,是电动汽车安全、可靠运行的重要保障.传统基于扩展卡尔曼滤波(extended Kalman filter,EKF)的SOC估计方法过度依赖于精确的电池模型,并且要求系统噪声必须服从高斯白噪声分布.为解决上述问题,基于模糊神经网络(fuzzy neural network,FNN)建立模型误差预测模型,并藉此修正扩展卡尔曼滤波测量噪声协方差,以实现当模型误差较小时对状态估计进行测量更新,而当模型误差较大时只进行过程更新.仿真和实验结果表明,该算法能有效消除由于模型误差和测量噪声统计特性不确定而引入的SOC估计误差,误差在1.2%以内,并且具有较好的收敛性和鲁棒性,适用于电动汽车的各种复杂工况,应用价值较高.     

基于国产安全操作系统的集中存储管控系统

主要介绍以国产安全操作系统为运行环境的集中存储管控系统的研究与设计,系统通过运用“沙箱”、多因素增强身份认证、数据集中加密存储、负载均衡等核心技术,实现对用户文档的安全加密、数据集中存储、终端安全管理、外设封控管理及日志全面审计功能,以达到针对特殊目标用户数据灵活、安全、高效的集中存储管控策略控制.     

Wideband turnstile junction coaxial waveguide orthomode transducer

A wideband turnstile junction coaxial waveguide orthomode transducer (OMT) is presented in this paper, featuring coaxial waveguide input and orthogonal rectangular waveguide outputs. It primarily comprises of a turnstile junction, bending stepped impedance transformers and power combiners. The symmetrical geometry helps achieve wide operating bandwidth and balanced output phases. The OMT covers the whole Ku band from 12 to 18 GHz, which aims at wideband dual‐polarized signal combination and separation within coaxial‐type multi‐band antenna systems. An experimental prototype is manufactured and the measured results confirm that the reflection coefficient is lower than ?15 dB within the whole band, and the port isolation is better than 35 dB. Turnstile junction coaxial waveguide OMTs can be adopted widely in circular/coaxial waveguide hybrid feeding networks for multi‐band satellite communication/remote sensing antenna systems.