An HLA/RTI Architecture Based on Multi-thread Processing

In order to improve the real-time performance of the real-time HLA(high level architecture) in the application of massive data communication volume,multi-thread processing was adopted,thread pool structure was introduced into the system,different threads to handle corresponding message queues was utilized to respond different message requests.Furthermore,an allocation strategy of semi-complete deprivation of priority was adopted,which reduces thread switching cost and processing burden in the system,provided that the message requests with high priority can be responded in time,thus improves the system's overall performance.The design and experiment results indicate that the method proposed in this paper can improve the real-time performance of HLA in distributed system applications greatly.

Dynamically Translating Binary Code for Multi-Threaded Programs Using Shared Code Cache

mc211vm is a process-level ARM-to-x86 binary translator developed in our lab in the past several years. Currently, it is able to emulate singlethreaded programs. We extend mc211vm to emulate multi-threaded programs. Our main task is to reconstruct its architecture for multi-threaded programs. Register mapping, code cache management, and address mapping in mc2llvm have all been modified. In addition, to further speed up the emulation, we collect hot paths, aggressively optimize and generate code for them at run time. Additional threads are used to alleviate the overhead. Thus, when the same hot path is walked through again, the corresponding optimized native code will be executed instead. In our experiments, our system is 8.8X faster than QEMU （quick emulator） on average when emulating the specified benchmarks with 8 guest threads.

On Multi-Thread Crawler Optimization for Scalable Text Searching

Web crawlers are an important part of modern search engines.With the development of the times,data has exploded and humans have entered a“big data era”.For example,Wikipedia carries the knowledge from all over the world,records the realtime news that occurs every day,and provides users with a good database of data,but because of the large amount of data,it puts a lot of pressure on users to search.At present,single-threaded crawling data can no longer meet the requirements of text crawling.In order to improve the performance and program versatility of single-threaded crawlers,a high-speed multi-threaded web crawler is designed to crawl the network hyper-scale text database.Multi-threaded crawling uses multiple threads to process web pages in parallel,combining breadth-first and depth-first algorithms to control web crawling.The practice project is based on the Python language to achieve multi-threaded optimization network hyper-large-scale text database-Wikipedia book crawling method,the project is inspired by the article on the Wikipedia article in the Big Data Digest public number.

Research and Review on the Java Multi-thread Programming and Its Further Development Tendency

In this paper, we conduct research on the Java multi-thread programming and its further development tendency. Multithreading mechanisms can run several programs at the same time, make the program run effi ciency becomes higher that also can overcome the problem of basic traditional programming language design while its design is the key to the realization of the synchronous thread. Multithreading is a mechanism that allows concurrent execution of multiple instruction stream in the program, each instruction stream is called a thread, independent from each other between each other. Thread is also known as a lightweight process, it have independent execution and process control. Our research starts from the analysis of the corresponding mechanism to enhance the performance that is innovative and meaningful.

Using multi-threads to hide deduplication I/O latency with low synchronization overhead

Data deduplication,as a compression method,has been widely used in most backup systems to improve bandwidth and space efficiency.As data exploded to be backed up,two main challenges in data deduplication are the CPU-intensive chunking and hashing works and the I/O intensive disk-index access latency.However,CPU-intensive works have been vastly parallelized and speeded up by multi-core and many-core processors;the I/O latency is likely becoming the bottleneck in data deduplication.To alleviate the challenge of I/O latency in multi-core systems,multi-threaded deduplication (Multi-Dedup) architecture was proposed.The main idea of Multi-Dedup was using parallel deduplication threads to hide the I/O latency.A prefix based concurrent index was designed to maintain the internal consistency of the deduplication index with low synchronization overhead.On the other hand,a collisionless cache array was also designed to preserve locality and similarity within the parallel threads.In various real-world datasets experiments,Multi-Dedup achieves 3-5 times performance improvements incorporating with locality-based ChunkStash and local-similarity based SiLo methods.In addition,Multi-Dedup has dramatically decreased the synchronization overhead and achieves 1.5-2 times performance improvements comparing to traditional lock-based synchronization methods.

Multi-threaded Fast Distance Field Computation Using Spatial Partition

This article describes three algorithms for distance field generation on triangulated model: brute force algorithm, single-threaded algorithm based on spatial partition and multi-threaded algorithm based on spatial partition. Spatial partition algorithm use equidistant network divide the bounding box into equal-sized cubes, calculates the maximum and minimum distances between the sample point and each of the small cubes,taking the minimum value from the maximum distance as the minimum distance from the sample point to the model named d1, comparing d1 with the distance from sample point to every little cube's minimum distance d2, if d1 <d2, the sample point's distance to all triangles inside this cube are greater than d1, skip this cube, otherwise, calculated the distance from the point to all the triangles intersect with the cube, then alternative d1 with the minimum value, circulate all small cubes intersect with the model. Comparing the calculation results, it can be seen that the algorithm about the multi-threaded distance field relative to the other two algorithms in computational speed is greatly improved especially for complex models.

基于国产ARM架构CPU的导航卫星精密定轨解算效率优化方法

以国产飞腾CPU为例,讨论在国产ARM架构CPU基础上的导航卫星精密定轨解算效率优化方法。基于导航卫星精密定轨解算流程中钟差约化和法方程求逆耗时较多,分别利用多线程和OpenBlas对上述2个过程进行优化。结果表明,优化后解算效率大幅提升。钟差约化方面,采用100个测站32颗导航卫星进行解算时,原始单历元平均耗时1.105 s,优化后为0.188 s;法方程求逆方面,原始求逆平均耗时2 264 s,优化后仅需78 s。

一种多线程概念约简算法

针对现有概念约简算法计算过程较为繁琐且执行效率低的问题,提出了一种多线程概念约简算法MTCR。MTCR以提高计算概念约简的效率为首要目标,在多核环境下利用多线程技术并行计算概念约简。首先,MTCR算法使用两个线程分别计算单个对象的对象代表概念集和单个属性的属性代表概念集;然后,将形式背景中的对象(属性)依次放入p个队列,并为每个队列创建线程;最后,通过多线程方式并行计算任意对象的对象代表概念集和任意属性的属性代表概念集,以及两类代表概念集的交集,进而构建代表概念矩阵,据此计算出所有概念约简。在MTCR算法中,使用多线程的每个阶段的数据相对独立,使得多线程之间不需要频繁的同步操作,从而减少了线程之间的竞争和等待。这样可充分有效地利用计算资源,大大提升算法的性能。UCI数据集和随机数据集上的实验表明:MTCR算法可以准确得到概念约简结果,在使用单线程情况下执行速度与串行概念约简算法SCR相近;当线程数不超过8时,线程数每增加1倍,MTCR算法执行速度可提高30%以上。

基于FFmpeg多线程编码的智能交通监控系统设计

针对智能交通管理设备本身缺乏安全监管,传统视频监控延迟高、画质低、稳定性差的问题,提出一种基于FFmpeg的多线程编码视频流传输方案。通过FFmpeg调用h264_nvenc编码器,实现宏块行级的GPU多线程加速,降低编码延迟。使用Visual Studio 2019和QT15.5开发基于FFmpeg的音视频处理软件,对多路视频流进行封装、推流,并搭建Nginx流媒体服务器进行分发。通过实验表明,该系统整体的传输延迟低于1 s,且拥有良好的率失真特性,监控画面清晰、稳定性高,实现了对交通管理设备实时稳定的安全监控。

高速旋转设备智能感知系统搭建及数据上传方法研究

针对高速旋转设备的特点搭建了物理智能感知系统,重点对系统所产生的传感器数据如何高效上传进行了深入研究。高速旋转设备物理感知系统具有采集信号多、采集方式多及数据量大等特点,提出3种上传算法:多线程多行算法可工作于普通单片机系统,上传速率达到0.06~0.07 MB/s,可满足系统工作于趋势值自动采集方式下的上传要求;单进程分页算法要求上传硬件系统为工业级单片机或嵌入式系统,上传速度可达0.7~0.8 MB/s,且稳定,可以满足系统工作于手动采集方式下数据实时上传的要求;多进程并行算法的硬件要求为多运算器设备,上传速率取决于运算器数量,10运算器主机上传速率稳定在约3.4 MB/s,可满足多设备系统任何数据采集方式下数据实时上传的要求。文中所做分析可为旋转机械行业数字化发展提供切实可行的方案。

Multi-threaded code generation from Signal program to OpenMP

The use of multi-core processors will become a trend in safety critical systems. For safe execution of multi- threaded code, automatic code generation from formal spec- ification is a desirable method. Signal, a synchronous lan- guage dedicated for the functional description of safety crit- ical systems, provides soundness semantics for determinis- tic concurrency. Although sequential code generation of Sig- nal has been implemented in Polychrony compiler, deter- ministic multi-threaded code generation strategy is still far from mature. Moreover, existing code generation methods use certain multi-thread library, which limits the cross plat- form executions. OpenMP is an application program inter- face （API） standard for parallel programming, supported by several mainstream compilers from different platforms. This paper presents a methodology translating Signal program to OpenMP-based multi-threaded C code. First, the intermedi- ate representation of the core syntax of Signal using syn- chronous guarded actions is defined. Then, according to the compositional semantics of Signal equations, the Signal pro- gram is synthesized to dependency graph （DG）. After par- allel tasks are extracted from dependency graph, the Signal program can be finally translated into OpenMP-based C code which can be executed on multiple platforms.

轻量化智慧乡村移动用图系统的设计与实现

为推进慧智慧乡村信息化、智能化建设进程,解决移动用图系统商业软件价格昂贵、系统庞大、硬件要求高等问题,设计一个轻量化的智慧乡村移动用图系统。基于Android开发平台,结合开源GDAL和移动GIS技术,研究移动GIS、影像金字塔的多线程快速加载、多线程矢量分层按区动态加载、线与节点双属性等关键技术,建设轻量化的智慧乡村移动用图系统。以智慧园区数据为例,研发了轻量化、安装方便、运行快捷、操作简单、展示直观的移动用图系统,取得了较好的应用效果。

多线程多核服务器功耗模型及性能监控

针对现有服务器的CPU功耗准确性不足和多线程处理功耗负载不平衡问题,本文提出了一种多线程和多核服务器CPU功耗模型。该模型采用前后端分离的整体架构思想,根据服务器功耗模型实时获取CPU的线程数、频率及利用率。通过日志文件进行反馈多线程和多核功耗模型,达到最佳服务器负载平衡。仿真测试的结果表明,改进的服务器功耗模型在CPU利用率方面比传统服务器提高了6%,内存以及I/O通信方面也有明显改善,为多线程和多核服务器提供了一种新的功耗模型思路。

网络版过程数据采集与分析软件的研究和应用

为提高变频器产品调试和故障监控分析能力,提出了网络版过程数据采集与分析软件设计方案,论述了软件系统的组成以及实现方式,提出了多线程、虚拟内存、绘图类库、高速光纤同步等技术手段用以解决系统运行技术难题。此软件系统经过现场应用表明,系统运行稳定,具有低成本、多通道传输、低采样周期、高数据精度、图形功能丰富、可扩展性强等特点。

一种船舶历史活动热力图实时生成策略

在船舶信息大数据系统中,针对在客户端向服务器请求大批量历史数据并实时绘制热力图时,会出现耗时较长、热力图效果失真以及地图软件漫游时跟随性差或卡顿等问题,提出一种改进的船舶历史活动热力图实时生成策略。该策略在基于像素聚类思想的热力图生成方法基础上,采用基于非线性变换的图像增强算法和像素补点方法,对传统方法绘制的热力图所存在的显示失真问题进行校正和优化,并在此基础上,提出动态加载与绘制策略和多线程实时成图策略,来生成船舶历史活动的热力图。试验表明,所提出策略在热力图绘制的效率、成图效果以及地图软件的交互体验上都得到了提升。

基于改进多智能体PPO的多无人机协同探索方法

采用多无人机对未知环境进行探索,可以提高探索任务的鲁棒性和执行效率。不同于启发式方法,多智能体深度强化学习方法可以省去人为制定规则的过程,将无人机作为智能体,通过与环境互动,自主习得更加有效的“规则”。搭建了多无人机多线程仿真环境,为多无人机协同训练提供环境,提出一种适应多线程环境的结合长短时循环神经网络(记忆)的共享多智能体近端策略优化(LSTM-MAPPO)方法,并在合作型LSTM-MAPPO方法的基础上增加了全局边界信息以增大每幕探索面积。数值实验结果表明:与现有的多智能体深度确定性策略梯度(MADDPG)方法相比,所提方法在训练后期连续动作下也能稳定收敛;相较于现有的LSTM-MAPPO方法,其最终获得的奖励稳定高于5000;对3种不同的仿真地图,训练完的网络在测试时能实现70%以上的稳定探索面积。

基于气象大数据云平台的监控告警应用研究

由于已有气象数据监控系统的业务流程不适用最新的业务发展,结合我省实际气象信息化业务需求,研究和分析气象数据传输的业务流程,采用Model+View+Controller(MVC)开发模式,使用作业调度Quartz、多线程Smart Thread Pool等技术框架,基于气象大数据云平台升级现有气象数据监控告警系统,实现我省常规气象数据的实时监控告警。目前,该系统已投入业务运行,各功能模块运行稳定,可高效地帮助一线值班人员发现数据异常问题,提高了我省气象数据的监控告警能力。

数据库间数据同步批量入库工具分析

针对在数据库之间进行数据同步时存在的问题,提出数据库间数据同步批量入库工具。对于多线程的算法,创建至少两个用于读取事务日志的子线程,并行读取源端数据库事务日志的不同内容块;每个子线程读取的内容块并行生成SQL执行语句、并行创建SQL文件,并将SQL文件的文件名写入待执行文件序列。对于单线程算法,通过解析源端数据库事务日志实现同步的技术背景下,批量执行SQL命令,提高数据同步效率。工具使得解析效率成倍提升,从而大幅提高数据同步效率。

勘察报告表格和文本信息提取算法研究

当前,勘察报告作为重要的工程设计依据,其中有大量表格和文本信息未被有效识别利用,为进一步打通专业软件研发的数据壁垒,有效识别和提取勘察报告信息迫在眉睫。针对该现状,本文设计Word表格及文本信息提取算法,并提出信息提取、显示和利用的一整套解决方案。基于文件读写库遍历Word表格,计算每个单元格的行列合并数,进而实现Word表格精准识别至Excel;基于文档自动化技术,记录Word表格范围,反向搜索获取表格标题。基于栈数据结构和匹配算法,遍历Word段落进行大纲匹配和范围计算,实现Word文本大纲信息识别;通过程序后台模拟复制粘贴操作将数据呈现在软件界面上。引入多线程机制,防止勘察报告信息提取操作阻塞主线程,引入并行分析机制,加速文本分析效率,进而提升软件的综合用户体验。以某一实际工程勘察报告为案例进行分析,验证该算法的适用性和准确性。

基于多线程通信的煤矿安全实时监控系统的设计

传统煤矿安全实时监控系统采用人工监控方法,导致系统的监控面小。为解决该问题,提出基于多线程通信的煤矿安全实时监控系统的设计。硬件设计,先设计PLC控制器,然后设计温湿度传感器,最后设计瓦斯浓度传感器。软件设计,先建立数据库,然后采集基于多线程通信数据,在此基础上设计监测系统的显示界面。对该系统进行性能测试,结果表明,该系统的监控面较广,能更准确反映矿山的安全状况,监控效果理想,满足实际应用需求。