高性能计算机系统中可视化负载信息的获取及性能分析工具:THPTii

由于并行应用程序的运行效率往往很低，如何帮助程序员提高性能成为高性能计算中的重要问题，本文介绍了一个基于MPI的性能评价工具，它可以在应用程序运行的同时是收集系统负载信息，跟踪程序流程，根据硬件资源情况对处理机进行分组，并将负载信息和程序流程同时以图形方式展示，程序员可以藉此对并行应用程序运行情况进行监测，分析算法执行过程和系统负载的关系，找出性能瓶颈，发掘应用程序的潜力，最终提高应用程序的性能。     

并行仿真多样本任务分发与调度工具的设计

并行离散事件仿真具有更高的运行效率,已在分析仿真领域得到了广泛的关注.分析仿真往往要对多组参数组合进行比较,要求仿真应用运行多次才能得到所需的结果数据.针对目前并行仿真应用进行多样本多次运行时需要进行大量手工配置、仿真运行效率低下这一问题,论文在对并行仿真应用多次连续运行控制技术进行深入研究的基础上,提出了一种多样本任务分发与调度框架,并设计了多样本任务分发与调度工具.该工具能够将样本运行信息自动部署到局域网内多个节点上,并调度各节点上的样本并行运行.应用表明工具减少了仿真试验人员仿真运行配置工作量,大大缩短了仿真任务运行所需时间.     

基于事件的异构平台并行程序性能可视化研究

为了便于用户快速、直观地了解到机群系统中并行应用程序的性能情况,将Linux计算机群与Windows控制显示平台相结合,提出了一种基于事件的异构平台并行程序性能可视化方法.该方法以MPI作为底层编程环境,在高层使用MPE技术,依据动态性能检测方式获取程序执行过程信息;设计C#语言及Jumpshot日志图形化分析集成工具实现并行程序性能可视化.实验结果表明,该方法可准确,直观地反映程序性能信息,有助于程序员简便、有效地对并行程序进行量化分析,对提高机群系统的可用性、改善程序性能及效率等方面具有较高的实用价值.     

QQ在Windows7下无法运行

Q 刚买的新笔记本,安装的是64位Windows7系统,安装了QQ但是不能运行,每次启动QQ都提示“应用程序无法启动,因为应用程序的并行配置不正确。有关详细信息,请参阅应用程序事件日志,或使用命令行运行sxstrace．exe工具。”请问这是怎么回事？     

并行计算应用程序开发（下）

本文上篇介绍了并行应用程序开发中的OpenMP、MPI以及网格计算,在下篇中将向您介绍真实案例研究和开发人员工具方面的知识。     

Visual C++实现多平台应用开发

当今应用程序开发人员面对着不断增多的平台,包括在Intel、MIPS和Digital的Alpha等处理器上运行的Windows NT以及Chicago和Macintosh操作系统等。本文介绍利用Visual C++系列开发工具,实现在这些平台上开发应用程序的实用技术。 Microsoft已经宣布了其用一套工具(包括94年Visual C++产品)开发16位和32位应用程序的策略。这个工具系列使开发支持多个平台间对象连接与嵌入(OLE2.0)的Windows和Win32的应用程序比较容易。实际上,使用Visual C++和Microsoft基础类(简称MFC),开发人员在多个平台上进行开发只需要学会一套工具和一套应用编程接口。     

并行离散事件仿真及其应用研究

并行离散事件仿真是一种非常有用的分析求解大规模复杂问题的工具,近年来成为住址界研究热点之一。本文首先指出并行离散事件仿真研究和应用中的不中足,在分析离散事件仿真机制和并行平台引入方式的基础上,结合实际应用现状阐述了并行离散事件仿真机制难以实现和应用的原因,然后针对这种不足提出了一种实现框架,并以通信系统仿真为例说明了所提框架的优越性。     

Android系统外部SDK安全漏洞检测研究

SDK是面向Android应用程序开发人员的工具集合,包括硬件平台基础信息、软件协议框架、操作系统等,其宗旨在于提高Android应用程序的开发效率。许多Android软件供应商提供的大多数Android App的开发普遍基于已有的SDK,在此基础上二次开发做出产品,如果所采用的SDK中存在安全风险或者漏洞,将导致所有基于此SDK开发的App都面临潜在攻击威胁,将对用户的隐私信息保护和Android系统的安全性产生严重的负面影响。本研究选择了35个使用较为广泛的非官方SDK,结合污点追踪、二进制插值方法,并使用FlowDroid和Droidbox软件工具分析了应用于外部SDK开发的应用程序。研究结果表明,在35个外部SDKS开发工具中,19个(54. 3%)存在SSL/TLS错误配置、不合理的敏感数据权限分配、HTTP的非必要调用、用户日志泄漏、开发人员考虑不周等漏洞和威胁,造成用户隐私数据面临较高的安全风险。     

高效使用GWT的研究与实现

GWT是开发Web应用程序的强大工具,越来越受到开发人员的青睐。该文分析了提高GWT使用效率的四个路径:巧妙使用CSS,扩展GWT,提高国际化和优化性能。同时,也给出相关实例。     

系统健康的体检医生

在Windows2000、WindowsXP操作系统中有一位系统运行状况的忠实记录者,从开机、运行到关机过程中发生的每一个事件都将被记录下来,它就是“事件查看器”。用户可以利用这个系统维护工具,收集有关硬件、软件、系统问题方面的信息,井监视系统安全事件,将系统和其他应用程序运行中的错误或警告事件记录下来,便于诊断和纠正系统发生的错误和问题。下面通过几个例子来讲解“事件查看器”的实际应用。     

并行网络蠕虫模拟中任务优化划分的研究

为提高并行网络蠕虫模拟的性能，需要对蠕虫模拟任务进行合理的划分．鉴于基于图划分工具的任务划分方法存在的不足，提出了并行网络蠕虫模拟任务的优化划分方法：以并行网络蠕虫模拟运行时间估计模型作为优化目标函数，采用改进的模拟退火算法实现对蠕虫模拟任务的划分．在PDNS上进行的Slammer蠕虫传播模拟实验表明，该优化划分方法较基于图划分工具的方法提高模拟性能20％以上．     

Estimating simulation metamodel parameters for unexpected shop floor real time events

In order to better understand assembly line system dynamic behavior and provide a basis for developing effective production controls, three unexpected real time events are studied, including sudden machine breakdown at a work station, parts supply shortage and high priority job order processing. Short term system performance is evaluated by dynamic response variables associated with assembly time and work in process (WIP) inventory. Simulation is used as the modeling tool, and the results are further described by mathematical metamodels for overall system behavior. The system transients can be adequately represented by first order exponential functions, and satisfactory results are also obtained for expressing simultaneous occurrence of dynamic events by combined metamodels using linear additivity. A procedure is proposed for the development of dynamic metamodels. For a given system, only a limited number of simulation runs should be made in advance to estimate the metamodel parameters. Using the resultant application program that only contains the metamodels, whenever an event occurs, without running simulation a user can instantaneously predict the consequence in a specified time period by an estimation to the number of assembly products to be finished late.     

分布式集群并行仿真平台中时间同步技术研究

基于集群的并行仿真对复杂大规模动态系统的研究以及探索其长远的应用提供了便利,近年来日益成为研究的热点。然而时间同步管理不但是关注并确保并行仿真正确执行的一种机制,而且更是影响并行分布仿真系统高效运行的关键因素之一。该文首先介绍了两类最基本的时间同步协议,并在此基础上分析了两类典型的乐观与保守时间同步机制,即时间卷回算法和周期时间桶算法,最后在深入讨论这两种算法局限性的基础上,提出并实现了一种周期时间卷回算法,实践证明该算法是一种适合分布式集群并行仿真平台的先进的时间同步算法。     

CPU–GPU Parallel Framework for Real‐Time Interactive Cutting of Adaptive Octree‐Based Deformable Objects

A software framework taking advantage of parallel processing capabilities of CPUs and GPUs is designed for the real‐time interactive cutting simulation of deformable objects. Deformable objects are modelled as voxels connected by links. The voxels are embedded in an octree mesh used for deformation. Cutting is performed by disconnecting links swept by the cutting tool and then adaptively refining octree elements near the cutting tool trajectory. A surface mesh used for visual display is reconstructed from disconnected links using the dual contour method. Spatial hashing of the octree mesh and topology‐aware interpolation of distance field are used for collision. Our framework uses a novel GPU implementation for inter‐object collision and object self collision, while tool‐object collision, cutting and deformation are assigned to CPU, using multiple threads whenever possible. A novel method that splits cutting operations into four independent tasks running in parallel is designed. Our framework also performs data transfers between CPU and GPU simultaneously with other tasks to reduce their impact on performances. Simulation tests show that when compared to three‐threaded CPU implementations, our GPU accelerated collision is 53–160% faster; and the overall simulation frame rate is 47–98% faster.     

改进中值滤波方法的图像预处理技术

图像实时处理系统日益发展,这无疑对FPGA的广泛应用提供了良好的平台。针对在某些领域传统的中值滤波算法无法快速有效的对采集到的图像进行处理,采用改进中值滤波利用FPGA运行速度快、内部程序并行运行等优点,设计出具有高实时性、高灵活性的图像预处理系统。通过中值滤波算法特点运用Verilog硬件描述语言进行代码编写,并在Quartus II、Modelsim进行实现仿真,最后与MATLAB中值滤波仿真图及多级中值滤波进行对比,得出利用FPGA处理改进中值滤波不但能够顺利对图像进行中值滤波,而且具有运算速度快、低能耗的特点。     

MPI并行程序设计的负载平衡实现方法

MPI是目前集群系统中最重要的并行编程工具,它采用消息传递的方式实现并行程序间通信。在MPI并行程序设计中实现负载平衡有着重要的意义,可以减少运行时间,提高MPI并行程序的性能。负载平衡又可分为静态负载平衡和动态负载平衡,对于静态负载平衡,提出了一种分配任务的算法,可有效地按照节点的计算能力,在节点间分配任务;对于动态负载平衡,提出了一种在MPI并行程序中实现的方法,可有效地根据节点的负载情况,在节点间迁移任务。     

基于Spark和PSO算法的军事物流配送路径优化问题研究

军事物流配送路径优化问题是研究如何在保证各个部队所需物资的前提下,各配送车辆总行驶路径最短的问题。利用粒子群优化(Particle Swarm Optimization, PSO)算法解决该类问题时,随着部队数量的增加,程序运行时间会显著增加。考虑到PSO算法迭代计算的特点,本文提出一种在Spark集群上并行运行PSO算法的解决方案。实验证明,利用Spark集群并行运行PSO算法能够大幅降低程序运行时间,提高解决军事物流配送路径优化问题的效率。     

异构环境下MPI程序Cache访问的单机模拟

Cache模拟工具可以在单机上模拟运行于异构环境下的并行程序的Cache访问。用户依照自己的需求指定Cache模型参数及替换算法,对每个进程中的某一段进行模拟,使并行程序中每个或每组子进程/线程分别对应一个Cache模型,从而同时得到每个或每组子进程/线程的Cache访问参数。使用单机Cache模拟环境降低了并行程序的Cache模拟对实际并行环境的依赖。同时,用户还可以很方便地在其基础上扩展并使用自行开发的替换算法或进程通信模块功能,适应了不同用户对并行程序Cache模拟工具的需要。     

The “Smart” simulation environment – A tool-set to develop new cache coherency protocols

“Smart” is a new system-level simulation environment that was developed in order to evaluate and improve algorithms for distributed and parallel systems. In this paper we focus our discussion on the developing of new cache coherency mechanisms that were optimized to handle system-level effects such as process switching and task migration. The developing of new cache coherency protocols is a good example to demonstrate many of the important features of Smart, since system-level events have a major influence on the effectiveness of different cache coherency policies and the overall performance of multicache systems. The Smart simulation environment was built as a separate layer that extends existing multi-processing simulators, so we could take the advantage of using mature and reliable simulation engines. Smart also provides a friendly graphical user interface (GUI) that allows: (1) control of different system parameters and mechanisms such as the cache coherency protocol type, cache organization, scheduling policies of processes and threads, etc., (2) simulation of the execution of shared-memory parallel architecture and measuring different systems' performance parameters and (3) use as a powerful visual based debugging tool. Although this paper presents a version of Smart which is dedicated for shared-bus architectures, other libraries of the tool can simulate different parallel and distributed architectures as well.     

A simulator for adaptive parallel applications

Dynamically allocating computing nodes to parallel applications is a promising technique for improving the utilization of cluster resources. Detailed simulations can help identify allocation strategies and problem decomposition parameters that increase the efficiency of parallel applications. We describe a simulation framework supporting dynamic node allocation which, given a simple cluster model, predicts the running time of parallel applications taking CPU and network sharing into account. Simulations can be carried out without needing to modify the application code. Thanks to partial direct execution, simulation times and memory requirements are reduced. In partial direct execution simulations, the application's parallel behavior is retrieved via direct execution, and the duration of individual operations is obtained from a performance prediction model or from prior measurements. Simulations may then vary cluster model parameters, operation durations and problem decomposition parameters to analyze their impact on the application performance and identify the limiting factors. We implemented the proposed techniques by adding direct execution simulation capabilities to the Dynamic Parallel Schedules parallelization framework. We introduce the concept of dynamic efficiency to express the resource utilization efficiency as a function of time. We verify the accuracy of our simulator by comparing the effective running time, respectively the dynamic efficiency, of parallel program executions with the running time, respectively the dynamic efficiency, predicted by the simulator under different parallelization and dynamic node allocation strategies.