多计算机的自动插桩与监测系统

在设计大规模的并行应用程序时,如何使多处理器的利用率达到最优,这对程序设计人员来讲是一个很大的挑战。一般说来,由于应用程序在运行时性能上的缺陷,计算资源得不到充分利用。因此,迫切需要对应用程序进行“性能调试”,即在正确性的基础上,通过揭示这些缺陷,对程序进行细调而提高程序性能。在这篇文章里,介绍了一个软件工具包—自动插桩和监测系统(theAutomatedInstrumentationandMonitoringSystem),它集程序插桩、运行监测和性能分析为一体,支持在多处理器上对并行应用程序进行性能评估。文章首先论述了一些建立性能调试工具的基本问题;然后,详细描述AIMS系统的体系结构以及在利用AIMS工具包进行性能调试工具的开发中的经验;最后,使用两个例子详细地描述使用AIMS系统进行性能调试的过程。     

嵌入式远程调试工具的研究与实现

在嵌入式软件开发中,调试是一个重要的环节,调试工具是衡量软件开发环境优劣的重要因素.本文对插桩方式的嵌入式远程调试工具进行了分析与研究,采用GNU gdb远程串口通信协议,通过软件接管目标系统的全部异常实现对目标程序的调试与跟踪,实现读/写内存与寄存器、设置断点、单步执行和继续执行功能,并应用于基于ARM的RTEMS嵌入式实时操作系统与应用程序的调试中.     

现代应用软件的测试策略与工具*

现代应用软件有许多新的特性．这样就对软件测试提出了新的要求，如要求测试工作更有效、进行面向用户的测试等．这些要求是传统的测试策略所不能解决的．本文提出了一种基于应用操作覆盖的测试方法来解决这些问题．这种方法的基本分析工具是导航图和事件记录序列．本文最后还给出了相应的自动测试工具．     

多集群并行作业的性能监测及分析

介绍一种多集群计算模式,在分析了多集群系统结构灵活、具有可重组性等特点的基础上,研究适用于该模式的并行作业性能监测分析方法与技术,设计和实现了一个并行作业性能监测分析工具。它采用动态性能分析方法,遵循分布式软件设计架构,具有高内聚、低耦合的模块组织结构,运行验证表明其能够在多集群计算模式下有效工作。     

基于动态插桩的程序分析工具的性能改进

基于动态插桩的工具被广泛应用于程序分析中, 但该类工具都面临着严重的性能问题。这类工具的性能开销主要由两部分组成, 即插桩引擎的开销和用户定义的分析程序的开销。为降低用户定义的分析工具的开销, 首先分析了基于动态插桩的工具的性能开销的组成, 并通过实验分析了造成性能开销的几点原因及其对工具的性能影响; 根据分析结论提出了使用离线分析方式来优化工具性能, 最后通过并行数据收集来进一步提升工具性能。使用该方法能减少分析程序5%～15%的CPU占用时间。     

图灵机的行为学习*

图灵机计算时读写头在带子上的活动,包括移动及改写字符，称为圈灵机的行为．本文证明，图灵机的行为是可学习的．即存在一个学习过程，它能根据一个图灵机的行为序列，学到另一个也能产生同样行为序列的图灵机．     

基于事件分析的并行调试与监测分析技术

该文在对并行调试技术进行深入分析的基础上,重点研究了基于事件分析的并行调试与监测分析技术,并对其设计与实现方法进行了详细探讨。     

嵌入式软件性能分析方法研究与工具设计

通过对当前业界常见软件性能分析方法和常用性能分析工具技术特点的分析,根据嵌入式系统交叉开发方法的特点,以GNU性能分析工具gprof为切入点,针对其在性能数据采集和处理方面的不足,设计并实现一个面向嵌入式领域交叉开发环境的嵌入式性能分析工具Cross-Profiler。该工具能够针对以GCC作为交叉编译器,运行在嵌入式交叉环境下的应用软件进行性能分析,统计软件中各函数的执行时间、被调用次数、调用关系链以及执行过程中的函数堆栈开销等性能信息,从而有效帮助定位嵌入式软件的执行热点与性能瓶颈,为改善软件性能提供依据。同时,对Cross-Profiler的处理结果进行了可视化的输出设计,增强了易用性、可移植性和扩展性。     

MIs系统的程序生成方法*

随着计算机技术的迅猛发展，MIs系统被广泛地应用于各行各业．本文提出一种程序生成技术，旨在提高MIs系统的开发效率和开发质量．本方法是基于构件库设计思想，首先设计出各种构件类脚本描述，用此可自动生成各种程序模块．用这种方法和技术，已成功开发出多个MIS系统，通常只需在2个月内就可完成大型信息系统的设计和生成工作．     

市场分析的一种框架*

本文提出并实现了一种利用市场信息进行市场分析的框架，并认为市场分析是一种提高市场行为决策质量的信息加工过程．在此基础上讨论了市场分析框架的组成结构．并且对信息加工中的主要问题如趋势分析、定性因果分析等进行了初步研究．     

Supporting Scalable Performance Monitoring and Analysis of Parallel Programs

Tools for performance monitoring and analysis become indispensable parts of programming environments for parallel computers. As the number of processors increases, the conventional techniques for monitoring the performance of parallel programs will produce large amounts of data in the form of event trace files. On the other hand, this wealth of information is a problem for the programmer who is forced to navigate through it, and for the tools that must store and process it. What makes this situation worse is that most of the time, a large amount of the data are irrelevant to understanding the performance of an application. In this paper, we present a new approach for collecting performance data. By tracing all the events but storing only the statistics of the performance, our approach can provide accurate and useful performance information yet require far less data to be stored. In addition, this approach also supports real-time performance monitoring.     

Dynamic Instrumentation, Performance Monitoring and Analysis of Grid Scientific Workflows

While existing work concentrates on developing QoS models of business workflows and Web services, few tools have been developed to support the monitoring and performance analysis of scientific workflows in Grids. This paper describes novel Grid services for dynamic instrumentation of Grid-based applications, performance monitoring and analysis of Grid scientific workflows. We describe a Grid dynamic instrumentation service that provides a widely accessible interface for other services and users to conduct the dynamic instrumentation of Grid applications during the runtime. We introduce a Grid performance analysis service for Grid scientific workflows. The analysis service utilizes various types of data including workflow graphs, monitoring data of resources, execution status of activities, and performance measurements obtained from the dynamic instrumentation of invoked applications, and provides a rich set of functionalities and features to support the online monitoring and performance analysis of scientific workflows. Workflows and their relevant information including performance metrics are stored and utilized for comparing the performance of constructs of different workflows and for supporting multi-workflow analysis. The work described in this paper is supported in part by the Austrian Science Fund as part of the Aurora Project under contract SFBF1104 and by the European Union through the IST-2002-511385 project K-WfGrid.     

一个基于硬件计数器的程序性能测试与分析工具

在Intel P6系列处理器与Microsoft Windows NT平台上开发了一个工具软件PTracker,它利用处理器中的硬件性能计数器来获取程序性能数据,并结合机器体系结构参数对数据进行分析。它无需用户编程,与应用程序所使用的编程语言无关,使用很方便。它不仅能够通过性能计数器获得精确的性能参数,而且还能通过对测试得到的性能数据的分析,揭示程序高层次的性能特征,对程序性能评价与优化具有一定的指导作用。本文介绍了PTracker的技术背景、设计与系统实现,并给出了一个应用实例。     

利用Itanium2的PMU部件开发程序性能分析工具

Itanium2处理器以寄存器组的形式提供的性能监视单元实现了在程序运行过程中捕捉微结构事件的功能。文中介绍了以Linux为Itanium2的性能监视单元提供的接口perfmon为基础的开发相对高端的性能分析工具的方法,以实现对这些由性能监视硬件提供的数据进行综合处理利用。     

A Performance Analysis Tool for PVM Parallel Programs

In this paper,we introduce the design and implementation of ParaVT,which is a visual performance analysis and parallel debugging tool.In ParaVT,we propose an automated instrumentation mechanism.Based on this mechanism,ParaVT automatically analyzes the performance bottleneck of parallel applications and provides a visual user interface to monitor and analyze the performance of parallel programs.In addition,it also supports certain extensions.     

基于pfmon的性能测试与分析工具Codemon

通过对Linux/IA64平台上性能数据监测工具pfmon各类硬件计数器功能的分析,提出一种基于停顿时钟周期数测试存储延迟分布的监测模型,在此基础上设计和实现了程序自动测试与分析工具Codemon。应用该工具测试二维非线性扩散方程BNLAG2D求解程序模型的源代码,给出程序的性能评价和优化重点。该程序优化后性能提高了15％。     

DGMonitor: A Performance Monitoring Tool for Sandbox-Based Desktop Grid Platforms

Accurate, continuous resource monitoring and profiling are critical for enabling performance tuning and scheduling optimization. In desktop grid systems that employ sandboxing, these issues are challenging because (1) subjobs inside sandboxes are executed in a virtual computing environment and (2) the state of this virtual environment within the sandboxes is reset to an initial empty state after a subjob completion.DGMonitor is a monitoring tool which builds a global, accurate, and continuous view of real resource utilization for desktop grids with sandboxing. Our monitoring tool measures performance unobtrusively and reliably, uses a simple performance data model, and is easy to use. Our measurements demonstrate that DGMonitor can scale to large desktop grids (up to 12000 PCs) with low monitoring overhead in terms of resource consumption (less than 0.1% per machine).Though we originally developed DGMonitor with the Entropia DCGrid platform, our tool is easily portable and integrated into other desktop grid systems. In all of these systems, DGMonitor data can support existing and novel information services, particularly for performance tuning and scheduling. In this paper, the high scalability and monitoring power of DGMonitor are demonstrated with the Entropia DCGrid platform and the BOINC platform respectively.