基于PageRank的计算机性能评价方法

现有选择性计算机性能评价方法主要使用基准程序评价方法,基准程序中各子程序的输出往往因为单位不同而无法进行进一步数据处理,同时基准程序评价方法广泛采用的权重和评分方法缺乏理论依据。针对该问题,提出基于佩奇排名(PageRank)的计算机性能评价方法,采用比较数据序列间相似性的方法产生邻接矩阵从而为各项评估功能计算PageRank得分。实验结果表明,该方法能客观反映目标计算机系统的性能。     

计算机性能的PageRank评价方法

随着时代经济的快速发展以及科学技术的日新月异,计算机技术被广泛的应用于各行各业的发展中,对国民经济的巩固发展有着实质性的积极促进作用。就目前而言,计算机性能的评价方法主要是对基准程序评价方法的采用,但是由于基准程序在输出的同时其数据的处理有着实质性的难度,缺乏一定的理论依据。而基于计算机性能的PageRan评价方法在某种程度上对目标计算机系统的性能客观的加以反映。本文首先对计算机性能的评价作了一定概述,进而阐述了基准程序评价方法和PageRan算法,最后着重探讨计算机性能的PageRan评价方法,并对实验作了一定的分析。     

一种新型圆弧插补算法

在现代计算机数控(CNC)系统中,插补算法大都采用计算机的程序软件来实现.目前应用最普遍的插补算法有基准脉冲法和数据采样法.     

用基准程序法对几种16/32位微处理机的性能评价

一、引言 国内引进不少微型机系统,迫切需要进行性能评价。 基准程序(Benchmark)法是一种反映机器综合性能的方法,它比指令混合法更接近于实际运行情况,能反映包括硬件、软件和固件在内的系统的综合性能与结构特点。基准程序一般采用实测,但也可采用模拟的方法或者人工计算得到基准程序所需空间和执行时间。 基准程序可以用汇编语言编写,也可以用高级语言编写。汇编语言写的基准程序对不同的机     

Spec CPU2000基准程序运行路径分析

Spec CPU2000的基准程序被广泛地应用于处理器的设计性能评估。在微处理器RTL级系统评估过程中,需要运行一些性能评估代码来完成系统的评估,因为运行整个基准程序的代价很大,所以都用运行部分代码的方式来获得性能情况。该文利用基准程序的频繁函数提取出微程序的方法,用于微处理器RTL级系统的评估,在函数提取过程中研究函数内部的频繁使用路径,研究了这些最频繁函数中的最频繁使用路径,了解基准程序的运行行为,为处理器的初级阶段的研究提供一些类基准程序,快速评估初级的处理器性能。     

管控机房计算机程序的运行

为提高课堂教学效率,需要加强对机房计算机可运行程序的管控.通过对Windows系统策略的配置和注册表的研究与实践,以及对计算机系统运行程序管控,并进一步采用批处理编程,实现了远程限制机房计算机程序的运行,有效提高了机房管理效率.     

自动化软件错误定位技术研究进展

调试过程中代价最昂贵和最耗时的活动之一就是定位错误.为了辅助开发人员进行程序错误的定位和修正,自动化错误定位技术通过对源程序、测试结果以及各种程序行为特征信息的计算分析,给出造成故障的软件缺陷在源代码中的可能位置.文中对现有错误定位技术进行了分类,介绍了各种代表性技术的原理以及建模方法,并给出了常用的评测基准集和评价标...     

微机系统基于WINDOWS环境下的图形基准程序

微机的图形性能已经成为微机性能的一个重要方面,但是目前尚未有标准的微机图形基准程序。本文介绍了我们设计的适合于微机系统的基于ＷＩＮＤＯＷＳ环境下的一组图形基准程序,以便测试微机的图形性能,并通过运行这组基准程序组出了几种微机的图形性能价格格比分析。     

程序正确性测试的相关技术进展

本文介绍了程序正确性测试的基本原理,并讨论了有关的测试技术,包括以程序规约为基准的黑箱测试和以程序实现结构为基准的白箱测试两个方面。随后探讨了相关技术向分布式程序的拓展问题。     

神经程序修复领域数据泄露问题的实证研究

修复软件缺陷是软件工程领域一个无法回避的重要问题,而程序自动修复技术则旨在自动、准确且高效地修复存在缺陷的程序,以缓解软件缺陷所带来的问题.近年来,随着深度学习的快速发展,程序自动修复领域兴起了一种使用深度神经网络去自动捕捉缺陷程序和其补丁之间关系的方法,被称为神经程序修复.从在基准测试上被正确修复的缺陷的数量上看,神经程序修复工具的修复性能已经显著超过了非学习的程序自动修复工具.然而,近期有研究发现神经程序修复系统性能的提升可能得益于测试数据在训练数据中存在,即数据泄露.受此启发,为进一步探究神经程序修复系统数据泄露的原因及影响,更公平地评估现有的系统,本文(1)对现有神经程序修复系统进行了系统的分类和总结,根据分类结果定义了神经程序修复系统的数据泄露,并为每个类别的系统设计了数据泄露的检测方法;(2)依照上一步骤中的数据泄露检测方法对现有模型展开了大规模检测,并探究了数据泄露对模型真实性能与评估性能间差异的影响以及对模型本身的影响;(3)分析现有神经程序修复系统数据集的收集和过滤策略,加以改进和补充,在现有流行的数据集上基于改进后的策略构建了一个纯净的大规模程序修复训练数据集,并验证了该数据集避免数据泄露的有效性.实验结果发现:本次调研的10个神经程序修复系统在基准测试集上均出现了数据泄露,其中神经程序修复系统RewardRepair的数据泄露问题较为严重,在基准测试集Defects4J(v1.2.0)上的数据泄露达24处,泄露比例高达53.33%.此外,数据泄露对神经程序修复系统的鲁棒性也造成了影响,调研的5个神经程序修复系统均因数据泄露产生了鲁棒性降低的问题.由此可见,数据泄露是一个十分常见的问题,且会使神经程序修复系统得到不公平的性能评估结果,以及影响系统本身的性质.研究人员在训练神经程序修复模型时,应尽可能避免出现数据泄露,且要考虑数据泄露问题对神经程序修复系统性能评估产生的影响,尽可能更公平地评估系统.     

CloudBM:云数据管理系统测试基准

随着云计算技术和云数据管理技术的不断发展,越来越多的云数据管理系统纷纷面世,为人们提供了一种以经济实用的方式管理海量数据的方案。面对各种各样纷繁复杂的云数据管理系统,如何结合不同的应用场景对它们进行全面详细的性能评价是目前亟待解决的挑战性问题。以电信业务中用户访问记录存储系统为应用背景,结合云数据管理系统的应用特点,设计了一个具有广泛代表性的测试基准,并对目前主流的云数据管理系统进行了实际测试。通过对测试结果进行对比分析,为用户提供了一个可供参考的性能评价结果,同时验证了该测试基准的可靠性和广泛适用性。     

基于SPEC 2000的桌面操作系统与处理器适配评测

桌面操作系统与处理器的适配评测是提升国产计算机系统质量的重要途径,传统桌面操作系统的评测侧重于软件本身的测试,不能够全面反映其与处理器的适配性能。基于SPEC 2000基准程序集,提出通过比较基准程序集在不同桌面操作系统下的评测分值差异来反映桌面操作系统与处理器的适配性能。进一步提出了剔除程度因子(λ)用以分析不同基准程序对任意两个桌面操作系统评测分值差值的影响,并选用了三种典型的桌面操作系统进行了验证。实验结果表明,剔除对两桌面操作系统差值较大的基准程序或者差值较小的基准程序在一定的λ值下会使不同桌面操作系统下的SPEC 2000整点运算评测分值发生逆转。文中提出的方法是相关软件评测标准在软硬件适配性能维度上的扩展,剔除程度因子的提出有利于判定对桌面操作系统评测分值差值影响较大的基准程序,进而可用于指导桌面操作系统和基准程序的改进和优化。     

An analysis of the computational and parallel complexity of the Livermore Loops

This paper presents and analyzes the computational and parallel complexity of the Livermore Loops. The Loops represent the type of computational kernels typically found in large-scale scientific computing and have been used to benchmark computer system since the mid-60's. On parallel systems, a process's computational structure can greatly affect its efficiency. If the loops are to be used to benchmark such systems, their computations must be understood thoroughly, so that efficient implementations may be written. This paper addresses that concern.     

Analysis of Database System Architectures Using Benchmarks

Database machine architectures have been proposed as a promising alternative to improve database system performance, control, and flexibility. While many claims have been made for the database machine concept, few studies have been made to test the performance advantages and disadvantages of a database machine in an application environment. A comprehensive benchmark study comparing the performance of database systems on a conventional computer system and a database machine is reported in this paper. The results show the database machine architecture to have superior performance in most cases. The performance advantage is sensitive to the communication line speed between the host computer and the database machine. The effects of line speed are studied and displayed in the benchmark results. A summary of the similarities and differences between the architectures based upon our benchmark results completes the paper.     

数据库系统应用基准测试规范设计方法

为准确度量数据库系统对领域应用系统的支撑能力,提出了一种应用基准测试规范设计方法,指导数据库系统的基准测试。提出以动作、环境、负载等信息项为框架,建立数据库系统使用需求集,规范初始信息格式;将使用需求初分为操作场景,建立关键变量矩阵,并应用K-means算法、层次式聚类等方法进行操作场景分组,确认典型应用系统集;设计了基准测试用例结构,提出了环境要求、事务要求、执行要求等重要信息项,并构建测试规范框架,描述了典型应用系统与应用基准测试规范的关系;通过实例应用,证明了该方法的可行性与适用性。所提方法可辅助解决应用系统在多个数据库系统中择优选型问题,也可用于数据库系统厂商自测,促进产品能力提升。     

The Manchester dataflow machine

A prototype dataflow computer system has been constructed by a research team at the University of Manchester. The hardware has been operational since October 1981, but has been steadily enhanced since that time. Store capacities and I/O bandwidth are approaching the state where realistically large applications programs can be used to evaluate system performance.During the period of hardware enhancement, there have been parallel advances in the development of dataflow system software in the form of assemblers, compilers, debugging systems and sundry software tools. The software is also approaching readiness for application to large-scale benchmark programs.The Manchester system implements a tagged-token dataflow model of computation. This model imposes a tag-field penalty on data values in order to maximise asynchronousness of instruction execution. It is important to know to what extent this overhead is necessary, and how to minimise it whilst maintaining acceptable asynchronousness. In comparison with more conventional architectures it is important that useful measures of cost and performance be developed. With emphasis on these issues, the paper describes the structure of the Manchester dataflow hardware and software, and outlines the system performance results so far obtained. Whilst this work is far from complete, it suggests new avenues for hardware and software development which are being followed at Manchester and elsewhere.     

The Manchester dataflow machine

A prototype dataflow computer system has been constructed by a search team at the University of Manchester. The hardware has been operational since October 1981, but has been steadily enhanced since that time. Store capacities and I/O bandwidth are approaching the state where realistically large application programs can be used to evaluate system performance.During the period of hardware enhancement, there have been parallel advances in the development of dataflow system software in the form of assemblers, compilers, debugging systems and sundry software tools. The software is also approaching readiness for application to large-scale benchmark programs.The Manchester system implements a tagged-token dataflow model of computation. This model imposes a tag-field penalty on data values in order to maximise asynchronousness of instruction execution. It is important to know to what extent this overhead is necessary, and how to minimise it whilst maintaining acceptable asynchronousness. In comparison with more conventional architectures it is important that useful measures of cost and performance be developed.With emphasis on these issues, the paper describes the structure of the Manchester dataflow hardware and software, and outlines the system performance results so far obtained. Whilst this work is far from complete, it suggests new avenues for hardware and software development which are being followed at Manchester and elsewhere.     

HPCC:面向存储访问模型的基准测试--一种可能替代TOP500 HPL的测试方法

高性能计算机系统的性能评价历来是本领域所关注的重要问题．TOP500排名所采用的标准测试HPL（High Performance Linpack）并不能真实的反映系统各方面的性能，尤其是存储访问方面．HPC Challenge基准测试则着重于各种存储访问模型，在HPL的基础之上又整合了多个有代表性的核心测试程序，很有可能在未来取代现在TOP500采用的的HPL测试．本文首先简单介绍HPC Challenge诞生的背景，解释基准测试的基本概念和原理，从存储访问模型的角度对各项测试进行了描述，并根据实际的测试结果进行比较和分析．最后给出结论以及将来的工作．     

A Pareto-based multi-objective evolutionary algorithm for automatic rule generation in network intrusion detection systems

Attacks against computer systems are becoming more complex, making it necessary to continually improve the security systems, such as intrusion detection systems which provide security for computer systems by distinguishing between hostile and non-hostile activity. Intrusion detection systems are usually classified into two main categories according to whether they are based on misuse (signature-based) detection or on anomaly detection. With the aim of minimizing the number of wrong decisions, a new Pareto-based multi-objective evolutionary algorithm is used to optimize the automatic rule generation of a signature-based intrusion detection system (IDS). This optimizer, included within a network IDS, has been evaluated using a benchmark dataset and real traffic of a Spanish university. The results obtained in this real application show the advantages of using this multi-objective approach.     

Design of a simulation model for high performance LINPACK in hybrid CPU-GPU systems

The Journal of Supercomputing - High performance LINPACK (HPL) benchmark is used to evaluate the maximum floating-point performance of a computer cluster. Since the performance of the graphics...