矩阵相乘Cannon并行算法在工作站机群上的实现

矩阵相乘Cannon并行算法是一个基于分布式存储多处理机模型的并行数据算法，文章研究了它在工作站机群上的实现。在满足负载平衡和减少网络间数据传输的条件下，主要探讨了子任务在工作站上的优化分配策略，最后给出了在PVM并行编程环境下的具体实现方法。     

在线直通车

1.Windows NT Server 4.0中文版下无盘工作站的安装、配置和实现 无盘工作站的工作方式在当前还很有市场,该文就是讲述如何配置NT的无盘工作站的方法,介绍了NT所不支持的网卡记录的添加办法,并给出了实现DOS无盘工作站的详细过程及在此基础上实现Windows 3.2、Windows 95远程启动工作站的步骤和具体配置。     

Linux下IPv6高级路由器的实现

介绍了IPv6的网络路由器的原理和在Linux上的具体实现方法。讨论了在Linux下如何组建IPv6网络试验平台,重点讨论如何将Linux工作站配置成路由器。然后介绍了静态路由和动态RIPng路由服务在Linux下的实现方法。     

用LAT协议连接SUNnet和DECnet

本文介绍ＳＵＮｎｅｔ和ＤＥＣｎｅｔ的通信方法，ＬＡＴ协议在ＳＵＮ工作站上的实现：在此基础上实现了ＤＥＣｎｅｔ中的终端和微机在ＳＵＮ工作站上的登录，以及ＳＵＮ工作站与微机ＰＣ之间远程文件传送功能。     

基于PXE无盘工作站的成功应用

微软最后推出Windows2000 SP4补丁,在很大程度上完善Windows2000操作系统。使用BXP软件．在PXE引导方式下,以Windows2003为平台组建Windows2000工作站,实现了无盘工作站组建。而在实际工作中总有一批被更换下来的计算机,要继续使用,却体现不出价值,无盘工作站技术功不可没。     

基于局域网的有限元网格分布式并行生成

在常见的PC＋Windows＋LAN环境下,采用Winsock API网络通信接口实现了局域网上的分布式并行有限元网格生成。网格生成区域在服务器上按照工作站数量被分解为若干个子区域,这些子区域及网格控制参数通过局域网（LAN）传给工作站。子区域在工作站上被剖分成子网格并通过局域网传回服务器以合并形成最终网格。算例表明只要有足够的计算节点,分布式并行技术可以将网格生成速度大幅度提高,而网络通信所占时间的比例基本固定。     

基于Windows2003的无盘WinXP网络的安装

微软已不再对Windows2000提供系统升级包,Windows2000的无盘工作站已经不能满足当前的需求.使用BXP软件,在PXE引导方式下,可以安装Windows2003平台上的WindowsXP无盘工作站,实现了无盘网络组建的更新换代。     

GKD-PROLOG/SUN多窗口系统的设计与实现

本文较系统地介绍和分析了SUN工作站上支持多窗口用户界面开发的窗口系统SUNVIEW,并根据PROLOG语言的特点,详细地讨论了在SUN工作站上PROLOG多窗口系统的设计思想,以及该系统与PROLOG解释器及各种工具软件的连接方法和在SUN工作站上的实现技术     

中文之星2.0在Netware 3.12下实现完全网络化共享

中文之星2.0是目前Windows环境下应用最广泛的中文平台之一,它所特有的智能化汉字输入法及一组迎合国情的实用工具(如轻松表格、艺术汉字等)得到广大用户的喜爱,其不足之处是无法在网络上实现完全的资源共享。在Netware 3.12局域网环境下,选用中文之星2.0的网络安装方式可方便地将其装至服务器和工作站中,但只能共享字库,而不能共享输入法和实用工具,这样就需要把大约7MB的内容安装在工作站上,占用工作站较大的空间。笔者在实践中摸索出一套安装方法,可使中文之星2.0在Netware 3.12下实现完全的资源共享。该方法具体操作如下:     

WINDOWS NT4.0下无盘DOS工作站的安装方法

InstallatingMethodofNon-HarddiskWorkstationinWindowsNT4．0ZhaoLuyunFanJinjunMicrosoft的Wnd0WSNT,由于功能强大提供了与Win一个eds相同的用户界面,使用户更容易接受,同时也减轻了网络管理员的负担,因此市场占有率直线上升。在网络的实现中,有盘工作站与无盘工作站在费用上相差悬殊,而两者在功能上则完全相同。在某些情况下,为了节约开支,网络中经常要用到无盘工作站,另外现在计算机应用中对DOS熟知的人较多,有众多软件还必须在］yJS环境下运行,所以WindOWSNT4．0下无盘IX）SI作站的安装成为迫切要求。以下简…     

Explicit nonlinear dynamic finite element analysis on homogeneous/heterogeneous parallel computing environment

This paper presents parallel computational strategies to implement explicit nonlinear finite element analysis code onto distributed memory parallel computers for solving large-scale problems in structural dynamics. Implementation details on both homogeneous and heterogeneous parallel processing environments are considered in detail in this paper. Implementation of an explicit nonlinear finite element dynamic analysis code on homogeneous systems is discussed first and this is later moved onto heterogeneous systems. Domain decomposition with explicit message passing is preferred for parallel implementation. The message passing implementation in the parallel algorithm is based on MPI (Message Passing Interface) libraries. Implementation aspects of overlapped, non-overlapped domain decomposition techniques, Dynamic Task Allocation (DTA) and clustering techniques for DTA and their relative merits are presented. The interprocessor communications are optimised by overlapping with computations to improve the performance of the domain decomposition based explicit dynamic analysis finite element code.The issues related to implementation of finite element code for nonlinear dynamic analysis on heterogeneous parallel computing environment are later presented. A new dynamic load-balancing algorithm is developed for this purpose and it is integrated with the domain decomposition based parallel explicit finite element code to test our algorithms on a coarse grain heterogeneous cluster of workstations. Numerical experiments have been carried out on PARAM-10000, an Indian parallel computer and also on cluster of Unix workstations.     

Benchmarking Explicit State Parallel Model Checkers

This paper presents a set of benchmarks and metrics for performance reporting in explicit state parallel model checking algorithms. The benchmarks are selected for controllability, and the metrics are chosen to measure speedup and communication overhead. The benchmarks and metrics are used to compare two parallel model checking algorithms: partition and random walk. Implementations of the partition algorithm using synchronous and asynchronous communication are used. Metrics are reported for each benchmark and algorithm for up to 128 workstations using a network of dynamically loaded workstations. Empirical results show that load balancing becomes an issue for more than 32 workstations in the partition algorithm and that random walk is a reasonable, low overhead, approach for finding errors in large models. The synchronous implementation is consistently faster than the asynchronous. The benchmarks, metrics and results given here are intended to be a starting point for a larger discussion of performance reporting in parallel explicit state model checking.     

基于工作站机群的PVM系统的序列比对

序列比对是分子生物学研究领域的一个重要的工具。在DNA数据量急剧增加的今天，高效的序列比对算法在研究新发现的次序中显得非常重要。通过Smith和Waterman法用PVM系统在工作站机群上已完成了分布式序列比对法。也同样在Inter iPSC/860高效性能并行计算机上获得了成功。这个分布式Smith-Waterman算法在Internet GRAIL和GENQUEST上充当搜索工具。该文论述了此算法的实现和性能指标。     

Parallel volume rendering using binary-swap compositing

We describe a parallel volume-rendering algorithm, which consists of two parts: parallel ray tracing and parallel compositing. In the most recent implementation on Connection Machine's CM-5 and networked workstations, the parallel volume renderer evenly distributes data to the computing resources available. Without the need to communicate with other processing units, each subvolume is ray traced locally and generates a partial image. The parallel compositing process then merges all resulting partial images in depth order to produce the complete image. The compositing algorithm is particularly effective for massively parallel processing, as it always uses all processing units by repeatedly subdividing the partial images and distributing them to the appropriate processing units. Test results on both the CM-5 and the workstations are promising. They do, however, expose different performance issues for each platform     

一种针对结构化并行控制机制的任务调度算法

缩短程序的执行时间是并行处理的首要目标,有效的任务分配算法是实现这一目标的关键,对机群系统来说更是如此.研究机群系统上针对结构化并行控制机制的任务调度问题,并基于贪心算法、粒度控制、反馈式分派的原则,提出近优的任务调度算法SSA(sub-optimal scheduling algorithm).实验结果表明,在机群环境下,该算法的并行计算性能与其他算法相比均有所提高.     

Sidle的远程执行设备

Ｓｉｄｌｅ系统是运行在ＳＵＮ工作站网络上的一组实用程序，利用空闲的处理机资源进行大粒度的并行计算．同其它远程执行设备相比，它能支持程序内部并行和嵌套的远程执行，允许一个服务员机接受多个远程执行任务．本文介绍了这些特点和透明性的实现方法．     

SPEED: A parallel platform for solving and predicting the performance of PDEs on distributed systems

Distributed systems such as networks of workstations are becoming an increasingly viable alternative to traditional supercomputer systems for running complex scientific applications. A large number of these applications require solving sets of partial differential equations (PDEs). In this paper, we describe the implementation and performance of SPEED (Scalable Partial differential Equation Environment on Distributed systems), a parallel platform which provides an efficient solution for time-dependent PDEs. SPEED allows the inclusion of a wide range of parameters and programming aids. PVM is employed as the underlying message-passing system. The parallel implementation has been performed using two algorithms. The first algorithm is a two-phase scheme which uses the conventional technique of alternating phases of computation and communication. The second algorithm employs a pre-computation technique that allows overlapping of computation and communication. Both methods yield significant speedups. The pre-computation technique reduces the communication time between the workstations but incurs additional overhead in buffer management. Hence, if the saving in communication time is larger than the overhead, the pre-computation technique outperforms the two-phase algorithm. SPEED also provides a performance prediction methodology that can accurately predict the performance of a given application on the system before running the application. This methodology allows the user to tune various parameters in order to identify system bottlenecks and maximize the performance.     

分布异构工作站上的任务调度算法

讨论了在一个由高速局域网连接的高性能异构工作站平台上，如何有效地利用空闲工作站来求解计算密集型任务矩阵相乘的问题，为了获得较好的并行计算性能，文中给出了一个异构工作站群之间任务调度的模型和算法，算法中考虑了并行计算中协作任务间的通信时间、数据加栽时间、结果收集时间和各个异构工作站的任务计算时间，通过这个模型，可以在所有可利用的工作站集合中找出最适合的子集，获得最短的执行时间．     

A network parallel genetic algorithm for the one machine sequencing problem

This paper presents a network parallel genetic algorithm for the one machine sequencing problem. It examines a parallel genetic algorithm in which processors exchange their best solution found at periodic intervals and the case when no exchange is performed. The network parallel genetic algorithm is executed on a cluster of IBM RS/6000 workstations using a master-slave approach. Performance to a serial genetic algorithm is reported.