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值算法,本文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析策略,最后给出了在pvm并行编程环境下的具体实现方法。     

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。     

多线程RPC分布式计算的实现

采用多线程RPC（Remote Procedure Call)很容易实现Unix系统下的分布式计算，网络上的工作站组可以在运行本机应用的同时通过后台运行的server为其它计算机提供计算功能，用一组低档工作站获得多CPU服务器的计算能力，讨论了XDR数据传输，server与client程序结构以及多线程或多进程RPC调用的实现方法。     

UNIX工作站与DOS PC之间的对等通讯

各网络节点之间的对等通讯是实现Ｃ／Ｓ应用的基础，在异构网络中需要在不同的网络节点上支持同一种对等通讯协议。为此，本文在简要介绍Ｓｕｎ ＯＳ下用ＮＩＴ进行链路层网络存取的方法和ＮｅｔＷａｒｅ ＮｅｔＢＩＯＳ各种包格式的基础上，给出了一种在ＵＮＩＸ工作站上实现的ＮｅｔＢＩＯＳ功能，以支持在ＵＮＩＸ工作站和ＤＯＳ ＰＣ之间用ＮｅｔＢＩＯＳ对等通讯。     

UNIX操作系统X—Window汉字系统的实现技术

本文论述了在ＵＮＩＸ操作系统Ｘ－Ｗｉｎｄｏｗ窗口环境下实现软件汉化的方法和途径，详细介绍了嵌入式汉字系统的设计思想与实现技术，包括汉字输入，输出和编辑等功能，为工作站上ＵＮＩＸ操作系统下商品化软件的汉化提供了一条可行的途径。     

实现对等通信的软件接口技术

各网络节点之间的对等通信是实现Ｃ／Ｓ应用的基础。在异构网络中需要在不同的网络节点上支持同一种对等通信协议。为此，本文在简要介绍Ｓｕｎ ＯＳ下用ＮＩＴ进行链路层网络存取的方法和ＮｅｔＷａｒｅ ＮｅｔＢＩＯＳ各种包格式的基础上，给出了一种在ＵＮＩＸ工作站上实现的ＮｅｔＢＩＯＳ功能，以支持在ＵＮＩＸ工作站和ＤＯＳ ＰＣ之间用ＮｅｔＢＩＯＳ进行对等通信。     

局部网中实时通信问题的研究

本文论述了在局部网中一种通用实时数据通信的实现技术，解决了网络环境下利用多缓冲区将实时数据从一台工作站的内存迅速转输到网上其它工作站内存的实时传输问题，并给如何实现ＷＩＮＤＯＷＳ环境下实时通信的编程方法。     

基于IPX的工作站之间实时通信的实现

本文讨论了在Ｎｏｖｅｌｌ网络环境下，实现工作站之间实时通信的三种方法，重点介绍了基于ＩＰＸ／ＳＰＸ协议实现工作站之间实时通信的方法，采用该方法开发的通信程序已在笔者所开发的实际系统中得到应用，效果良好。     

三维动画在HP工作站上的实现

本文介绍了在HP工作站上实现3D动画的方法，首先介绍了HP工作站的显示系统，在PCDX图像文件格式的基础上设计了一种动画图像文件格式，并对图像文件的压缩，反压缩算法进行了讨论。     

UNIX操作系统X－Window汉字系统的实现技术

本文论述了在ＵＮＩＸ操作系统Ｘ－Ｗｉｎｄｏｗ窗口环境下实现软件汉化的方法和途径，详细介绍了嵌入武汉字系统的设计思想与实现技术，包括汉字输人、输出和编辑等功能，为工作站上ＵＮＩＸ操作系统下商品化软件的汉化提供了一条可行的途径．     

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．     

A parallel asynchronous implementation of the ϵ-relaxation method for the linear minimum cost flow problem

In this paper we present a parallel asynchronous implementation of the ϵ-relaxation method for solving the linear minimum cost flow problem on distributed memory message-passing multiprocessor systems. The general structure of the method is well suited to efficient parallelization, since a single iteration can be performed on several nodes simultaneously. We describe the implementation details of the parallel version on both a Fujitsu AP1000 and a cluster of Digital Alpha workstations connected via FDDI links. The results obtained demonstrate that our implementation is capable of substantial speedups.     

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.     

Anonymous remote computing: a paradigm for parallel programming oninterconnected workstations

Parallel computing on interconnected workstations is becoming a viable and attractive proposition due to the rapid growth in speeds of interconnection networks and processors. In the case of workstation clusters, there is always a considerable amount of unused computing capacity available in the network. However, heterogeneity in architectures and operating systems, load variations on machines, variations in machine availability, and failure susceptibility of networks and workstations complicate the situation for the programmer. In this context, new programming paradigms that reduce the burden involved in programming for distribution, load adaptability, heterogeneity and fault tolerance gain importance. This paper identifies the issues involved in parallel computing on a network of workstations. The anonymous remote computing (ARC) paradigm is proposed to address the issues specific to parallel programming on workstation systems. ARC differs from the conventional communicating process model by treating a program as one single entity consisting of several loosely coupled remote instruction blocks instead of treating it as a collection of processes. The ARC approach results in distribution transparency and heterogeneity transparency. At the same time, it provides fault tolerance and load adaptability to parallel programs on workstations. ARC is developed in a two-tiered architecture consisting of high level language constructs and low level ARC primitives. The paper describes an implementation of the ARC kernel supporting ARC primitives     

Efficient scheduling of MPI applications on networks of workstations

The availability of a large number of workstations connected through a network can represent an attractive option for high-performance computing for many applications. The message-passing interface (MPI) software environment is an effort from many organisations to define a de facto message-passing standard. In other words, the original specification was not designed as a comprehensive parallel programming environment and some researchers agree that the standard should be preserved as simple and clean as possible. Nevertheless, a software environment such as MPI should have somehow a scheduling mechanism for the effective submission of parallel applications on network of workstations. This paper presents an alternative lightweight approach called Selective-MPI (S-MPI), which was designed to enhance the efficiency of the scheduling of applications on an MPI implementation environment.     

Parallel processing of chemical information in a local area network — I. HYDRA: Concept,configuration, and implementation of parallel applications

Sophisticated software packages put an increasing demand on computer hardware. In local area networks, computational intensive programs can lower the performance of individual workstations to an unacceptable level. However, utilizing in a coarse grained sense the computing power of all hosts in such networks, offers the potential to achieve considerable improvements in execution speed within reasonable cost limits. Since conventional workstations are not designed to be used in a parallel configuration, the program HYDRA is developed to control and synchronize parallel processing in a local area network. Part I of this paper focuses on the technical aspects of HYDRA, i.e. configuration and implementation. The second and third parts describe two applications of the HYDRA package in the field of chemistry: using parallel genetic algorithms for the conformational analysis of nucleic acids, and parallel cross-validation of artificial neural networks.     

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.     

Modeling and distributed simulation of a broadband-ISDN network

A distributed approach to communication network simulation using a network of workstations configured as a loosely coupled parallel processor to model and simulate the broadband integrated services digital network (B-ISDN) is proposed. In a loosely coupled parallel processor system, a number of concurrently executable processors communicate asynchronously using explicit messages over high-speed links. Since this architecture is similar to that of B-ISDN networks, it constitutes a realistic testbed for their modeling and simulation. The authors describe an implementation of this approach on 50 Sun workstations at Brown University. Performance results, based on representative B-ISDN networks and realistic traffic models, indicate that the distributed approach is efficient and accurate     

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