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。     

视频服务器网络中影像对象映射问题的研究

视频服务器网络中的影像对象映射问题是一种新的组合优化问题.服务器网络可以建立在基于局域网的工作站网络之上,也可以建立在广域网之上.基于对用户的服务请求模式、服务器网络的存储容量和通信带宽等因素的综合考虑,研究了服务器网络中影像对象映射问题,利用局部搜索算法给出了一套对该映射问题的解决方案.然后用一套基准集实例对给出的算法集进行验证.结果表明,在较短的计算时间内,该算法可以得到近似最优解的方案.     

Performance bottlenecks and potentials of parallel computing on networks of workstations

The network of workstations (NOW) we consider for parallel computing is heterogeneous and nondedicated (time-sharing), where computing power varies among the workstations, and multiple jobs may interact with each other in execution. We address three performance issues in this paper. First, we examine the effects of heterogeneity on co-scheduling and local scheduling policies for parallel computing. Through experimentation and quantitative comparisons, we discuss features and requirements of scheduling policies on heterogeneous NOW. Second, the heterogeneity and non-dedication of NOW introduce new performance factors into parallel computing, which make traditional performance metrics for parallel computing under homogeneous platforms not suitable. We conducted a collection of experimental measurements to show the performance impact to parallel computing. Finally, using network latencies we experimentally evaluate the parallel computing scalability on NOW. Our objective of this study is to provide insights into unique performance bottlenecks and potentials of networks of workstations.     

Performance evaluation of a Windows NT based PC cluster for high performance computing

In recent times the computational power of personal computers has remarkably increased and the use of groups of PCs and workstations, connected by a network and dedicated to parallel computations, is today frequent. Computing clusters are mainly based on UNIX workstations and Linux PCs but, in the last few years, different implementations of message passing systems were made available also for Microsoft Windows. In this work we test the performance of two implementations of MPI for Windows platforms, and we compare the results with those obtained from Linux systems.     

异构集群的一种基于遗传的负载均衡改进算法

计算机集群系统是通过网络将一组PC或工作站连接起来,架构成的高可靠、可扩展的集群服务器,能够统一调度、协调运行,实现高效并行处理。负载均衡是集群系统良好性能的保障。用节点的总体资源、CPU的就绪队列长度和节点的任务数来构造遗传算法的目标函数,既考虑了集群异构的特点,又能很好的体现负载程度,通过使用网络压力测试工具对该算法进行性能测试,表明了其具有比较好的优越性。     

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.     

Prophet: automated scheduling of SPMD programs in workstation networks

Obtaining efficient execution of parallel programs in workstation networks is a difficult problem for the user. Unlike dedicated parallel computer resources, network resources are shared, heterogeneous, vary in availability, and offer communication performance that is still an order of magnitude slower than parallel computer interconnection networks. Prophet, a system that automatically schedules data parallel SPMD programs in workstation networks for the user, has been developed. Prophet uses application and resource information to select the appropriate type and number of workstations, divide the application into component tasks and data across these workstations, and assign tasks to workstations. This system has been integrated into the Mentat parallel processing system developed at the University of Virginia. A suite of scientific Mentat applications has been scheduled using Prophet on a heterogeneous workstation network. The results are promising and demonstrate that scheduling SPMD applications can be automated with good performance. Copyright © 1999 John Wiley & Sons, Ltd.     

Coordinating Parallel Processes on Networks of Workstations

The network of workstations (NOW) we consider for scheduling is heterogeneous and nondedicated, where computing power varies among the workstations and local and parallel jobs may interact with each other in execution. An effective NOW scheduling scheme needs sufficient information about system heterogeneity and job interactions. We use the measured power weight of each workstation to quantify the differences of computing capability in the system. Without a processing power usage agreement between parallel jobs and local user jobs in a workstation, job interactions are unpredictable, and performance of either type of jobs may not be guaranteed. Using the quantified and deterministic system information, we design a scheduling scheme calledself-coordinated local schedulingon a heterogeneous NOW. Based on a power usage agreement between local and parallel jobs, this scheme coordinates parallel processes independently in each workstation based on the coscheduling principle. We discuss its implementation on Unix System V Release 4 (SVR4). Our simulation results on a heterogeneous NOW show the effectiveness of the self-coordinated local scheduling scheme.     

Coupling hundreds of workstations for parallel molecular sequence analysis

We present a highly scalable approach to distributed parallel computing on workstations in the Internet which provides significant speed-up to molecular biology sequence analysis. Recent developments show that smaller numbers of workstations connected via a local area network can be used efficiently for parallel computing. This work emphasizes scalability with respect to the number of workstations employed. We show that a massively parallel approach using several hundred workstations, dispersed over all continents, can successfully be applied for solving problems with low requirements on communication bandwidth. We calculated the optimal local alignment scores between a single genetic sequence and all sequences of a genetic sequence database using the ssearch code that is well known among molecular biologists. In a heterogeneous network with more than 800 workstations this job terminated after several minutes, in contrast to several days it would have taken on a single machine.     

Distributed concurrent engineering computation on a network of microcomputers

A programming method that facilitates interworkstation communications on a local area network (LAN) of microcomputers has been developed. Communications are managed using a set of common access status and data files, which are writen to and read from the file server hard disk.Use of this programming method permits the work load associated with large computational problems to be distributed to various workstations connected to a LAN for concurrent processing, and has resulted in substantial solution time savings in problems that have been run.Test problems have been programmed in IBM Compiled BASIC [1] and are continuing with further programs in BASIC and IBM Professional FORTRAN [2]. Applications to actual computational engineering problems are presently being investigated and are briefly discussed.This paper describes the basic principles underlying the distributed processing technique that was developed and presents several example problems that were run to test the technique and develop benchmark results for a particular LAN configuration.     

The Hector distributed run-time environment

Harnessing the computational capabilities of a network of workstations promises to off-load work from overloaded supercomputers onto largely idle resources overnight. Several capabilities are needed to do this, including support for an architecture-independent parallel programming environment, task migration, automatic resource allocation, and fault tolerance. The Hector distributed run-time environment is designed to present these capabilities transparently to programmers. MPI programs can be run under this environment on homogeneous clusters with no modifications to their source code needed. The design of Hector, its internal structure, and several benchmarks and tests are presented     

基于并行容错网的对等服务器集群的设计与实现

为了提高服务器系统的可靠性、可用性和性能,并改变目前非对称式服务器集群资源利用率低的状况,我们提出了一种新的服务器集群实现方案一基于并行容错网的对等服务器集群。在服务器集群的实现中,我们采用了软件集群的方法,设计实现了服务器集群管理层和并行容错通信层。     

A concurrent process creation service to support SPMD based parallel processing on COWs

Current software environments used to support parallel processing on a cluster of workstations (COW) are not satisfactory, do not provide complete transparency and are not specifically designed for parallel processing. In particular, the establishment of a parallel processing environment and the initialisation of parallel processes suffer from poor performance. Each parallel process of an application is created sequentially and in many cases the logon operation must be completed before remote resources could be acquired. These operations are also performed manually. We present in this paper an original approach that addresses the problem of parallel process creation. The remote workstations are acquired completely transparently and dynamically, and parallel processes are created concurrently. To demonstrate the feasibility of this approach we show a system based on RHODOS (a client/server and microkernel based distributed operating system), specifically designed to improve the performance of process instantiation and therefore able to improve the overall execution performance of parallel programs, in particular parallel process creation. Copyright © 1999 John Wiley & Sons, Ltd.     

A slowdown model for applications executing on time-shared clustersof workstations

Distributed applications executing on clustered environments typically share resources (computers and network links) with other applications. In such systems, application execution may be retarded by the competition for these shared resources. In this paper, we define a model that calculates the slowdown imposed on applications in time-shared multi-user clusters. Our model focuses on three kinds of slowdown: local slowdown, which synthesizes the effect of contention for CPU in a single workstation; communication slowdown, which synthesizes the effect of contention for the workstations and network links on communication costs; and aggregate slowdown, which determines the effect of contention on a parallel task caused by other applications executing on the entire cluster, i.e., on the nodes used by the parallel application. We verify empirically that this model provides an accurate estimate of application performance for a set of compute-intensive parallel applications on different clusters with a variety of emulated loads     

Metacomputing with Mobile Agents

In this paper we present Parallel Computing with Mobile Agents (PaCMAn), a mobile agent based Metacomputer that enables its users to utilize idle resources on the internet to tackle computational problems that could not be handled efficiently with their own resources. The PaCMAn launches multiple mobile agents that cooperate and communicate to solve problems in parallel. Each agent supports the basic communication and synchronization tasks of the classical parallel worker assuming the role of a process in a parallel processing application. Application tasks, however, are assigned dynamically to the PaCMAn’s mobile agents via TaskHandlers. TaskHandlers are Java objects capable of implementing particular tasks of the application. The PaCMAn consists of three major components: Broker, Server and Client. A server machine has to be explicitly registered in order to take part in the PaCMAn Metacomputer. A number of brokers keep track of the available resources. In the PaCMAn system both server and client machines can be located anywhere in the Internet. The clients select the servers that they will utilize based on the specific resource requirements. We have developed and tested prototype systems with several applications. These prototypes provide proof of concept of our proposed Metacomputing philosophy. Furthermore they have demonstrated that PaCMAn provides parallel efficiency. We also demonstrate that the PaCMAn Metacomputer can be used as the computational engine for the creation of sophisticated Pervasive Services anywhere anytime.     

Parallelizing a Level 3 BLAS Library for LAN-Connected Workstations

LAN-connected workstations are a heterogeneous environment, where each workstation provides time-varying computing power, and thus dynamic load balancing mechanisms are necessary for parallel applications to run efficiently. Parallel basic linear algebra subprograms (BLAS) have recently shown promise as a means of taking advantage of parallel computing in solving scientific problems. Most existing parallel algorithms of BLAS are designed for conventional parallel computers; they do not take the particular characteristics of LAN-connected workstations into consideration. This paper presents a parallelizing method of Level 3 BLAS for LAN-connected workstations. The parallelizing method makes dynamic load balancing throughcolumn-blockingdata distribution. The experiment results indicate that this dynamic load balancing mechanism really leads to a more efficient parallel level 3 BLAS for LAN-connected workstations.     

基于任务树的分布式计算平台的设计与实现

针对当前网络中PC资源利用率低和大型任务的难解性，设计并实现了一个通用的基于任务树的分布式计算平台TT-DCP（Distributed Computing Platform based on Task Tree）．TT—DCP旨在利用网络中计算机的空闲时间求解可分布运行的大型任务，主要包括服务器端程序、客户端程序、后台数据库三部分．服务器端程序主要负责利用任务树描述大型任务、对树的操作以及处理客户端返回的任务结果；客户端程序采用主动式策略获取子任务，并下载任务到本地执行、将结果返回服务器；后台数据库保存任务树．任务分布化过程中，提出采用任务树结构保存任务数据，使用回溯法构建任务树并保存在后台数据库中．同时，设计并实现了平台中服务器端与客户端的应用层通信协议UPDP（Unprocessed Packet Download Protocol）和PPUP（Processed Packet Upload Protocol）．本文进一步讨论了如何利用TT—DCP求解Mesh网络连通性问题，并给出了处理结果．TT—DCP可以用来求解生物计算中的多序列比对、motif查找等问题．     

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．     

Admission control and scheduling in simple series parallel networksusing fuzzy logic

Two outstanding problems of admission control and scheduling in networks with three and two workstations, respectively, are solved using fuzzy logic. Neither problem has been tackled up until now analytically, whereas the fuzzy approach provides computational solutions. In the first case, we have one workstation with two parallel ones. A reward is earned whenever the first stage accepts a customer and a holding cost is incurred by a customer in queue in the second stage. The class of customer to be next served by the first stage is dynamically selected so as to maximize an average benefit over an infinite horizon. In the second case, there are two parallel servers and three arrival processes generated by independent Poisson streams. Each server has its own queue and receives customers from its own arrival stream. A third arrival stream consists of customers with resource demand on both servers. Each customer pays a holding cost per unit time in the system. Again, the scheduling policy is specified which minimizes the average cost. The fuzzy models are new in this context and tackle computationally problems for which we have not analytical solutions     

Analytical and experimental evaluation of cluster-based network servers

In this paper we use analytic modeling and simulation to evaluate network servers implemented on clusters of workstations. More specifically, we model the potential benefits of locality-conscious request distribution within the cluster and evaluate the performance of a cluster-based server (called L2S) we designed in light of our experience with the model. Our most important modeling results show that locality-conscious distribution on a 16-node cluster can increase server throughput with respect to a locality-oblivious server by up to 5-fold, depending on the average size of the files requested and on the size of the server's working set. Our simulation results demonstrate that L2S achieves throughput that is within 28% of the full potential of locality-conscious distribution on 16 nodes, outperforming and significantly outscaling the best-known locality-conscious server. Based on our results and on the fact that the files serviced by network servers are becoming larger and more numerous, we conclude that our locality-conscious network server should prove very useful for its performance, scalability, and availability properties.