一种实现并行计算的新主充技术—NOW

当前，在并行计算领域，ＮＯＷ正受到日益重视，国外很多学者和厂商对这一技术进行着研究和开发，并预言它将具有与ＭＰＰ一样的地位，主导今后并行计算技术的发展，本文对ＮＯＷ进行介绍，回答关于ＮＯＷ的几个问题，分析实现ＮＯＷ的关键所在，并对其发展前景进行展望，试图引起国内同行对这一新技术的关注。     

网络并行计算中矩阵QR分解的并行算法

随着高速网络技术（如ＡＴＭ）的出现,网络并行计算系统（ＮＯＷ）已成为并行处理的主要平台,由于它的高通信延迟,某些在并行机上实现的细粒度并行算法已不适合在该环境下运行。为此,有必要对算法重新进行任务划分,研究它在网络环境中的并行实现。基于这一点,本文对矩阵的ＱＲ分解提出了一种新的任务划分策略,并由此得到了它的一种粗粒度并行算法,实验结果表明,设计的并行算法在网络并行计算环境中具有较高的加速比。     

一种基于异构网络的NOW中的群通信模型

工作站网络（ＮＯＷ）作为一种新的并行计算结构越来越受到人们的重视。文中讨论了基于异构网络的ＮＯＷ中群通信问题，提出了一种群通信层次模型，较好地解决了异构网络环境中的群通信问题，其实现群通信的思想是将参与群通信操作的结点按它们所处的子网分成一个个基计算域，通过这些基计算域的并行操作来达到降低通信时延同时又不增加太多网络流量的目的，并且还可以在不同的子网中选择最合适的群通信实现，这一做法做全网面向过程     

工作站网络环境下的并行计算

当前工作站网络环境（ＮＯＷｓ）下高性能科学与工程计算是并行计算的一个热门话题，本文借助于ＬｏｇＰ并行计算模型，提出了一套新的效率评价准则，用于优化并行算法效率以达到最佳实现效果，揭示了影响算法并行效率发挥的关键因素，并从算法和程序设计角度提出了相应措施，探讨了急需解决的几个关键性问题，三个典型应用问题的数值实验结果文中给出。     

JAPS中通信支撑策略的比较

在分布式并行计算系统中,任务运行时支撑平台的功能和效率对并行执行的效果有着重要的影响,Ｊａｖａ言中的线程机制和ＲＭＩ机制为ＮＯＷ环境下的分布并行应用提供了高效的支持＾「１」。在基于Ｊａｖａ的自动并行编译系统ＪＡＰＳ＾「２」中,设计和实现了分别基于Ｊａｖａ ＲＭＩ和Ｓｏｃｋｅｔ通信支持策略的并行任务支撑平台ＰＴＳＰ;并比较了这两种通信策略对在ＮＯＷ环境下的分布式并行计算的支持能力和系统效率。     

基于ATM局域网的并行计算中的通信问题的研究

本文首先介绍了并行计算中的通信问题和ＡＴＭ局域网的特点，然后讨论了已有的关于以ＡＴＭ局域网为基础的ＮＯＷ环境中并行计算中的通信问题的研究。最后，指出了进一步应研究的问题及研究方法     

PON技术浅析

文章讨论了一种很有前途的光接入系统－ＰＯＮ。在描述了网络结构后对ＰＯＮ的几种成风方案（ＴＤＭ／ＴＤＭＡ、ＷＤＭ和ＳＣＭＡ）进行了分析，指出ＷＤＭ是ＰＯＮ系统升级的关键。最后着重从经济性的角度分析了ＰＯＮ的器件技术并对网络升级策略进行了讨论。     

一种并行计算K阶线性递归N方程组的新方法

一种并行计算Ｋ阶线性递归Ｎ方程组的新方法朱大铭，马绍汉，马军（山东大学计算机科学系、济南２５０１００）ＡＮＥＷＭＥＴＨＯＤＦＯＲＳＯＬＶＩＮＧＴＨＥＳＹＳＴＥＭＯＦＫ－ＴＨＯＲＤＥＲＬＩＮＥＡＲＲＥＣＵＲＲＥＮＣＥＥＱＵＡＴＩＯＮＳＩＮＰＡＲＡＬＬＥ...     

工作站网络下三对角方程组并行求解

考虑工作站网络（ＮＯＷｓ）中三对角线性方程组的并行求解，基于最小秩解耦算法与分布治之并行计算模式，并行最小秩解耦算法（ＰＭＲＤ）。它在计算过程中保持原矩阵的结构特征，数值稳定性高，本文给出算法的数值特征分析以及计算与通讯复杂性分析并与Ｍｅｈｒｍａｎｎ分治算比较，所有算法由ＰＶＭ软件系统实现并在工作站网络中测试。     

HPF—FORTRAN最新版本

ＨＰＦ（高性能ＦＯＲＴＲＡＮ）公布于１９９３年，是当今世界上ＦＯＲＴＲＡＮ语言的最新版本。本文系统地介绍了ＨＰＦ相对于以往ＦＯＲＴＲＡＮ版本（主要是ＦＯＲＴＲＡＮ９０）的新特点，并举出了一个程序实例，供并行计算技术的研究者以及工程技术人员参考。     

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.     

一种实用的并行计算模型

对于当前流行的工作站集群环境和各类并行机系统,文中提出了一种实用的并行计算模型,即基于LogGP的非独占异质同步模型NHBL（Nondedicated Heterogeneous Barrier LogGP）,它旨在反映具有异质性和非独占性的NOW计算环境对并行算法设计和分析的影响,然后用NHBL模型分析了PSRS算法在国家高性能计算中心（合肥）的工作站集群NHPCC-Cluster和曙光－1000MPP由的代价,并用实测结果进行了验证。     

High performance computing on networks of workstations through the exploitation of function parallelism

Network of workstations (NOW) has become a widely accepted form of high-performance parallel computing. As in conventional multicomputers, parallel programs running on such a platform are often written in an SPMD form to exploit data parallelism. Each workstation in a NOW is treated similarly to a processing element in a multicomputer system. However, workstations are far more powerful and flexible than the processing elements in conventional multicomputers. In this paper, we discuss how workstations in a NOW can be used to exploit more parallelism in an SPMD program, especially those induced from concurrent activities.     

"NOW"环境下电路并行仿真算法的研究和实现

针对电路并行仿真,基于求解对角分块结构非线性系统的并行方法,提出并实现了"NOW"(Network Of Workstations) 环境下的一个并行计算模型.主要分析了该算法的并行特性、同步条件及"NOW"环境并行性能关键影响因素.文中提出了一种启发式的静态、动态负载平衡算法,并在Linux平台下采用MPI消息库实现该并行模型.仿真结果表明该算法在"NOW"环境下能获得比串行算法较为可观的加速比.同时文中提出的负载平衡算法也比一些经典算法能更有效得平衡系统负载.     

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.     

Efficient Multiple Multicast on Heterogeneous Network of Workstations

In recent years, network of workstations/PCs (so called NOW) are becoming appealing vehicles for cost-effective parallel computing. Due to the commodity nature of workstations and networking equipment, LAN environments are gradually becoming heterogeneous. The diverse sources of heterogeneity in NOW systems pose a challenge on the design of efficient communication algorithms for this class of systems. In this paper, we propose efficient algorithms for multiple multicast on heterogeneous NOW systems, focusing on heterogeneity in processing speeds of workstations/PCs. Multiple multicast is an important operation in many scientific and industrial applications. Multicast on heterogeneous systems has not been investigated until recently. Our work distinguishes itself from others in two aspects: (1) In contrast to the blocking communication model used in prior works, we model communication in a heterogeneous cluster more accurately by a non-blocking communication model, and design multicast algorithms that can fully take advantage of non-blocking communication. (2) While prior works focus on single multicast problem, we propose efficient algorithms for general, multiple multicast (in which single multicast is a special case) on heterogeneous NOW systems. To our knowledge, our work is the earliest effort that addresses multiple multicast for heterogeneous NOW systems. These algorithms are evaluated using a network simulator for heterogeneous NOW systems. Our experimental results on a system of up to 64 nodes show that some of the algorithms outperform others in many cases. The best algorithm achieves completion time that is within 2.5 times of the lower bound.     

一种基于ATM的支持并行处理的高速通信机制

随着高速网络（如ＡＴＭ）的发展以及工作站性能的不断提高，工作站网络（ＮＯＷ）作为一种新型的并行计算结构越来越受到人们的重视。传统的传输协议和报文传递系统不能充分作为高速网的传输能力。本文提出一种基于ＡＴＭ的支持并行处理的高速通信机制ＨＰＭＰＡ。在ＨＰＭＰＡ中，可靠的端－端传输协议ＨＳＴＰ为并行应用提供高速可靠的数据传输，而不可靠的端－端传输协议ＵＴＰ则提供不可靠的高速数据报服务，以混合树结构为基础     

基于LAN的并行计算环境

文章给出厂一个这种模型的并行计算机系统，设计了一个简单的工作算法．并对该算法的性能进行了分析，最终发现影响并行计算的性能的主要因素——传输速度。为了提高其性能，必须对传输介质、传输设备和通信协议等进行改造。