一个实用的并行/分布程序设计工具PJVM

ＰＪＶＭ（ＰａｒａｌｅｌＪａｖａＶｉｒｔｕａｌＭａｃｈｉｎｅ）采用扩充Ｊａｖａ语言功能的方法，提供了基于分布式共享存储器的编程接口ＤＳＭ（ＤｉｓｔｒｉｂｕｔｅｄＳｈａｒｉｎｇＭｅｍｏｒｙ）和基于消息传递的编程接口ＭＰＩ（ＭｅｓｓａｇｅＰａｓｉｎｇＩｎｔｅｒｆａｃｅ），用户可以利用Ｊａｖａ语言和扩充的两个编程接口，方便地设计在异构环境下运行的并行／分布程序。     

PVM应用移植到MPI问题的探讨

消息传递方式是广泛应用于一些并行机,特别是分布存储并行机的一种模式。ＰＶＭ（ＰａｒａｌｌｅｌＶｉｒｔｕａｌＭａｃｈｉｎｅ）和ＭＰＩ（ＭｅｓｓａｇｅＰａｓｓｉｎｇＩｎｔｅｒｆａｃｅ）都是目前是广受欢迎的基于消息传递的并行程序库,其中ＰＶＭ的消息传递接口,因其简单性,而没有给用户最大的灵活性以实现最佳的性能：为此,消息传递标准的讨论会工作组制定了消息传递接口ＭＰＩ标准,为ＰＶＭ实现最佳性能提供了可能。该文通过对ＰＶＭ和ＭＰＩ的比较,指出了从ＰＶＭ应用移植到ＭＰＩ应用时有利的方面和潜在的缺陷。如果一个应用程序能避开这些缺陷的影响,那么它就能够从移植中提高通信的性能,从而提高其分布式计算的性能。     

基于消息传递的并行计算环境:MPI与PVM的比较

本文对在分布式计算中广泛应用的二种并行计算环境ＭＰＩ（Ｍｅｓｓａｇｅ Ｐａｓｓｉｎｇ Ｉｎｔｅｒｆａｃｅ）和ＰＶＭ（Ｐａｒａｌｌｅｌ Ｖｉｒｔｕａｌ Ｍａｃｈｉｎｅ）进行了比较。从ＭＰＩ和ＰＶＭ的设计思想出发,在可移植性、任务控制和分配、资源管理、容错、安全通信的上下文和多线程、通信方式、名字服务和消息句柄八个方面分析了它们各自的功能特点。     

蒙特卡罗中子-光子输运程序MCNP的并行化

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Sony Chooses Engineous Software for Its Home Electronics Products' Production Process Improvements

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可预测扩展并行性能的并行程序设计模型

ＢＳＰ（Ｂｕｌｋ－Ｓｙｎｃｈｒｏｎｏｕｓ）模型是独立于并行体系结构的,即可作为并行计算模型又可看作并地程序设计模型,该模型使程序员在算法设计阶段和编程调试阶段可精确地分析和预测并行程序性能。ＢＳＰ程序可移植性强,可在多种并行系统发ＰＶＭ,ＭＰＩ等上实现。     

Sun提供XML语言分析选项包JAXP的Java应用编程接口 JAXP的推出是XML技术与Java2平台结合的第一步

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运用JSP技术开发动态网站

相信很多朋友对Ｍｉｃｒｏｓｏｆｔ的ＡＳＰ技术比较熟悉,ＡＳＰ技术可以在静态ＨＴＭＬ页面中嵌入由服务器运行的代码,并将代码运行的结果作为主页内容发送给客户机,从而实现了眼务器与客户机的真正的交互,为创建动态网站提供了方便有效的途径。在Ｍｉｃｒｏｓｏｆｔ的ＡＳＰ技术取得了成功之后,Ｓｕｎ公司正式发布了 ＪＳＰ（Ｊａｖａｓｅｒｖｅｒ ＰａｓｅｓＴＭ）规范,这种新的Ｗｅｂ开发技术很快引起了人们的关注。ＪＳＰ为创建高度动态的Ｗｅｂ应用提供了一个独特的开发环境。按照Ｓｕｎ公司的说法,ＪＳＰ能够适应市场上包括 …     

Nested parallelism for multi-core HPC systems using Java

Since its introduction in 1993, the Message Passing Interface (MPI) has become a de facto standard for writing High Performance Computing (HPC) applications on clusters and Massively Parallel Processors (MPPs). The recent emergence of multi-core processor systems presents a new challenge for established parallel programming paradigms, including those based on MPI. This paper presents a new Java messaging system called MPJ Express. Using this system, we exploit multiple levels of parallelism–messaging and threading–to improve application performance on multi-core processors. We refer to our approach as nested parallelism. This MPI-like Java library can support nested parallelism by using Java or Java OpenMP (JOMP) threads within an MPJ Express process. Practicality of this approach is assessed by porting to Java a massively parallel structure formation code from Cosmology called Gadget-2. We introduce nested parallelism in the Java version of the simulation code and report good speed-ups. To the best of our knowledge it is the first time this kind of hybrid parallelism is demonstrated in a high performance Java application.     

MPI并行编程环境的研究

以RISC工作站或高档微机通过LAN连接的机群系统已经成为并行计算的主流技术，研究适应机群系统的并行编程环境自然重要起来。在众多的并行编程环境中，应用较为广泛的有消息传递接口(MPI)标准和并行虚拟机(PVM)环境。本文重点分析了MPI编程环境，并出给了MPI并行程序设计的基本方法。     

网络环境中MPI和PVM的分析与比较

消息传递接口(MessagePassingInterface,MPI)和并行虚拟机(ParallelVirtualMachine,PVM)是两种广泛应用的网络分布式并行计算环境。论文首先介绍了消息传递接口和并行虚拟机两者各自的起源和特点,然后在此基础上从可移植性、点对点通信、集体通信、资源管理和容错能力等多方面分析和比较了这两者的功能特点。     

Jcluster: an efficient Java parallel environment on a large‐scale heterogeneous cluster

In this paper, we present Jcluster, an efficient Java parallel environment that provides some critical services, in particular automatic load balancing and high‐performance communication, for developing parallel applications in Java on a large‐scale heterogeneous cluster. In the Jcluster environment, we implement a task scheduler based on a transitive random stealing (TRS) algorithm. Performance evaluations show that the scheduler based on TRS can make any idle node obtain a task from another node with much fewer stealing times than random stealing (RS), which is a well‐known dynamic load‐balancing algorithm, on a large‐scale cluster. In the performance aspects of communication, with the method of asynchronously multithreaded transmission, we implement a high‐performance PVM‐like and MPI‐like message‐passing interface in pure Java. The evaluation of the communication performance is conducted among the Jcluster environment, LAM‐MPI and mpiJava on LAM‐MPI based on the Java Grande Forum's pingpong benchmark. Copyright © 2005 John Wiley & Sons, Ltd.     

MPI集群通信技术浅析

简要介绍了集群系统,指出其用于并行计算的工作原理,重点介绍MPI并行环境及其通信技术,并分析了MPI并行程序中的基本模式及其采用的通信技术。最后对构建MPI并行环境的集群系统进行了展望。     

曙光机群系统并行调试器的设计与实现

介绍了为曙光机群系统设计实现的并行调试器DCDB。DCDB同时支持调试MPI或PVM、C或Fortran的并行应用程序，实现了记录／重放并行调试功能，支持循环调试，解决了并行调试时并行程序的不确定性问题。DCDB采用Client／server／Client结构，具有友好的图形用户界面，系统主要采用Java语言开发，具有良好的可移植性和可扩展性。     

VCluster: a thread‐based Java middleware for SMP and heterogeneous clusters with thread migration support

Clusters, composed of symmetric multiprocessor (SMP) machines and heterogeneous machines, have become increasingly popular for high‐performance computing. Message‐passing libraries, such as message‐passing interface (MPI) and parallel virtual machine (PVM), are de facto parallel programming libraries for clusters that usually consist of homogeneous and uni‐processor machines. For SMP machines, MPI is combined with multithreading libraries like POSIX Thread and OpenMP to take advantage of the architecture. In addition to existing parallel programming libraries that are in C/C++ and FORTRAN programming languages, the Java programming language presents itself as another alternative with its object‐oriented framework, platform neutral byte code, and ever‐increasing performance. This paper presents a new parallel programming model and a library, VCluster, which implements this model. VCluster is based on migrating virtual threads instead of processes to support clusters of SMP machines more efficiently. The implementation uses thread migration, which can be used in dynamic load balancing. VCluster was developed in pure Java, utilizing the portability of Java to support clusters of heterogeneous machines. Several applications are developed to illustrate the use of this library and compare the usability and performance of VCluster with other approaches. Copyright © 2007 John Wiley & Sons, Ltd.     

Design and implementation of Java bindings in Open MPI

This paper describes the Java MPI bindings that have been included in the Open MPI distribution. Open MPI is one of the most popular implementations of MPI, the Message-Passing Interface, which is the predominant programming paradigm for parallel applications on distributed memory computers. We have added Java support to Open MPI, exposing MPI functionality to Java programmers. Our approach is based on the Java Native Interface, and has similarities with previous efforts, as well as important differences. This paper serves as a reference for the application program interface, and in addition we provide details of the internal implementation to justify some of the design decisions. We also show some results to assess the performance of the bindings.     

Parallel Implementation of 2-D Telegraphic Equation on MPI/PVM Cluster

In this paper, a parallel implementation of the Iterative Alternating Direction Explicit method by D’Yakonov (IADE-DY) to solve 2-D telegraphic problem on a distributed system using Message Passing Interface (MPI) and Parallel Virtue Machine (PVM) are presented. The parallelization of the program is implemented by a domain decomposition strategy. A Single Program Multiple Data (SPMD) model is employed for the implementation. The implementation is discussed in relation to means of the parallel performance strategies and analysis. The model enhances overlap communication and computation to avoid unnecessary synchronization, hence, the method yields significant speedup. The level of speedup observed from tables as the mesh increases are in the range of 5–10%. Improvement has been achieved by numbers of tables and figures in our experiment. We present some analyses that are helpful for speedup and efficiency. It is concluded that the efficiency is strongly dependent on the grid size, block numbers and the number of processors for both MPI and PVM. Different strategies to improve the computational efficiency are proposed.     

A comparative study of Java and C performance in two large‐scale parallel applications

In the 1990s the Message Passing Interface Forum defined MPI bindings for Fortran, C, and C++. With the success of MPI these relatively conservative languages have continued to dominate in the parallel computing community. There are compelling arguments in favour of more modern languages like Java. These include portability, better runtime error checking, modularity, and multi‐threading. But these arguments have not converted many HPC programmers, perhaps due to the scarcity of full‐scale scientific Java codes, and the lack of evidence for performance competitive with C or Fortran. This paper tries to redress this situation by porting two scientific applications to Java. Both of these applications are parallelized using our thread‐safe Java messaging system—MPJ Express. The first application is the Gadget‐2 code, which is a massively parallel structure formation code for cosmological simulations. The second application uses the finite‐domain time‐difference method for simulations in the area of computational electromagnetics. We evaluate and compare the performance of the Java and C versions of these two scientific applications, and demonstrate that the Java codes can achieve performance comparable with legacy applications written in conventional HPC languages. Copyright © 2009 John Wiley & Sons, Ltd.