基于HPJava集群系统的环境搭建与性能分析

Bcwulf集群系统是基于广泛应用的高性能网络环境的由一些微机组成的系统,它可以运行于很多操作系统,如Linux、Windows.Java在作为科学与工程计算语言方面,并没有显著的缺点,却有一些明显的优点.随着Java编译技术的进步,用户会发现用Java编写新应用程序将变得更有吸引力.HPJava语言作为一种支持科学和并行计算的Java新扩展语言,尤其适合大型的并行编程和分布式存储的计算机.HPJava是用Java来实现科学和并行编程的环境,它是基于Java语言的扩充.主要介绍了HPJava在Ljnux系统下构建集群的方法,并用矩阵相乘算法对该系统进行了性能分析.     

基于Linux的PC集群系统的构建

并行计算在各个领域的应用越来越广泛,基于Linux的PC集群系统是一个廉价、高效的并行计算系统。在实验室网络环境下,使用多台普通计算机完成了集群的构建,提供了软件的详细配置过程,为在集群上进行并行编程提供了一个实际的软硬件环境。     

基于Docker的MPI和OpenMP混合编程

针对当前搭建集群并行系统复杂且耗时等问题,提出基于Docker搭建并行系统。介绍轻量级虚拟化技术Docker的核心概念和基本架构,并基于Docker技术在Linux平台上搭建集群并行开发环境。简要阐述并行计算的思想,叙述MPI和OpenMP并行计算的基本概念和特点,针对矩阵并行乘法的算法建立MPI和OpenMP的混合编程模型,并给出混合编程模型与MPI并行编程模型以及OpenMP并行编程模型的性能对比,分析出现差异的原因。基于该混合编程模型比较Docker与传统物理机两者搭建的并行系统的并行效率。     

Android平台Java和C++混合编程实现

Android是基于Linux的移动操作系统,主要使用于智能手机和平板电脑等移动设备,它采用的是分层架构框架,包括:应用程序层、应用程序框架层、系统运行库层、Linux内核层,其中应用程序层是使用Java语言编写的.以Eclipse为开发环境,在Android-sdk-4.2.2和Android-ndk-r10基础上实现了Java和C++的混合编程,用Java实现应用程序UI操作部分,用C++实现图像处理、算法等运算量大的部分,这样整个应用程序的执行效率就会得到改善和提高.     

基于Linux的PC集群

本文简单介绍了基于Linux的PC集群的特点,建立,以及在之上用MPI编程接口实现并行程序设计的方法。     

应用GPU集群加速计算蛋白质分子场

针对生物化学计算中采用量子化学理论计算蛋白质分子场所带来的巨大计算量的问题,搭建起一个GPU集群系统,用来加速计算基于量子化学的蛋白质分子场.该系统采用消息传递并行编程环境(MPI)连接集群各结点,以开放多线程OpenMP编程标准作为多核CPU编程环境,以CUDA语言作为GPU编程环境,提出并实现了集群系统结点中GPU和多核CPU协同计算的并行加速架构优化设计.在保持较高计算精度的前提下,结合MPI,OpenMP和CUDA混合编程模式,大大提高了系统的计算性能,并对不同体系和规模的蛋白质分子场模拟进行了计算分析.与相应的CPU集群、GPU单机和CPU单机计算方法对比,该GPU集群大幅度地提高了高分辨率复杂蛋白质分子场模拟的计算效率,比CPU集群的平均计算加速比提高了7.5倍.     

Java连接数据库SQL Server 2005

Java是全球使用广泛的一门网络编程语言,当今许多系统都是用Java语言进行编写的;SQL Server 2005是Microsoft公司推出的大型数据库系统,现在在一些大中型系统中有着广泛的使用,它的编程接口非常丰富、易用,提供了JDBC编程接口。在基于Java的软件系统中通过加载JDBC驱动和相关jar包,既可以实现在Java编程中连接SQL Server,也可通过连接池来连接SQL Server数据库。     

基于Linux的PC集群

本文简单介绍了基于Linux的PC集群的特点，建立，以及在之上用MPI编程接口实现并行程序设计的方法。     

集群的生命力

集群技术发展迅速 IA服务器集群是伴随着计算机芯片技术、网络技术、集成技术和Linux的快速发展而出现的新产品。集群是一个复杂的系统,由于IA服务器集群是基于Linux操作系统平台的集群高性能并行计算机,因此它更像是计算机。     

基于MPICH的Beowulf集群系统构建与性能评测

Beowulf集群系统是基于广泛应用的高性能网络环境的由一些微机组成的系统,它可以运行于很多操作系统如Linux、Windows。论文主要介绍了如何在Linux操作系统下构建Beowulf集群系统的方法,并利用矩阵相乘算法对该系统进行了系统性能测试。     

Runtime support for scalable programming in Java

The paper research is concerned with enabling parallel, high-performance computation—in particular development of scientific software in the network-aware programming language, Java. Traditionally, this kind of computing was done in Fortran. Arguably, Fortran is becoming a marginalized language, with limited economic incentive for vendors to produce modern development environments, optimizing compilers for new hardware, or other kinds of associated software expected of by today’s programmers. Hence, Java looks like a very promising alternative for the future. The paper will discuss in detail a particular environment called HPJava. HPJava is the environment for parallel programming—especially data-parallel scientific programming—in Java. Our HPJava is based around a small set of language extensions designed to support parallel computation with distributed arrays, plus a set of communication libraries. A high-level communication API, Adlib, is developed as an application level communication library suitable for our HPJava. This communication library supports collective operations on distributed arrays. We include Java Object as one of the Adlib communication data types. So we fully support communication of intrinsic Java types, including primitive types, and Java object types.     

智能卡的研究与发展

综述了智能卡及ＪＡＶＡ卡的相关技术,智能ＩＣ卡由硬件和操作系统组成 ,可理解成一个计算机系统,智能ＩＣ卡有着完善的安全技术体制,安全性是其最大的特点,近年来,Ｊａｖａ技术与智能卡技术的结合产生了Ｊａｖａ卡,Ｊａｖａ卡是一种新型的智能卡,它基于Ｊａｖａ语言和Ｊａｖａ卡虚拟机ＪＣＶＭ（Ｊａｖａ Ｃａｒｄ Ｖｉｒｔｕａｌ Ｍａｃｈｉｎｅ）,是智能卡发展的方向。     

An evaluation of Java implementations of message‐passing

As an objected‐oriented programming language and a platform‐independent environment, Java has been attracting much attention. However, the trade‐off between portability and performance has not spared Java. The initial performance of Java programs has been poor, due to the interpretive nature of the environment. In this paper we present the communication performance results of three different types of message‐passing programs: native, Java and native communications, and pure Java. Despite concerns about performance and numerical issues, we believe the obtained results confirm that high‐performance parallel computing in Java is possible, as the technology matures and the approach is pragmatic.Copyright © 2000 John Wiley & Sons, Ltd.     

Editorial: Java for computational science and engineering – simulation and modeling

We are pleased to present a set of papers discussing the role of Java in Science and Engineering Simulation. These were presented at a small workshop with 45 participants at Syracuse on 16-17 December 1996. This was very successful, and a follow-up event will be sponsored by ACM in Las Vegas on 21 June 1997. The growing interest in this field is also supported by an email discussion list and other materials collected at the web site http://www.npac.syr.edu/projects/javaforcse. Java and Web technology can be used in many areas of science and engineering computation. These include sophisticated user interfaces and coarse-grain integration of different modules in complex meta-applications. However, also interesting (and controversial) is perhaps the use of Java as the language used for the computationally intense parts of a scientific code. All these areas were discussed at the workshop, with promising initial results and studies reported in each case. Again applications were described both for large-scale event-driven and time-stepped simulations and also for smaller client-side applets aimed at education. The appeal of Java as a simulation language includes its object-oriented characteristics, elegant applet software distribution model and natural support of graphical user interfaces. There are also non-technical reasons to think Java will be very important. In particular, one expects children to learn Java naturally as part of their Web experiences. On entering University, I find it hard to believe that many will be willing to switch from Java to Fortran77 or Fortran90. The papers in this issue fall into five areas. The first paper (‘Java for parallel computing and as a general language for scientific and engineering simulation and modeling’ by Geoffrey C. Fox and Wojtek Furmanski) is a general overview and the next three (‘Optimizing Java bytecodes’ by Michał Cierniak an Wei Li; ‘Optimizing Java: theory and practice’ by Zoran Budimlic and Ken Kennedy; ‘Technologies for ubiquitous supercomputing: a Java interface to the Nexus communication system’ by Ian Foster, George K. Thiruvathukal and Steven Tuecke) describe base Java technology from optimized compilation to linkage with communication infrastructure. The next two papers (‘Java simulations for physics education’ by Simeon Warner, Simon Catterall and Edward Lipson; ‘Using Java and JavaScript in the Virtual Programming Laboratory: a Web-based parallel programming environment’ by Kivanc Dincer and Geoffrey C. Fox) describe uses of Java in both science and computer science education. Then we have two papers (‘Java's role in distributed collaboration by Marina Chen and James Cowie’; ‘Java enabling collaborative education, health care, and computing’ by Lukasz Beca, Gang Cheng, Geoffrey C. Fox, Tomasz Jurga, Konrad Olszewski, Marek Podgorny, Piotr Sokolowski and Krzysztof Walczak) centred on the fascinating field of collaboration. The last six papers study the critical area of parallel and distributed computing in Java. These discuss world-wide computing (‘SuperWeb: research issues in Java-based global computing’ by Albert D. Alexandrov, Maximilian Ibel, Klaus E. Schauser and Chris J. Scheiman), large-scale software integration with Java servers (‘WebFlow – a visual programming paradigm for Web/Java based coarse grain distributed computing’ by Dimple Bhatia, Vanco Burzevski, Maja Camuseva, Geoffrey Fox, Wojtek Furmanski and Girish Premchandran) and mobility (‘Resource-aware metacomputing’ by Anurag Acharya, M. Ranganathan and Joel Saltz). These three distributed computing studies are contrasted with three on parallel computing: ‘Automatically exploiting implicit parallelism in Java’ by Aart J. C. Bik and Dennis B. Gannon on shared memory; ‘SPMD programming in Java’ by Susan Flynn Hummel, Ton Ngo and Harini Srinivasan on the SPMD style, and ‘Experiments with “HP Java”’ by Bryan Carpenter, Yuh-Jye Chang, Geoffrey Fox, Donald Leskiw and Xiaoming Li on classic distributed memory data parallelism. Currently, it appears that Java promises the computational scientist programming environments which have both attractive user interfaces and high-performance execution. An important purpose of the first workshop and the follow-up events is to get a broad input and study of the issues in this field so that we can guide the rapidly moving Java juggernaut to be maximally effective for scientific and engineering computation. © 1997 John Wiley & Sons, Ltd.     

基于龙芯2号的Java虚拟机的移植与优化

Java语言作为一种跨平台的编程语言在企业应用开发、桌面应用开发及嵌入式开发上获得了广泛的应用。为了在龙芯上运行Java程序,将Sun HotSpot Java虚拟机移植到了Linux/龙芯2上,该文描述了移植过程中的主要工作、遇到的问题及解决的方法和优化工作。     

Java技术在嵌入式系统中的作用探究简

Java语言是在C＋＋语言的基础上来进行改变而成的,其是属于一种新型的计算机编程语言,在计算机技术的发展过程中,Java语言逐渐得到了广泛的应用,Java技术不但是一种编程语言,更是一个开发平台。Java技术在使用过程中具有较高的安全性、可移植性、稳定性及通用性,因此在嵌入式系统中有广泛的应用。本文通过Java技术、Java卡、J2ME的介绍,来分析Java技术在嵌入式系统中具有的作用。     

Dalvik虚拟机进程模型分析

Android手机操作系统是Google于2008年推出的智能手机操作系统,它的所有应用都是基于Java语言的,它的类Java虚拟机Dalvik提供了所有应用的运行时环境。Dalvik是一个面向Linux作为嵌入式操作系统设计的虚拟机,尤其是它的面向进程的设计,充分利用了Linux进程管理的特点。介绍了Dalvik所依赖的基础,即Linux操作系统内核中进程管理的一些特性和传统Java程序对进程的控制;进而论述了Dalvik的进程模型的特点,从API和本地代码两个层面具体阐述了进程运行、创建和之间通信的部分细节。文中旨在为Dalvik的研究和应用提供参考。     

Linux下的Oracle编程技术

本文探讨了在Linux操作系统下用C和Java语言访问Oracle数据库的几种方法,通过实例源代码的形式介绍了ProC、JDBC和SQLJ等关键技术的简单原理以及在Oracle数据库编程中的实际应用。     

The Hydra Parallel Programming System

The Hydra Parallel Programming System, a new parallel language extension to Java, and its supporting software are described. It is a fairly simple yet powerful language designed to address a number of areas that have not received much attention. One of these areas is the recompilation of parallel programs at runtime to allow a parallel program to adapt to the architecture it is executing on. The first version of this software system focuses on smaller Symmetric Multiprocessing and compatible architectures which are becoming more common. This particular class of machines has a great need for more options in the area of parallel programming among the vastly popular Java language programmers. Hydra programs will run as sequential Java on machines that do not have the parallel support or do not have an implemented Hydra runtime system without requirement of any modifications to the program. This paper describes the language, compares it with other languages (specifically with JOMP, an OpenMP implementation for Java), presents a brief discussion on compiling and executing Hydra programs, presents some sample benchmarks and their performance on three platforms, and concludes with a discussion of issues and future directions for Hydra. Copyright © 2007 John Wiley & Sons, Ltd.