An architecture for Java-based real-time distributed visualization

In this paper, we present a Java-based software architecture for real-time visualization that utilizes a cluster of conventional PCs to generate high-quality interactive graphics. Normally, a large multiprocessor computer would be needed for interactive visualization tasks requiring more processing power than a single PC can provide. By using clusters of PCs, enormous cost savings can be realized, and proprietary "high-end" hardware is no longer necessary for these tasks. Our architecture minimizes the amount of synchronization needed between PCs, resulting in excellent scalability. It provides a modular framework that can accommodate a wide variety of rendering algorithms and data formats, provided that the rendering algorithms can generate pixels individually and the data is duplicated on each PC. Demonstration modules that implement ray tracing, fractal rendering, and volume rendering algorithms were developed to evaluate the architecture. Results are encouraging-using 15 PCs connected to a standard 100 Megabit/s Ethernet network, the system can interactively render simple to moderately complex data sets at modest resolution. Excellent scalability is achieved; however, our tests were limited to a cluster of 15 PCs. Results also demonstrate that Java is a viable platform for real-time distributed visualization.     

构建基于Windows和MPI的Beowulf并行计算系统

利用普通微机构建并行计算集群(常称为Beowulf系统),能够以低廉的价格获得强大的计算能力。文章介绍了利用16台微机构建一套Beowulf并行计算系统,节点微机上运行Windows2000操作系统,采用MPI(Message-Passing-Interface)的MPICH最新版本:MPICH.NT1.2.3作为并行计算的支撑环境,并以100Mbps高速交换式以太网作为互连网络。通过编制的并行计算程序对该Beowulf系统进行了并行效率的实际测试,测试结果表明该Beowulf系统能够达到非常高的并行加速比和并行效率。     

On Exploiting Heterogeneity for Cluster Based Parallel Multithreading Using Task Duplication

Triggered by the ever increasing advancements in processor and networking technology, a cluster of PCs connected by a high-speed network has become a viable and cost-effective platform for the execution of computation intensive parallel multithreaded applications. However, there are two research issues to be tackled in the scheduling problem for PC cluster computing: (1) how to reduce the communication overhead of executing a multithreaded application on the cluster; (2) how to exploit the heterogeneity, which is unavoidable in an evolving PC cluster, for the application. In this paper, we propose to use a duplication based approach in scheduling tasks/threads to a heterogeneous cluster of PCs. In duplication based scheduling, critical tasks are redundantly scheduled to more than one machine, in order to reduce the number of inter-task communication operations. The start times of the succeeding tasks are also reduced. The task duplication process is guided given the system heterogeneity in that the critical tasks are scheduled or replicated in faster machines. The algorithm has been implemented in our experimental application parallelization system for generating multithreaded parallel code executable on a cluster of Pentium PCs. Our experiments, using three numerical applications and one protocol processing kernel (multithreading per request), have indicated that heterogeneity of PC cluster is indeed useful for optimizing the execution of parallel multithreaded programs.     

PC机群的建立及在数值计算中的研究与应用

文中给出了一个利用SSH（Secure Shell）技术组建机群环境的新方案，并分析了PC机群的系统环境和网络并行软件PVM和MPI的主要功能，指出了各自的优缺点。分析设计了DAC并行算法，利用机群求解大规模线性方程组。数值结果表明算法收到较好的效果。PC机群能满足求解犬规模、高精度问题的需要，推动数值计算进一步发展。     

基于MPI并行计算的信号稀疏分解

在研究信号稀疏分解理论及其最常用的匹配追踪算法的基础上,针对MP算法存在的计算量过大的问题,提出一种基于并行计算系统实现信号稀疏分解的方法。该方法利用8台微机,采用MPI消息传递机制,以100 M高速以太网作为互联网络,构建了一套Beowulf 并行计算系统,在此系统上通过编制并行程序来实现MP算法。实际测试表明这种方法具有很高的并行计算效率,分解时间从单机75 min左右下降到8机并行11 min左右,大大提高了信号稀疏分解的速度。     

SCIPVM: Parallel distributed computing on SCI workstation clusters

Workstation and PC clusters interconnected by SCI (scalable coherent interface) are very promising technologies for high-performance cluster computing. Using commercial SBus to SCI interface cards and system software and drivers, a two-workstation cluster has been constructed for initial testing and evaluation. The PVM system has been adapted to operate on this cluster using both raw channel and shared-memory access to the SCI interconnect, and preliminary communications performance tests have been carried out. To achieve mutual exclusion in accessing shared-memory segments, two protocols were used. Our preliminary results indicate that communications throughput in the range of 17.7 Mbytes/s, and round-trip latencies of 80 μs using the first and 140 μs using the second protocol, can be obtained on SCI clusters. These figures are significantly better (by a factor of 2 to 4) for small and large messages than those attainable on Fast Ethernet LANs. Since these performance results are very encouraging, we expect that, in the very near future, SCI networks will be capable of delivering several tens of Mbytes/s bandwidth and a few tens of microseconds latencies, and will significantly enhance the viability of cluster computing. Copyright © 1999 John Wiley & Sons, Ltd.     

用于并行计算的PC机群

随着计算机技术的高速发展，使用机群进行并行计算也越来越流行，尤其是利用工作站机群进行并行计算已经十分普遍。但使用ＰＣ机群进行并行计算的系统还很少，这种ＰＣ机群由一组ＰＣ机（４８６，５８６）通过网络互连组成。本文介绍现有的几个ＰＣ机群和我们研制的一个ＰＣ机群计算环境     

高效且可验证的多授权机构属性基加密方案

移动云计算对于移动应用程序来说是一种革命性的计算模式,其原理是把数据存储及计算能力从移动终端设备转移到资源丰富及计算能力强的云服务器.但是这种转移也引起了一些安全问题,例如,数据的安全存储、细粒度访问控制及用户的匿名性.虽然已有的多授权机构属性基加密云存储数据的访问控制方案,可以实现云存储数据的保密性及细粒度访问控制;但其在加密和解密阶段要花费很大的计算开销,不适合直接应用于电力资源有限的移动设备;另外,虽然可以通过外包解密的方式,减少解密计算的开销,但其通常是把解密外包给不完全可信的第三方,其并不能完全保证解密的正确性.针对以上挑战,本文提出了一种高效的可验证的多授权机构属性基加密方案,该方案不仅可以降低加密解密的计算开销,同时可以验证外包解密的正确性并且保护用户隐私.最后,安全分析和仿真实验表明了方案的安全性和高效性.     

Heterogeneous parallel and distributed computing

Heterogeneous network-based distributed and parallel computing is gaining increasing acceptance as an alternative or complementary paradigm to multiprocessor-based parallel processing as well as to conventional supercomputing. While algorithmic and programming aspects of heterogeneous concurrent computing are similar to their parallel processing counterparts, system issues, partitioning and scheduling, and performance aspects are significantly different. In this paper, we discuss the evolution of heterogeneous concurrent computing, in the context of the parallel virtual machine (PVM) system, a widely adopted software system for network computing. In particular, we highlight the system level infrastructures that are required, aspects of parallel algorithm development that most affect performance, system capabilities and limitations, and tools and methodologies for effective computing in heterogeneous networked environments. We also present recent developments and experiences in the PVM project, and comment on ongoing and future work.     

Javelin: Parallel computing on the internet

Java offers the basic infrastructure needed to integrate computers connected to the Internet into a seamless distributed computational resource: an infrastructure for running coarse-grained parallel applications on numerous, anonymous machines. First, we sketch such a resource’s essential technical properties. Then, we present a prototype of Javelin, an infrastructure for global computing. The system is based on Internet software that is interoperable, increasingly secure, and ubiquitous: Java-enabled Web technology. Ease of participation is seen as a key property for such a resource to realize the vision of a multiprocessing environment comprising thousands of computers. Javelin’s architecture and implementation require participants to have access to only a Java-enabled Web browser. Experimental results are given in the form of a Mersenne Prime application and a ray-tracing application that run on a heterogeneous network of several parallel machines, workstations, and PCs. Two key areas of current research, fault-tolerance and scalability, are subsequently explored briefly.     

可证安全的CLPKC-to-IDPKC在线/离线异构签密方案

在线/离线签密不仅可以提高移动设备的计算效率,而且还可以保证数据的机密性和不可伪造性。异构密码环境下,需要考虑不同公钥密码环境之间的在线/离线签密问题。定义了从无证书密码体制到身份密码体制的在线/离线异构签密安全模型,并提出了具体的CLPKC-to-IDPKC在线/离线异构签密方案。方案执行签密运算时,不需要双线性对运算;执行解签密时,只需要2个双线性对运算。与已有在线/离线异构签密方案相比,在效率相当的情况下不存在证书管理问题,适合于计算能力受限的移动设备。通过安全性证明本文方案满足机密性和不可伪造性。最后的实验仿真分析了所提方案在线/离线签密和解签密的效率,该方案采用了独立系统参数,更适用于实际应用环境。     

基于MPICH2的高性能计算集群系统研究

目前在高等学校和科研机构中对于高性能计算的需求很大,而商业的超级计算机性能虽高但价格昂贵,同时这些单位又都拥有大量普通的PC机和网络设备。为了利用现有硬件资源获取高性能计算能力,文中研究了在PC机和Linux环境下构建基于MPICH2的高性能计算集群系统的方法,搭建了一个拥有16个节点的系统并利用高性能Linpack基准测试方法进行了性能测试。测试结果表明,这种构建高性能计算集群系统的方法切实可行,是低成本获取高性能计算能力的良好途径。     

Energy efficiency of dynamic management of virtual cluster with heterogeneous hardware

Cloud computing is an essential part of today’s computing world. Continuously increasing amount of computation with varying resource requirements is placed in large data centers. The variation among computing tasks, both in their resource requirements and time of processing, makes it possible to optimize the usage of physical hardware by applying cloud technologies. In this work, we develop a prototype system for load-based management of virtual machines in an OpenStack computing cluster. Our prototype is based on an idea of ‘packing’ idle virtual machines into special park servers optimized for this purpose. We evaluate the method by running real high-energy physics analysis software in an OpenStack test cluster and by simulating the same principle using the Cloudsim simulator software. The results show a clear improvement, 9–48 % , in the total energy efficiency when using our method together with resource overbooking and heterogeneous hardware.     

PVM与网络并行计算

松散耦合的异构型并行处理系统近年来又有较大的发展，这种只能支持粗粒度并行的计算环境，由于通讯硬件的更新和软件环境的开发，其性能已经能够与某些ＭＰＰ机相媲美，因而形成并行处理领域一个强有力的分支－网络计算，本文围绕ＰＶＭ，讨论网络计算的软件环境，概述其特色和发展，并与其它基于消息传递的软件环境相比较，最后预测ＰＶＭ未来可能面临的问题和发展方向。     

面向异构计算的高性能计算算法与软件

研发适应国产异构计算环境的高性能计算算法与软件是非常重要的课题,对我国高性能计算软件研发匹配高性能计算硬件高水平发展的速度具有重要意义.首先,简要介绍高性能计算应用软件的现状、趋势和面临挑战,并对几类典型高性能计算应用软件开展并行计算算法特征分析,涵盖了宇宙N体模拟、地球系统模式、计算材料相场动力学、分子动力学、量子计算化学和格点量子色力学等多个问题、尺度和领域.其次,讨论了面向国产异构计算系统的对策,提炼出若干典型应用算法和软件的共性问题,涉及核心算法、算法发展、优化策略等.最后,面向异构计算体系结构,对高性能计算算法与软件进行了总结.     

Public grid computing participation: An exploratory study of determinants

Using the Internet, “public” computing grids can be assembled using “volunteered” PCs. To achieve this, volunteers download and install a software application capable of sensing periods of low local processor activity. During such times, this program on the local PC downloads and processes a subset of the project's data. At the completion of processing, the results are uploaded to the project and the cycle repeats.     

Empirical analysis of overheads in cluster environments

In concurrent computing environments based on heterogeneous processing elements interconnected by general-purpose networks, several classes of overheads contribute to lowered performance. The most obvious limitations are network throughput and latency, but certain other factors also play a significant role. In an attempt to gain some insight into the nature of these overheads, and to propose strategies to alleviate them, empirical measurements of native communication performance as well as application execution performance were conducted, using the PVM network computing system. These experiments and our analyses have identified load imbalance, the parallelism model adopted, communication delay and throughput, and within-host overheads as the primary factors affecting performance in cluster environments. Interestingly, we find that agenda parallelism and load balancing strategies contribute significantly more to better performance than improved communications or system tuning. Drawing general conclusions on how these inefficiencies may be overcome is inadvisable because of the tremendous variability of many parameters in general purpose network environments; we therefore propose several potential approaches, including model selection criteria, partitioning strategies, and software system heuristics, to reduce overheads and enhance performance in network based environments.     

基于随机背包公钥密码的攻击

针对基于随机背包公钥密码方案,根据方案不同参数分别给出了恢复私钥攻击和恢复密文中明文的格攻击,并通过计算实例验证格攻击有效。因此证明了基于随机背包中公钥方案是不安全的。     

基于PSO算法的神经网络集成入侵检测系统

在系统结构上提出了一种多检测器并行的智能机群入侵检测系统模型，系统中每一个检测器是一个神经网络集成分类检测器，由多个PC组成，以提高系统响应速度。采用两次粒子群优化算法选择性集成神经网络集，提高了神经网络集成检测器的预测精度。程序设计采用PVM并行方式实现。