Visual Supercomputing: Technologies, Applications and Challenges

If we were to have a Grid infrastructure for visualization, what technologies would be needed to build such an infrastructure, what kind of applications would benefit from it, and what challenges are we facing in order to accomplish this goal? In this survey paper, we make use of the term ‘visual supercomputing’ to encapsulate a subject domain concerning the infrastructural technology for visualization. We consider a broad range of scientific and technological advances in computer graphics and visualization, which are relevant to visual supercomputing. We identify the state‐of‐the‐art technologies that have prepared us for building such an infrastructure. We examine a collection of applications that would benefit enormously from such an infrastructure, and discuss their technical requirements. We propose a set of challenges that may guide our strategic efforts in the coming years.     

SuperWeb: research issues in Java-based global computing

The Internet, in particular the World Wide Web, continues to expand at an amazing pace. We propose a new infrastructure, SuperWeb, to harness global resources, such as CPU cycles or disk storage, and make them available to every user on the Internet. SuperWeb has the potential for solving parallel supercomputing applications involving thousands of co-operating components on the Internet. However, we anticipate that initial implementations will be used inside large organizations with large heterogeneous intranets. Our approach is based on recent advances in Internet connectivity and the implementation of safe distributed computing realized by languages such as Java. Our SuperWeb prototype consists of brokers, clients and hosts. Hosts register a fraction of their computing resources (CPU time, memory, bandwidth, disk space) with resource brokers. Clients submit tasks that need to be executed. The broker maps client computations onto the registered hosts. We examine an economic model for trading computing resources, and discuss several technical challenges associated with such a global computing environment. © 1997 John Wiley & Sons, Ltd.     

网络计算与IPv6

网格计算、P2P(peer to peer)计算与普适计算都是近几年出现的新的网络计算模式，这些新的计算模式与传统的Web计算模式相比体现出不同的特征，同时都受到通信技术与通信基础设施的制约。以IPv6为核心协议的下一代互联网技术的发展，特别是IPv6充足的地址空间、简化的报头、网络节点的自动配置、邻居发现协议、增强的安全特征等，能够对这些新的网络计算模式起到进一步的推动与融合作用。     

Analysis and Provision of QoS for Distributed Grid Applications

Grid computing provides the infrastructure necessary to access and use distributed resources as part of virtual organizations. When used in this way, Grid computing makes it possible for users to participate in collaborative and distributed applications such as tele-immersion, visualization, and computational simulation. Some of these applications operate in a collaborative mode, requiring data to be stored and delivered in a timely manner. This class of applications must adhere to stringent real-time constraints and Quality-of-Service (QoS) requirements. A QoS management approach is therefore required to orchestrate and guarantee the timely interaction between such applications and services. We discuss the design and a prototype implementation of a QoS system, and demonstrate how we enable Grid applications to become QoS compliant. We validate this approach through a case study of an image processing task derived from a nanoscale structures application.     

A survey on approaches to gridification

The Grid shows itself as a globally distributed computing environment, in which hardware and software resources are virtualized to transparently provide applications with vast capabilities. Just like the electrical power grid, the Grid aims at offering a powerful yet easy‐to‐use computing infrastructure to which applications can be easily ‘plugged’ and efficiently executed. Unfortunately, it is still very difficult to Grid‐enable applications, since current tools force users to take into account many details when adapting applications to run on the Grid. In this paper, we survey some of the recent efforts in providing tools for easy gridification of applications and propose several taxonomies to identify approaches followed in the materialization of such tools. We conclude this paper by describing common features among the proposed approaches, and by pointing out open issues and future directions in the research and development of gridification methods. Copyright © 2007 John Wiley & Sons, Ltd.     

Internetworked graphics and the Web

Although the networking and computer graphics fields are considered to be distinct disciplines, they must begin to converge in order to support collaborative exploration and information visualization on the Internet and the World Wide Web. Telecommunication breakthroughs remove bottlenecks and provide new opportunities for interactive 3D graphics across globally interconnected, dissimilar networks. Multicast backbone tools, developed in the networking arena, provide desktop videoconferencing tools for sharing information visualization and virtual reality explorations. The Virtual Reality Modeling Language (VRML), developed in the computer graphics arena, supports the 3D display and fly-through of networked computing resources on the Internet. The computer graphics community considers VRML to be an interactive tool for exploring content on the Web. The telecommunications community calls it an application on the networking infrastructure. The authors define the concept of internetworked graphics to describe the future merger and dependencies of computer graphics applications and the telecommunications networking infrastructure     

广域网虚拟平台：网格计算和对等计算的融合

近几年，分布式计算领域出现了两个研究热点：网格计算(Grid Computing)和对等计算(PeertoPeer Computing)。网格计算和对等计算以不同的方法组织大规模分布式的资源，包括计算能力、存储资源和带宽等。两者的研究领域有一定的重叠，又有很好的互补性，融合将是必然趋势。我们构想了一个广域网虚拟平台，全世界的计算机连接成一个整体，任何人随时随地都可以得到所需的资源和服务。正是这一理想，驱动着网格计算和对等计算技术的快速进步。     

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.     

网格环境下的集群系统作业管理研究

网格计算已经逐渐形成一个重要的新领域。相对于传统的分布式计算，它的显著之处在于它能够共享网络上的各种资源，包括地理上分布的各种计算资源。PBS是广泛应用于并行计算机的作业管理系统，它可以按照用户定义的配置参数相对公平地为每个作业分配系统资源。但是在网格环境范围内对集群系统进行管理仍然是一门有待研究的课题。利用网格系统软件和集群系统管理软件，实现了一种在网格环境下对集群系统作业进行管理的方法。     

Web computing framework

In this paper an approach to provide Web-based framework for distributed execution of collaborative applications is presented. The work is part of a wider on-going project whose aim is to make computing resources, both hardware and software, available to Web users. The core of the system is the Web computing skeleton constructed from prefabricated Web-enabled components with the ability to open and maintain Internet connections and provide collaboration over the World Wide Web. A number of examples illustrate how Web presentation can be enriched with collaborative software using the Web computing framework.     

Distributed data mining patterns and services: an architecture and experiments

Distributed data mining implements techniques for analyzing data on distributed computing systems by exploiting data distribution and parallel algorithms. The grid is a computing infrastructure for implementing distributed high‐performance applications and solving complex problems, offering effective support to the implementation and use of data mining and knowledge discovery systems. The Web Services Resource Framework has become the standard for the implementation of grid services and applications, and it can be exploited for developing high‐level services for distributed data mining applications. This paper describes how distributed data mining patterns, such as collective learning, ensemble learning, and meta‐learning models, can be implemented as Web Services Resource Framework mining services by exploiting the grid infrastructure. The goal of this work was to design a distributed architectural model that can be exploited for different distributed mining patterns deployed as grid services for the analysis of dispersed data sources. In order to validate such an approach, we presented also the implementation of two clustering algorithms on the developed architecture. In particular, the distributed k‐means and distributed expectation maximization were exploited as pilot examples to show the suitability of the implemented service‐oriented framework. An extensive evaluation of its performance was provided. Copyright © 2011 John Wiley & Sons, Ltd.     

Autonomic oil reservoir optimization on the Grid

The emerging Grid infrastructure and its support for seamless and secure interactions is enabling a new generation of autonomic applications where the application components, Grid services, resources, and data interact as peers to manage, adapt and optimize themselves and the overall application. In this paper we describe the design, development and operation of a prototype of such an application that uses peer‐to‐peer interactions between distributed services and data on the Grid to enable the autonomic optimization of an oil reservoir. Copyright © 2005 John Wiley & Sons, Ltd.     

面向知识网格的本体学习研究

网格计算正在从单纯的面向大型计算的分布式资源共享发展为一种面向服务的架构,以实现透明而可靠的分布式系统集成。网格智能是指如何获取、预处理、表示和集成不同层次的网格服务(如HTML/XML/RDF/OWL文档、服务响应时间和服务质量等)的数据和信息,并最终转换为有用的智能(知识)。因为高层知识将在未来的网格应用起到越来越重要的作用,本体是知识网格实现的关键。文章提出了一种实现从Web文档中本体(半)自动构建的本体学习框架WebOntLearn,并讨论了本体学习中领域概念的抽取、概念之间关系的抽取和分类体系的自动构建等关键技术。     

Algorithms and the Grid

We review the impact of Grid Computing and Web Services on scientific computing, stressing the importance of the “data-deluge” that is driven by deployment of new instruments, sensors and satellites. This implies the need to integrate the naturally distributed data sources with large simulation engines offering parallel low latency communication and so to integrate parallel and Grid computing paradigms. We start with an overview of these and the evolving service architectures. We illustrate the identified areas of interest for Algorithms and the Grid with the specific example of SERVOGrid that supports earthquake science research. We comment on the appropriate messaging infrastructure for Grids and data assimilation and contrast it with MPI.     

A Science Driven Production Cyberinfrastructure��the Open Science Grid

This article describes the Open Science Grid, a large distributed computational infrastructure in the United States which supports many different high-throughput scientific applications, and partners (federates) with other infrastructures nationally and internationally to form multi-domain integrated distributed systems for science. The Open Science Grid consortium not only provides services and software to an increasingly diverse set of scientific communities, but also fosters a collaborative team of practitioners and researchers who use, support and advance the state of the art in large-scale distributed computing. The scale of the infrastructure can be expressed by the daily throughput of around seven hundred thousand jobs, just under a million hours of computing, a million file transfers, and half a petabyte of data movement. In this paper we introduce and reflect on some of the OSG capabilities, usage and activities.     

网格计算技术初探

网格计算被誉为是继Internet和Web之后的"第三个信息技术浪潮",有望提供下一代分布式应用和服务,对信息系统发展有着深远的影响.本文深入透析了网格计算技术的特点、历史和现状,给出了待解决的问题以及未来网格的标准问题,最后对全文进行了总结.     

GridBLAST: a Globus‐based high‐throughput implementation of BLAST in a Grid computing framework

Improvements in the performance of processors and networks have made it feasible to treat collections of workstations, servers, clusters and supercomputers as integrated computing resources or Grids. However, the very heterogeneity that is the strength of computational and data Grids can also make application development for such an environment extremely difficult. Application development in a Grid computing environment faces significant challenges in the form of problem granularity, latency and bandwidth issues as well as job scheduling. Currently existing Grid technologies limit the development of Grid applications to certain classes, namely, embarrassingly parallel, hierarchical parallelism, work flow and database applications. Of all these classes, embarrassingly parallel applications are the easiest to develop in a Grid computing framework. The work presented here deals with creating a Grid‐enabled, high‐throughput, standalone version of a bioinformatics application, BLAST, using Globus as the Grid middleware. BLAST is a sequence alignment and search technique that is embarrassingly parallel in nature and thus amenable to adaptation to a Grid environment. A detailed methodology for creating the Grid‐enabled application is presented, which can be used as a template for the development of similar applications. The application has been tested on a ‘mini‐Grid’ testbed and the results presented here show that for large problem sizes, a distributed, Grid‐enabled version can help in significantly reducing execution times. Copyright © 2005 John Wiley & Sons, Ltd.     

Web数据并行搜索驱动模型

面对海量Web数据的高效率搜索问题的需求，并行、分布式的体系结构可以构建大规模搜索系统。该文利用多级分布式并行构架，运用网格理论技术，挖掘Internet上空闲的计算资源，提出了一个Web数据并行搜索驱动模型，描述了模型的主要部件、体系结构、搜索过程及并行驱动机制。分析和实验表明，该模型具有良好的可扩展性，适合Internet网络数据的大规模搜索应用。     

Grid Computing in China

Grid computing presents a new trend to distributed computation and Internet applications, which can construct a virtual single image of heterogeneous resources, provide uniform application interface and integrate widespread computational resources into super, ubiquitous and transparent aggregation. In the adoption of Grid computing, China, who is facing more resource heterogeneity and other specific demands, has put much effort on both research and practical utilization. In this paper, we introduce the major China Grid research projects and their perspective applications. First we give the overview of the four government-sponsored programs in Grid, namely the China National Grid, ChinaGrid, NSFC Grid, and ShanghaiGrid. Then we present six representative ongoing Grid systems in details, which are categorized into Grid middleware and Grid application. This paper provides the general picture of Grid computing in China, and shows the great efforts, devotion and confidence in China to use Grid technology to boost the society, economics and scientific research.     

Service-oriented middleware for distributed data mining on the grid

Distribution of data and computation allows for solving larger problems and executing applications that are distributed in nature. The grid is a distributed computing infrastructure that enables coordinated resource sharing within dynamic organizations consisting of individuals, institutions, and resources. The grid extends the distributed and parallel computing paradigms allowing for resource negotiation and dynamical allocation, heterogeneity, open protocols, and services. Grid environments can be used both for compute-intensive tasks and data intensive applications by exploiting their resources, services, and data access mechanisms. Data mining algorithms and knowledge discovery processes are both compute and data intensive, therefore the grid can offer a computing and data management infrastructure for supporting decentralized and parallel data analysis. This paper discusses how grid computing can be used to support distributed data mining. Research activities in grid-based data mining and some challenges in this area are presented along with some promising future directions for developing grid-based distributed data mining.