Dữ liệu gird

In this short article, we aim to describe the relevance of Grids in education. As in fact information technology for education builds on that for any organization, we first discuss the implication of Grids and Web services for any organization – we call this an Enterprise to stress the importance of the Enterprise Grids and the different roles of general and specific features in any Grid deployment.

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In line with the usual chemistry seminar speaker who cannot resist changing the advertised title of a talk as the first, action of the talk, we will first, if not actually extend the title, indicate the vast scope of combinatorial chemistry. ‘Combinatorial Chemistry’ includes not only the synthesis of new molecules and materials, but also the associated purification, formulation, ‘parallel experiments’ and ‘high-throughput screening’ covering all areas of chemical discovery.

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This chapter introduces a project named eDiamond, which aims to develop a Grid-enabled federated database of annotated mammograms, built at a number of sites (initially in the United Kingdom), and which ensures database consistency and reliable image processing. A key feature of eDiamond is that images are ‘standardised’ prior to storage. Section 41.3 describes what this means, and why it is a fundamental requirement for numerous grid applications, particularly in medical image analysis, and especially in mammography....

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Computational biology is undergoing a revolution from a traditionally compute-intensive science conducted by individuals and small research groups to a high-throughput, datadriven science conducted by teams working in both academia and industry. It is this new biology as a data-driven science in the era of Grid Computing that is the subject of this chapter.

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INTRODUCTION: SCIENTIFIC EXPLORATION AT THE HIGH-ENERGY FRONTIER The major high-energy physics (HEP) experiments of the next twenty years will break new ground in our understanding of the fundamental interactions, structures and symmetries that govern the nature of matter and space-time. Among the principal goals are to find the mechanism responsible for mass in the universe, and the ‘Higgs’ particles associated with mass generation, as well as the fundamental mechanism that led to the predominance of matter over antimatter in the observable cosmos.

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THE VIRTUAL OBSERVATORY Astronomers have always been early adopters of technology, and information technology has been no exception. There is a vast amount of astronomical data available on the Internet, ranging from spectacular processed images of planets to huge amounts of raw, processed and private data. Much of the data is well documented with citations, instrumental settings, and the type of processing that has been applied.

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From the standpoint of the average user, today’s computer networks are extremely primitive compared to other networks. While the national power, transportation, and telecommunications networks have evolved to their present state of sophistication and ease of use, computer networks are at an early stage in their evolutionary process. Eventually, users will be unaware that they are using any computer but the one on their desk, because it will have the capability to reach out across the national network and obtain whatever computational resources that are necessary...

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There are many issues that should be considered in examining the implications of the imminent flood of data that will be generated both by the present and by the next generation of global ‘e-Science’ experiments. The term e-Science is used to represent the increasingly global collaborations – of people and of shared resources – that will be needed to solve the new problems of science and engineering [1]. These e-Science problems range from the simulation of whole engineering or biological systems, to research in bioinformatics, proteomics and pharmacogenetics.

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This book, Grid Computing: Making the Global Infrastructure a Reality, is divided into four parts. This short chapter introduces the last part, Part D, on applications for the Grid. All the chapters in the book contain material relevant for Grid applications, but in this part the focus is the applications themselves. Some of the previous chapters also cover applications as part of an overview or to illustrate a technological issue.

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Built upon a foundation of Simple Object Access Protocol (SOAP), Web Services Description Language (WSDL) and Universal Description Discovery and Integration (UDDI) technologies, Web services have become a widely accepted industry standard in the last few years [1, 2]. Because of their platform independence, universal compatibility, and network accessibility, Web services will be at the heart of the next generation of distributed systems. As more vendors offer SOAP tools and services, the advantages of using SOAP and Web services as an integration point will become even more pronounced.

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Computational Grids [1, 2] are large collections of resources such as computers, networks, on-line instruments, or storage archives, and they are becoming popular platforms for running large-scale, resource-intensive applications. Many challenges exist in providing the necessary mechanisms for accessing, discovering, monitoring, and aggregating Grid resources. Consequently, a tremendous effort has been made to develop middleware technology to establish a Grid software infrastructure (GSI) [2–4].

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Most, if not all, Computational Grid resource allocation and scheduling research espouses one of two paradigms: centralized omnipotent resource control [1–4] or localized application control [5–8]. The first is not a scalable solution either in terms of execution efficiency (the resource broker or scheduler becomes a bottleneck) or fault resilience (the allocation mechanism is a single point of failure). On the other hand, the second approach can lead to unstable resource assignments as ‘Grid-aware’ applications adapt to compete for resources....

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A collaboratory is defined as a place where scientists and researchers work together to solve complex interdisciplinary problems, despite geographic and organizational boundaries [1]. The growth of the Internet and the advent of the computational ‘Grid’ [2, 3] have made it possible to develop and deploy advanced computational collaboratories [4, 5] that provide uniform (collaborative) access to computational resources, services, applications and/or data. These systems expand the resources available to researchers, enable ...

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Computational Grid technologies hold the promise of providing global scale distributed computing for scientific applications. The goal of projects such as Globus [1], Legion [2], Condor [3], and others is to provide some portion of the infrastructure needed to support ubiquitous, geographically distributed computing [4, 5].

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This chapter describes a GridService demonstrator built around the Unicore Grid environment, its architectural design and implementation [1]. It then examines some lessons learned from the process of developing an implementation of a family of GridServices that conforms to the Open Grid Services Architecture (OGSA) [2] and the Grid Service Specification [3]. The goals of this project were two fold. Primarily, it is only through implementation that complexities such as those that arise in OGSA can be fully understood and analyzed....

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In this chapter, we discuss the development, architecture, and functionality of the National Partnership for Advanced Computational Infrastructure NPACI Grid Portals project. The emphasis of this paper is on the NPACI Grid Portal Toolkit (GridPort); we also discuss several Grid portals built using GridPort including the NPACI HotPage.

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Computational Grids [1] have emerged as a distributed computing infrastructure for providing pervasive, ubiquitous access to a diverse set of resources ranging from highperformance computers (HPC), tertiary storage systems, large-scale visualization systems, expensive and unique instruments including telescopes and accelerators. One of the primary motivations for building Grids is to enable large-scale scientific research projects to better utilize distributed, heterogeneous resources to solve a particular problem or set of problems....

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Over the past few years, various international groups have initiated research in the area of parallel and distributed computing in order to provide scientists with new programming methodologies that are required by state-of-the-art scientific application domains. These methodologies target collaborative, multidisciplinary, interactive, and large-scale applications that access a variety of high-end resources shared with others.

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Recent developments in high-speed networking enables collective use of globally distributed computing resources as a huge single problem-solving environment, also known as the Grid. The Grid not only presents a new, more difficult degree of inherent challenges in distributed computing such as heterogeneity, security, and instability, but will also require the constituent software substrates to be seamlessly interoperable across the network

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The emergence of Grid computing as the prototype of a next-generation cyber infrastructure for science has excited high expectations for its potential as an accelerator of discovery, but it has also raised questions about whether and how the broad population of research professionals, who must be the foundation of such productivity, can be motivated to adopt this new and more complex way of working.

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