776 research outputs found

    Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies

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    Grid is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid applications often involve large amounts of data and/or computing resources that require secure resource sharing across organizational boundaries. This makes Grid application management and deployment a complex undertaking. Grid middlewares provide users with seamless computing ability and uniform access to resources in the heterogeneous Grid environment. Several software toolkits and systems have been developed, most of which are results of academic research projects, all over the world. This chapter will focus on four of these middlewares--UNICORE, Globus, Legion and Gridbus. It also presents our implementation of a resource broker for UNICORE as this functionality was not supported in it. A comparison of these systems on the basis of the architecture, implementation model and several other features is included.Comment: 19 pages, 10 figure

    EGI user forum 2011 : book of abstracts

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    Survey and Analysis of Production Distributed Computing Infrastructures

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    This report has two objectives. First, we describe a set of the production distributed infrastructures currently available, so that the reader has a basic understanding of them. This includes explaining why each infrastructure was created and made available and how it has succeeded and failed. The set is not complete, but we believe it is representative. Second, we describe the infrastructures in terms of their use, which is a combination of how they were designed to be used and how users have found ways to use them. Applications are often designed and created with specific infrastructures in mind, with both an appreciation of the existing capabilities provided by those infrastructures and an anticipation of their future capabilities. Here, the infrastructures we discuss were often designed and created with specific applications in mind, or at least specific types of applications. The reader should understand how the interplay between the infrastructure providers and the users leads to such usages, which we call usage modalities. These usage modalities are really abstractions that exist between the infrastructures and the applications; they influence the infrastructures by representing the applications, and they influence the ap- plications by representing the infrastructures

    Enabling quantitative data analysis through e-infrastructures

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    This paper discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities which are central to quantitative data analysis, referred to as ‘data management’, can benefit from e-infrastructure support. We conclude by discussing how these issues are relevant to the DAMES (Data Management through e-Social Science) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences

    Fine-Grained Workflow Interoperability in Life Sciences

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    In den vergangenen Jahrzehnten fĂŒhrten Fortschritte in den SchlĂŒsseltechnologien der Lebenswissenschaften zu einer exponentiellen Zunahme der zur VerfĂŒgung stehenden biologischen Daten. Um Ergebnisse zeitnah generieren zu können werden sowohl spezialisierte Rechensystem als auch ProgrammierfĂ€higkeiten benötigt: Desktopcomputer oder monolithische AnsĂ€tze sind weder in der Lage mit dem Wachstum der verfĂŒgbaren biologischen Daten noch mit der KomplexitĂ€t der Analysetechniken Schritt zu halten. Workflows erlauben diesem Trend durch ParallelisierungsansĂ€tzen und verteilten Rechensystemen entgegenzuwirken. Ihre transparenten AblĂ€ufe, gegeben durch ihre klar definierten Strukturen, ebenso ihre Wiederholbarkeit, erfĂŒllen die Standards der Reproduzierbarkeit, welche an wissenschaftliche Methoden gestellt werden. Eines der Ziele unserer Arbeit ist es Forschern beim Bedienen von Rechensystemen zu unterstĂŒtzen, ohne dass Programmierkenntnisse notwendig sind. DafĂŒr wurde eine Sammlung von Tools entwickelt, welche jedes Kommandozeilenprogramm in ein Workflowsystem integrieren kann. Ohne weitere Anpassungen kann unser Programm zwei weit verbreitete Workflowsysteme unterstĂŒtzen. Unser modularer Entwurf erlaubt zudem UnterstĂŒtzung fĂŒr weitere Workflowmaschinen hinzuzufĂŒgen. Basierend auf der Bedeutung von frĂŒhen und robusten WorkflowentwĂŒrfen, haben wir außerdem eine wohl etablierte Desktop–basierte Analyseplattform erweitert. Diese enthĂ€lt ĂŒber 2.000 Aufgaben, wobei jede als Baustein in einem Workflow fungiert. Die Plattform erlaubt einfache Entwicklung neuer Aufgaben und die Integration externer Kommandozeilenprogramme. In dieser Arbeit wurde ein Plugin zur Konvertierung entwickelt, welches nutzerfreundliche Mechanismen bereitstellt, um Workflows auf verteilten Hochleistungsrechensystemen auszufĂŒhren—eine Aufgabe, die sonst technische Kenntnisse erfordert, die gewöhnlich nicht zum Anforderungsprofil eines Lebenswissenschaftlers gehören. Unsere Konverter–Erweiterung generiert quasi identische Versionen desselben Workflows, welche im Anschluss auf leistungsfĂ€higen Berechnungsressourcen ausgefĂŒhrt werden können. Infolgedessen werden nicht nur die Möglichkeiten von verteilten hochperformanten Rechensystemen sowie die Bequemlichkeit eines fĂŒr Desktopcomputer entwickelte Workflowsystems ausgenutzt, sondern zusĂ€tzlich werden BerechnungsbeschrĂ€nkungen von Desktopcomputern und die steile Lernkurve, die mit dem Workflowentwurf auf verteilten Systemen verbunden ist, umgangen. Unser Konverter–Plugin hat sofortige Anwendung fĂŒr Forscher. Wir zeigen dies in drei fĂŒr die Lebenswissenschaften relevanten Anwendungsbeispielen: Strukturelle Bioinformatik, Immuninformatik, und Metabolomik.Recent decades have witnessed an exponential increase of available biological data due to advances in key technologies for life sciences. Specialized computing resources and scripting skills are now required to deliver results in a timely fashion: desktop computers or monolithic approaches can no longer keep pace with neither the growth of available biological data nor the complexity of analysis techniques. Workflows offer an accessible way to counter against this trend by facilitating parallelization and distribution of computations. Given their structured and repeatable nature, workflows also provide a transparent process to satisfy strict reproducibility standards required by the scientific method. One of the goals of our work is to assist researchers in accessing computing resources without the need for programming or scripting skills. To this effect, we created a toolset able to integrate any command line tool into workflow systems. Out of the box, our toolset supports two widely–used workflow systems, but our modular design allows for seamless additions in order to support further workflow engines. Recognizing the importance of early and robust workflow design, we also extended a well–established, desktop–based analytics platform that contains more than two thousand tasks (each being a building block for a workflow), allows easy development of new tasks and is able to integrate external command line tools. We developed a converter plug–in that offers a user–friendly mechanism to execute workflows on distributed high–performance computing resources—an exercise that would otherwise require technical skills typically not associated with the average life scientist's profile. Our converter extension generates virtually identical versions of the same workflows, which can then be executed on more capable computing resources. That is, not only did we leverage the capacity of distributed high–performance resources and the conveniences of a workflow engine designed for personal computers but we also circumvented computing limitations of personal computers and the steep learning curve associated with creating workflows for distributed environments. Our converter extension has immediate applications for researchers and we showcase our results by means of three use cases relevant for life scientists: structural bioinformatics, immunoinformatics and metabolomics

    A formal architecture-centric and model driven approach for the engineering of science gateways

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    From n-Tier client/server applications, to more complex academic Grids, or even the most recent and promising industrial Clouds, the last decade has witnessed significant developments in distributed computing. In spite of this conceptual heterogeneity, Service-Oriented Architecture (SOA) seems to have emerged as the common and underlying abstraction paradigm, even though different standards and technologies are applied across application domains. Suitable access to data and algorithms resident in SOAs via so-called ‘Science Gateways’ has thus become a pressing need in order to realize the benefits of distributed computing infrastructures.In an attempt to inform service-oriented systems design and developments in Grid-based biomedical research infrastructures, the applicant has consolidated work from three complementary experiences in European projects, which have developed and deployed large-scale production quality infrastructures and more recently Science Gateways to support research in breast cancer, pediatric diseases and neurodegenerative pathologies respectively. In analyzing the requirements from these biomedical applications the applicant was able to elaborate on commonly faced issues in Grid development and deployment, while proposing an adapted and extensible engineering framework. Grids implement a number of protocols, applications, standards and attempt to virtualize and harmonize accesses to them. Most Grid implementations therefore are instantiated as superposed software layers, often resulting in a low quality of services and quality of applications, thus making design and development increasingly complex, and rendering classical software engineering approaches unsuitable for Grid developments.The applicant proposes the application of a formal Model-Driven Engineering (MDE) approach to service-oriented developments, making it possible to define Grid-based architectures and Science Gateways that satisfy quality of service requirements, execution platform and distribution criteria at design time. An novel investigation is thus presented on the applicability of the resulting grid MDE (gMDE) to specific examples and conclusions are drawn on the benefits of this approach and its possible application to other areas, in particular that of Distributed Computing Infrastructures (DCI) interoperability, Science Gateways and Cloud architectures developments
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