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Distributed computing practice for large-scale science and engineering applications

机译:面向大规模科学和工程应用的分布式计算实践

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摘要

It is generally accepted that the ability to develop large-scale distributed applications has lagged seriously behind other developments in cyberinfrastructure. In this paper, we provide insight into how such applications have been developed and an understanding of why developing applications for distributed infrastructure is hard. Our approach is unique in the sense that it is centered around half a dozen existing scientific applications; we posit that these scientific applications are representative of the characteristics, requirements, as well as the challenges of the bulk of current distributed applications on production cyberinfrastructure (such as the US TeraGrid). We provide a novel and comprehensive analysis of such distributed scientific applications. Specifically, we survey existing models and methods for large-scale distributed applications and identify commonalities, recurring structures, patterns and abstractions. We find that there are many ad hoc solutions employed to develop and execute distributed applications, which result in a lack of generality and the inability of distributed applications to be extensible and independent of infrastructure details. In our analysis, we introduce the notion of application vectors: a novel way of understanding the structure of distributed applications. Important contributions of this paper include identifying patterns that are derived from a wide range of real distributed applications, as well as an integrated approach to analyzing applications, programming systems and patterns, resulting in the ability to provide a critical assessment of the current practice of developing, deploying and executing distributed applications. Gaps and omissions in the state of the art are identified, and directions for future research are outlined.
机译:人们普遍认为,开发大规模分布式应用程序的能力严重落后于网络基础设施的其他发展。在本文中,我们提供了有关如何开发此类应用程序的见解,并了解了为什么很难为分布式基础架构开发应用程序。我们的方法是独特的,因为它以六种现有的科学应用为中心。我们认为,这些科学应用代表了生产网络基础设施(例如美国TeraGrid)上当前的大量分布式应用的特征,要求和挑战。我们提供了这种分布式科学应用的新颖而全面的分析。具体来说,我们调查了用于大规模分布式应用程序的现有模型和方法,并确定了共性,重复出现的结构,模式和抽象。我们发现,有许多临时解决方案用于开发和执行分布式应用程序,这导致缺乏通用性,并且分布式应用程序无法扩展且与基础结构细节无关。在我们的分析中,我们介绍了应用程序向量的概念:一种理解分布式应用程序结构的新颖方法。本文的重要贡献包括识别从各种实际分布式应用程序衍生的模式,以及分析应用程序,编程系统和模式的集成方法,从而能够对当前开发实践进行关键评估。 ,部署和执行分布式应用程序。确定了现有技术的差距和遗漏,并概述了未来研究的方向。

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  • 来源
    《Concurrency and Computation》 |2013年第11期|1559-1585|共27页
  • 作者单位

    Center for Computation & Technology, Louisiana State University, Baton Rouge, LA, USA,School of Informatics, University of Edinburgh, Edinburgh, Scotland, UK,NSF Cloud and Autonomic Computing Center, Rutgers University, PiscatawayNJ, USA,Department of Electrical and Computer Engineering, Rutgers University, Piscataway NJ, USA;

    School of Informatics, University of Edinburgh, Edinburgh, Scotland, UK;

    Center for Computation & Technology, Louisiana State University, Baton Rouge, LA, USA,Computation Institute, University of Chicago, Chicago, IL, USA,Argonne National Laboratory, Argonne, IL, USA,Department of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA, USA;

    NSF Cloud and Autonomic Computing Center, Rutgers University, PiscatawayNJ, USA,Department of Electrical and Computer Engineering, Rutgers University, Piscataway NJ, USA;

    School of Computer Science & Informatics, Cardiff University, UK;

    Department of Computer Science, University of Minnesota, Minneapolis, MN, USA;

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