FONDA合作研究中心。

Ulf Leser, Marcus Hilbrich, Claudia Draxl, Peter Eisert, Lars Grunske, Patrick Hostert, Dagmar Kainmüller, Odej Kao, Birte Kehr, Timo Kehrer, Christoph Koch, Volker Markl, Henning Meyerhenke, Tilmann Rabl, Alexander Reinefeld, Knut Reinert, Kerstin Ritter, Björn Scheuermann, Florian Schintke, Nicole Schweikardt, Matthias Weidlich
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引用次数: 6

摘要

今天的科学数据分析经常需要在分布式计算基础设施上执行复杂的数据分析工作流(daw),例如集群。许多研究工作致力于针对特定集群的特定工作流的调优和性能优化。然而,加速研究的一个更重要的问题是减少daw的开发、适应和维护时间。我们描述了协作研究中心(CRC) 1404“FONDA——大规模科学数据分析工作流的基础”的设计和设置,其中大约50名研究人员共同研究新技术、算法和模型,以增加在分布式基础设施上执行的daw的可移植性、适应性和可靠性。我们描述了我们项目背后的动机,解释了其潜在的核心概念,介绍了FONDA的内部结构,并概述了我们对未来基于工作流的科学数据分析的愿景。我们还描述了在“制作”具有强大跨学科成分的计算机科学CRC期间获得的一些经验教训,目的是促进类似的努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The Collaborative Research Center FONDA.

Today's scientific data analysis very often requires complex Data Analysis Workflows (DAWs) executed over distributed computational infrastructures, e.g., clusters. Much research effort is devoted to the tuning and performance optimization of specific workflows for specific clusters. However, an arguably even more important problem for accelerating research is the reduction of development, adaptation, and maintenance times of DAWs. We describe the design and setup of the Collaborative Research Center (CRC) 1404 "FONDA -- Foundations of Workflows for Large-Scale Scientific Data Analysis", in which roughly 50 researchers jointly investigate new technologies, algorithms, and models to increase the portability, adaptability, and dependability of DAWs executed over distributed infrastructures. We describe the motivation behind our project, explain its underlying core concepts, introduce FONDA's internal structure, and sketch our vision for the future of workflow-based scientific data analysis. We also describe some lessons learned during the "making of" a CRC in Computer Science with strong interdisciplinary components, with the aim to foster similar endeavors.

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