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Workflow management for high volume supernova search

机译:高卷超新加坡搜索的工作流管理

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Observational astrophysics has recently become a data-intensive science after many decades of relative data poverty. As a result, many of the algorithms developed for processing astronomical data, although well established for low-volume data capture, do not scale well to today's high-volume sky surveys and transient searches. Specifically, problems may occur with data transfer, workflow management, efficient parallelization, and integration of legacy code. Observational astrophysics workflows present computational challenges unique in high performance computing, including 24/7 operations, time-critical processing, and very large numbers of relatively small data files which must all be processed and archived. We present a case study based on Sunfall, a distributed, parallel scientific workflow system we built for the Nearby Supernova Factory, the largest data-volume supernova search currently in existence. We describe innovative techniques for data transfer and workflow management, and discusslessons learned in building a large-scale observational astrophysics workflow management system.
机译:在多十年的相对数据贫困之后,观察天体物理学最近成为数据密集型科学。因此,用于处理天文数据的许多算法虽然为低批量数据捕获成熟,但对当今的大批量天空调查和瞬态搜索不符。具体而言,数据传输,工作流管理,有效并行化和传统代码集成可能发生问题。观察天体物理学工作流程当前在高性能计算中具有独特的计算挑战,包括24/7操作,时间关键处理以及必须所有都会处理和存档的相对较小的数据文件。我们展示了一个基于Sunfall的案例研究,我们为附近的Supernova Factory建造了一个用于附近的Supernova Factory的分布式并行科学工作流系统,该搜索目前存在的最大数据卷超新星搜索。我们描述了用于数据传输和工作流程管理的创新技术,并在构建大规模观测天体工作流程管理系统时讨论了讨论。

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