海报:PanDA:面向大数据的新一代工作量管理与分析系统

K. De, A. Klimentov, S. Panitkin, M. Titov, A. Vaniachine, T. Wenaus, D. Yu, G. Záruba
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引用次数: 3

摘要

在现实世界中,任何大型科学项目都意味着使用复杂的工作负载管理系统(WMS)来处理大量高度分布式的数据,这些数据通常由大型协作访问。生产和分布式分析系统(PanDA)是一个高性能的WMS,旨在满足能够在大型强子对撞机数据处理规模上运行的数据驱动工作负载管理系统的生产和分析需求。PanDA为广泛的实验应用提供执行环境,自动化集中数据生产和处理,支持物理组的分析活动,支持单个物理学家的自定义工作流,提供分布式全球资源的统一视图,通过集成的监控系统呈现工作流的状态和历史,存档和管理所有工作流。作为一个已经在极端规模上得到验证的WMS, PanDA现在正在被一般化和打包,以供大数据社区更广泛地使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poster: PanDA: Next Generation Workload Management and Analysis System for Big Data
In real world any big science project implies to use a sophisticated Workload Management System (WMS) that deals with a huge amount of highly distributed data, which is often accessed by large collaborations. The Production and Distributed Analysis System (PanDA) is a high-performance WMS that is aimed to meet production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider data processing scale. PanDA provides execution environments for a wide range of experimental applications, automates centralized data production and processing, enables analysis activity of physics groups, supports custom workflow of individual physicists, provides a unified view of distributed worldwide resources, presents status and history of workflow through an integrated monitoring system, archives and curates all workflow. PanDA is now being generalized and packaged, as a WMS already proven at extreme scales, for the wider use of the Big Data community.
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