为物理学家提供计算和数据:ATLAS分布式计算系统概述

Proceedings of 40th International Conference on High Energy physics — PoS(ICHEP2020) Pub Date : 2021-02-26 DOI:10.22323/1.390.0926

M. Svatos

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引用次数: 1

摘要

欧洲核子研究中心的ATLAS实验使用WLCG中的150多个站点来处理和分析大型强子对撞机记录的数据。网格工作流系统PanDA通常使用这些站点的40多万个CPU内核。数据管理系统Rucio管理分布在这些站点之间的大约半eb的探测器和模拟数据。随着大型强子对撞机性能的不断提高，预计会有更多的数据出现，ATLAS计算需要不断发展和适应。磁盘空间将变得更加稀缺，这应该通过更积极地使用磁带和缓存以及新的更小的数据格式来缓解。网格作业不仅可以在WLCG站点上运行，还可以在机会资源上运行，例如云和高性能计算。一种新的基于grafana的监测系统便于ATLAS计算的操作。本演讲将回顾和解释即将到来的Run 3的改进，并将展望HL-LHC所需的许多改进。

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Providing the computing and data to the physicists: Overview of the ATLAS distributed computing system

The ATLAS experiment at CERN uses more than 150 sites in the WLCG to process and analyze data recorded by the LHC. The grid workflow system PanDA routinely utilizes more than 400 thousand CPU cores of those sites. The data management system Rucio manages about half an exabyte of detector and simulation data distributed among these sites. With the ever-improving performance of the LHC, more data is expected to come and the ATLAS computing needs to evolve and adapt to that. Disk space will become more scarce which should be alleviated by more active usage of tapes and caches and new smaller data formats. Grid jobs can run not just on the WLCG sites but also on opportunistic resources, i.e. clouds and HPCs. A new grafana-based monitoring system facilitates operation of the ATLAS computing. This presentation will review and explain the improvements put in place for the upcoming Run 3 and will provide an outlook to the many improvements needed for the HL-LHC.

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Proceedings of 40th International Conference on High Energy physics — PoS(ICHEP2020)

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