The Data Ocean Project An ATLAS and Google R&D collaboration

被引：2

作者：

Barisits, Martin ^{[1
]}

Barreiro, Fernando ^{[2
]}

Beermann, Thomas ^{[3
]}

Bhatia, Karan ^{[4
]}

De, Kaushik ^{[2
]}

Dubreuil, Arnaud ^{[5
]}

Elmsheuser, Johannes ^{[6
]}

Klimentov, Alexei ^{[6
]}

Lassnig, Mario ^{[1
]}

Love, Peter ^{[7
]}

Maeno, Tadashi ^{[6
]}

Manzi, Andrea ^{[1
]}

Mashinistov, Ruslan ^{[6
]}

Murphy, Andy ^{[4
]}

Nilsson, Paul ^{[6
]}

Panitkin, Sergey ^{[6
]}

Wegner, Tobias ^{[1
]}

机构：

[1] CERN, European Org Nucl Res, Geneva, Switzerland

[2] Univ Texas Arlington, Arlington, TX 76019 USA

[3] Univ Innsbruck, Innsbruck, Austria

[4] Google LLC, Mountain View, CA USA

[5] Univ Geneva, Geneva, Switzerland

[6] Brookhaven Natl Lab, Upton, NY 11973 USA

[7] Univ Lancaster, Lancaster, England

来源：

23RD INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS (CHEP 2018) | 2019年 / 214卷

关键词：

D O I：

10.1051/epjconf/201921404020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Transparent use of commercial cloud resources for scientific experiments is a hard problem. In this article, we describe the first steps of the Data Ocean R&D collaboration between the high-energy physics experiment ATLAS together with Google Cloud Platform, to allow seamless use of Google Compute Engine and Google Cloud Storage for physics analysis. We start by describing the three preliminary use cases that were identified at the beginning of the project. The following sections then detail the work done in the data management system Rucio and the workflow management systems PanDA and Harvester to interface Google Cloud Platform with the ATLAS distributed computing environment, and show the results of the integration tests. Afterwards, we describe the setup and results from a full ATLAS user analysis that was executed natively on Google Cloud Platform, and give estimates on projected costs. We close with a summary and and outlook on future work.

引用

页数：8

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