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ATLAS & Google - The Data Ocean Project

With the LHC High Luminosity upgrade the workload and data management systems are facing new major challenges. To address those challenges ATLAS and Google agreed to cooperate on a project to connect Google Cloud Storage and Compute Engine to the ATLAS computing environment. The idea is to allow ATL...

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Autores principales: Lassnig, Mario, Klimentov, Alexei, De, Kaushik, Barreiro Megino, Fernando Harald, Elmsheuser, Johannes, Panitkin, Sergey, Wegner, Tobias Thomas, Barisits, Martin-Stefan, Beermann, Thomas Alfons, Mashinistov, Ruslan, Love, Peter, Dubreuil, Arnaud, Maeno, Tadashi, Nilsson, Paul
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:http://cds.cern.ch/record/2627092
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author Lassnig, Mario
Klimentov, Alexei
De, Kaushik
Barreiro Megino, Fernando Harald
Elmsheuser, Johannes
Panitkin, Sergey
Wegner, Tobias Thomas
Barisits, Martin-Stefan
Beermann, Thomas Alfons
Mashinistov, Ruslan
Love, Peter
Dubreuil, Arnaud
Maeno, Tadashi
Nilsson, Paul
author_facet Lassnig, Mario
Klimentov, Alexei
De, Kaushik
Barreiro Megino, Fernando Harald
Elmsheuser, Johannes
Panitkin, Sergey
Wegner, Tobias Thomas
Barisits, Martin-Stefan
Beermann, Thomas Alfons
Mashinistov, Ruslan
Love, Peter
Dubreuil, Arnaud
Maeno, Tadashi
Nilsson, Paul
author_sort Lassnig, Mario
collection CERN
description With the LHC High Luminosity upgrade the workload and data management systems are facing new major challenges. To address those challenges ATLAS and Google agreed to cooperate on a project to connect Google Cloud Storage and Compute Engine to the ATLAS computing environment. The idea is to allow ATLAS to explore the use of different computing models, to allow ATLAS user analysis to benefit from the Google infrastructure, and to give Google real science use cases to improve their cloud platform. Making the output of a distributed analysis from the grid quickly available to the analyst is a difficult problem. Redirecting the analysis output to Google Cloud Storage can provide an alternative, faster solution for the analyst. First, Google's Cloud Storage will be connected to the ATLAS Data Management System Rucio. The second part aims to let jobs run on Google Compute Engine, accessing data from either ATLAS storage or Google Cloud Storage. The third part involves Google implementing a global redirection between their regions to expose Google Cloud Storage as a single global entity. The last part will deal with the economic model necessary for sustainable cloud resource usage, including Google Cloud Storage costs, network costs, and peering costs with ESnet.
id cern-2627092
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
record_format invenio
spelling cern-26270922019-11-12T12:54:33Zhttp://cds.cern.ch/record/2627092engLassnig, MarioKlimentov, AlexeiDe, KaushikBarreiro Megino, Fernando HaraldElmsheuser, JohannesPanitkin, SergeyWegner, Tobias ThomasBarisits, Martin-StefanBeermann, Thomas AlfonsMashinistov, RuslanLove, PeterDubreuil, ArnaudMaeno, TadashiNilsson, PaulATLAS & Google - The Data Ocean ProjectParticle Physics - ExperimentWith the LHC High Luminosity upgrade the workload and data management systems are facing new major challenges. To address those challenges ATLAS and Google agreed to cooperate on a project to connect Google Cloud Storage and Compute Engine to the ATLAS computing environment. The idea is to allow ATLAS to explore the use of different computing models, to allow ATLAS user analysis to benefit from the Google infrastructure, and to give Google real science use cases to improve their cloud platform. Making the output of a distributed analysis from the grid quickly available to the analyst is a difficult problem. Redirecting the analysis output to Google Cloud Storage can provide an alternative, faster solution for the analyst. First, Google's Cloud Storage will be connected to the ATLAS Data Management System Rucio. The second part aims to let jobs run on Google Compute Engine, accessing data from either ATLAS storage or Google Cloud Storage. The third part involves Google implementing a global redirection between their regions to expose Google Cloud Storage as a single global entity. The last part will deal with the economic model necessary for sustainable cloud resource usage, including Google Cloud Storage costs, network costs, and peering costs with ESnet.ATL-SOFT-SLIDE-2018-421oai:cds.cern.ch:26270922018-06-28
spellingShingle Particle Physics - Experiment
Lassnig, Mario
Klimentov, Alexei
De, Kaushik
Barreiro Megino, Fernando Harald
Elmsheuser, Johannes
Panitkin, Sergey
Wegner, Tobias Thomas
Barisits, Martin-Stefan
Beermann, Thomas Alfons
Mashinistov, Ruslan
Love, Peter
Dubreuil, Arnaud
Maeno, Tadashi
Nilsson, Paul
ATLAS & Google - The Data Ocean Project
title ATLAS & Google - The Data Ocean Project
title_full ATLAS & Google - The Data Ocean Project
title_fullStr ATLAS & Google - The Data Ocean Project
title_full_unstemmed ATLAS & Google - The Data Ocean Project
title_short ATLAS & Google - The Data Ocean Project
title_sort atlas & google - the data ocean project
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2627092
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