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The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation

The Cherenkov Telescope Array (CTA) is the next-generation instrument in the field of very high energy gamma-ray astronomy. It will be composed of two arrays of Imaging Atmospheric Cherenkov Telescopes, located at La Palma (Spain) and Paranal (Chile). The construction of CTA has just started with th...

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Autores principales: Arrabito, Luisa, Bernlöhr, Konrad, Bregeon, Johan, Cumani, Paolo, Hassan, Tarek, Haupt, Andreas, Maier, Gernot, Moralejo, Abelardo, Neyroud, Nadine, Stagni, Federico, Tsaregorodtsev, Andrei
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/201921403052
http://cds.cern.ch/record/2701503
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author Arrabito, Luisa
Bernlöhr, Konrad
Bregeon, Johan
Cumani, Paolo
Hassan, Tarek
Haupt, Andreas
Maier, Gernot
Moralejo, Abelardo
Neyroud, Nadine
Stagni, Federico
Tsaregorodtsev, Andrei
author_facet Arrabito, Luisa
Bernlöhr, Konrad
Bregeon, Johan
Cumani, Paolo
Hassan, Tarek
Haupt, Andreas
Maier, Gernot
Moralejo, Abelardo
Neyroud, Nadine
Stagni, Federico
Tsaregorodtsev, Andrei
author_sort Arrabito, Luisa
collection CERN
description The Cherenkov Telescope Array (CTA) is the next-generation instrument in the field of very high energy gamma-ray astronomy. It will be composed of two arrays of Imaging Atmospheric Cherenkov Telescopes, located at La Palma (Spain) and Paranal (Chile). The construction of CTA has just started with the installation of the first telescope on site at La Palma and the first data expected by the end of 2018. The scientific operations should begin in 2022 for a duration of about 30 years. The overall amount of data produced during these operations is around 27 PB per year. The associated computing power for data processing and Monte Carlo (MC) simulations is of the order of hundreds of millions of CPU HS06 hours per year. In order to cope with these high computing requirements, we have developed a production system prototype basedon the DIRAC framework, that we have intensively exploited during the past 6 years to handle massive MC simulations on the grid for the CTA design and prototyping phases. CTA workflows are composed of several inter-dependent steps, which we used to handle separately within our production system. In order to fully automatize the whole workflows execution, we have partially revised the production system by further enhancing the data-driven behavior and by extending the use of meta-data to link together the different steps of a workflow. In this contribution we present the application of the production system to the last years MC campaigns as well as the recent production system evolution, intended to obtain a fully data-driven and automatized workflow execution for efficient processing of real telescope data.
id oai-inspirehep.net-1760949
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
record_format invenio
spelling oai-inspirehep.net-17609492022-08-10T12:26:25Zdoi:10.1051/epjconf/201921403052http://cds.cern.ch/record/2701503engArrabito, LuisaBernlöhr, KonradBregeon, JohanCumani, PaoloHassan, TarekHaupt, AndreasMaier, GernotMoralejo, AbelardoNeyroud, NadineStagni, FedericoTsaregorodtsev, AndreiThe Cherenkov Telescope Array production system for data-processing and Monte Carlo simulationComputing and ComputersAstrophysics and AstronomyThe Cherenkov Telescope Array (CTA) is the next-generation instrument in the field of very high energy gamma-ray astronomy. It will be composed of two arrays of Imaging Atmospheric Cherenkov Telescopes, located at La Palma (Spain) and Paranal (Chile). The construction of CTA has just started with the installation of the first telescope on site at La Palma and the first data expected by the end of 2018. The scientific operations should begin in 2022 for a duration of about 30 years. The overall amount of data produced during these operations is around 27 PB per year. The associated computing power for data processing and Monte Carlo (MC) simulations is of the order of hundreds of millions of CPU HS06 hours per year. In order to cope with these high computing requirements, we have developed a production system prototype basedon the DIRAC framework, that we have intensively exploited during the past 6 years to handle massive MC simulations on the grid for the CTA design and prototyping phases. CTA workflows are composed of several inter-dependent steps, which we used to handle separately within our production system. In order to fully automatize the whole workflows execution, we have partially revised the production system by further enhancing the data-driven behavior and by extending the use of meta-data to link together the different steps of a workflow. In this contribution we present the application of the production system to the last years MC campaigns as well as the recent production system evolution, intended to obtain a fully data-driven and automatized workflow execution for efficient processing of real telescope data.oai:inspirehep.net:17609492019
spellingShingle Computing and Computers
Astrophysics and Astronomy
Arrabito, Luisa
Bernlöhr, Konrad
Bregeon, Johan
Cumani, Paolo
Hassan, Tarek
Haupt, Andreas
Maier, Gernot
Moralejo, Abelardo
Neyroud, Nadine
Stagni, Federico
Tsaregorodtsev, Andrei
The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation
title The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation
title_full The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation
title_fullStr The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation
title_full_unstemmed The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation
title_short The Cherenkov Telescope Array production system for data-processing and Monte Carlo simulation
title_sort cherenkov telescope array production system for data-processing and monte carlo simulation
topic Computing and Computers
Astrophysics and Astronomy
url https://dx.doi.org/10.1051/epjconf/201921403052
http://cds.cern.ch/record/2701503
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