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A New Petabyte-scale Data Derivation Framework for ATLAS

During the Long Shutdown of the LHC, the ATLAS collaboration overhauled its analysis model based on experience gained during Run 1. A significant component of the model is a ``Derivation Framework" that takes the Petabyte-scale AOD output from ATLAS reconstruction and produces samples, typicall...

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Autores principales: Catmore, James, Laycock, Paul, Gramstad, Eirik, Gillam, Thomas, Cranshaw, Jack, Ozturk, Nurcan, Stewart, Graeme
Lenguaje:eng
Publicado: 2015
Materias:
Acceso en línea:https://dx.doi.org/10.1088/1742-6596/664/7/072007
http://cds.cern.ch/record/2016628
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author Catmore, James
Laycock, Paul
Gramstad, Eirik
Gillam, Thomas
Cranshaw, Jack
Ozturk, Nurcan
Stewart, Graeme
author_facet Catmore, James
Laycock, Paul
Gramstad, Eirik
Gillam, Thomas
Cranshaw, Jack
Ozturk, Nurcan
Stewart, Graeme
author_sort Catmore, James
collection CERN
description During the Long Shutdown of the LHC, the ATLAS collaboration overhauled its analysis model based on experience gained during Run 1. A significant component of the model is a ``Derivation Framework" that takes the Petabyte-scale AOD output from ATLAS reconstruction and produces samples, typically Terabytes in size, targeted at specific analyses. The framework incorporates all of the functionality of the core reconstruction software, while producing outputs that are simply configured. Event selections are specified via strings, including support for logical operations. The output content can be highly optimised to minimise disk requirements, while maintaining the same C++ interface. The framework includes an interface to the late-stage physics analysis tools, ensuring that the final outputs are consistent with tool requirements. Finally, the framework allows several outputs to be produced for the same input, providing the possibility to optimise configurations to computing resources.
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
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spelling cern-20166282022-08-10T12:55:10Zdoi:10.1088/1742-6596/664/7/072007http://cds.cern.ch/record/2016628engCatmore, JamesLaycock, PaulGramstad, EirikGillam, ThomasCranshaw, JackOzturk, NurcanStewart, GraemeA New Petabyte-scale Data Derivation Framework for ATLASParticle Physics - ExperimentDuring the Long Shutdown of the LHC, the ATLAS collaboration overhauled its analysis model based on experience gained during Run 1. A significant component of the model is a ``Derivation Framework" that takes the Petabyte-scale AOD output from ATLAS reconstruction and produces samples, typically Terabytes in size, targeted at specific analyses. The framework incorporates all of the functionality of the core reconstruction software, while producing outputs that are simply configured. Event selections are specified via strings, including support for logical operations. The output content can be highly optimised to minimise disk requirements, while maintaining the same C++ interface. The framework includes an interface to the late-stage physics analysis tools, ensuring that the final outputs are consistent with tool requirements. Finally, the framework allows several outputs to be produced for the same input, providing the possibility to optimise configurations to computing resources.ATL-SOFT-PROC-2015-041oai:cds.cern.ch:20166282015-05-16
spellingShingle Particle Physics - Experiment
Catmore, James
Laycock, Paul
Gramstad, Eirik
Gillam, Thomas
Cranshaw, Jack
Ozturk, Nurcan
Stewart, Graeme
A New Petabyte-scale Data Derivation Framework for ATLAS
title A New Petabyte-scale Data Derivation Framework for ATLAS
title_full A New Petabyte-scale Data Derivation Framework for ATLAS
title_fullStr A New Petabyte-scale Data Derivation Framework for ATLAS
title_full_unstemmed A New Petabyte-scale Data Derivation Framework for ATLAS
title_short A New Petabyte-scale Data Derivation Framework for ATLAS
title_sort new petabyte-scale data derivation framework for atlas
topic Particle Physics - Experiment
url https://dx.doi.org/10.1088/1742-6596/664/7/072007
http://cds.cern.ch/record/2016628
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