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Data preparation for NA62

In 2017, NA62 recorded over a petabyte of raw data, collecting around a billion events per day of running. Data are collected in bursts of 3-5 seconds, producing output files of a few gigabytes. A typical run, a sequence of bursts with the same detector configuration and similar experimental conditi...

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Autor principal: Laycock, Paul
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1051/epjconf/201921402017
http://cds.cern.ch/record/2701781
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author Laycock, Paul
author_facet Laycock, Paul
author_sort Laycock, Paul
collection CERN
description In 2017, NA62 recorded over a petabyte of raw data, collecting around a billion events per day of running. Data are collected in bursts of 3-5 seconds, producing output files of a few gigabytes. A typical run, a sequence of bursts with the same detector configuration and similar experimental conditions, contains 1500 bursts and constitutes the basic unit for offline data processing. A sample of 100 random bursts is used to make timing calibrations of all detectors, after which every burst in the run is reconstructed. Finally the reconstructed events are filtered by physics channel with an average reduction factor of 20, and data quality metrics are calculated.Initially a bespoke data processing solution was implemented using a simple finite state machine with limited production system functionality. In 2017, the ATLAS Tier-0 team offered the use of their production system, together with the necessary support. Data processing workflows were rewritten with better error-handling and I/O operations were minimised, the reconstruction software was improved and conditions data handling was changed to follow best practices suggested by the HEP Software Foundation conditions database working group. This contribution describes the experience gained in using these tools and methods for data-processing on a petabyte scale experiment.
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spelling oai-inspirehep.net-17605582022-08-10T12:23:27Zdoi:10.1051/epjconf/201921402017http://cds.cern.ch/record/2701781engLaycock, PaulData preparation for NA62Particle Physics - ExperimentComputing and ComputersIn 2017, NA62 recorded over a petabyte of raw data, collecting around a billion events per day of running. Data are collected in bursts of 3-5 seconds, producing output files of a few gigabytes. A typical run, a sequence of bursts with the same detector configuration and similar experimental conditions, contains 1500 bursts and constitutes the basic unit for offline data processing. A sample of 100 random bursts is used to make timing calibrations of all detectors, after which every burst in the run is reconstructed. Finally the reconstructed events are filtered by physics channel with an average reduction factor of 20, and data quality metrics are calculated.Initially a bespoke data processing solution was implemented using a simple finite state machine with limited production system functionality. In 2017, the ATLAS Tier-0 team offered the use of their production system, together with the necessary support. Data processing workflows were rewritten with better error-handling and I/O operations were minimised, the reconstruction software was improved and conditions data handling was changed to follow best practices suggested by the HEP Software Foundation conditions database working group. This contribution describes the experience gained in using these tools and methods for data-processing on a petabyte scale experiment.oai:inspirehep.net:17605582019
spellingShingle Particle Physics - Experiment
Computing and Computers
Laycock, Paul
Data preparation for NA62
title Data preparation for NA62
title_full Data preparation for NA62
title_fullStr Data preparation for NA62
title_full_unstemmed Data preparation for NA62
title_short Data preparation for NA62
title_sort data preparation for na62
topic Particle Physics - Experiment
Computing and Computers
url https://dx.doi.org/10.1051/epjconf/201921402017
http://cds.cern.ch/record/2701781
work_keys_str_mv AT laycockpaul datapreparationforna62