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iLCDirac and CI: Automated testing for distributed computing
Detector optimization studies for future high-energy physics experiments require the simulation and reconstruction of many physics processes and detector geometries. As an efficient way of accessing the necessary computational and storage resources, DIRAC has been developed and extended by iLCDirac,...
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Lenguaje: | eng |
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2016
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Acceso en línea: | https://dx.doi.org/10.23727/CERN-Proceedings-2017-001.103 http://cds.cern.ch/record/2225427 |
_version_ | 1780952402579423232 |
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author | Ebbing, Jan Hendrik |
author_facet | Ebbing, Jan Hendrik |
author_sort | Ebbing, Jan Hendrik |
collection | CERN |
description | Detector optimization studies for future high-energy physics experiments require the simulation and reconstruction of many physics processes and detector geometries. As an efficient way of accessing the necessary computational and storage resources, DIRAC has been developed and extended by iLCDirac, which is specialized for the applications used in the context of linear collider detector studies. We give a short introduction of grid computing and the concept of “High-throughput computing” behind DIRAC before explaining the unique features of DIRAC and iLCDirac. With this preparation we explain how we leveraged continuous integration to ensure smooth day-to-day operations, and that changes to the underlying code base do not cause an interruption of the service. |
id | cern-2225427 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2016 |
record_format | invenio |
spelling | cern-22254272019-09-30T06:29:59Zdoi:10.23727/CERN-Proceedings-2017-001.103http://cds.cern.ch/record/2225427engEbbing, Jan HendrikiLCDirac and CI: Automated testing for distributed computingComputing and ComputersDetector optimization studies for future high-energy physics experiments require the simulation and reconstruction of many physics processes and detector geometries. As an efficient way of accessing the necessary computational and storage resources, DIRAC has been developed and extended by iLCDirac, which is specialized for the applications used in the context of linear collider detector studies. We give a short introduction of grid computing and the concept of “High-throughput computing” behind DIRAC before explaining the unique features of DIRAC and iLCDirac. With this preparation we explain how we leveraged continuous integration to ensure smooth day-to-day operations, and that changes to the underlying code base do not cause an interruption of the service.CLICdp-Conf-2016-012oai:cds.cern.ch:22254272016 |
spellingShingle | Computing and Computers Ebbing, Jan Hendrik iLCDirac and CI: Automated testing for distributed computing |
title | iLCDirac and CI: Automated testing for distributed computing |
title_full | iLCDirac and CI: Automated testing for distributed computing |
title_fullStr | iLCDirac and CI: Automated testing for distributed computing |
title_full_unstemmed | iLCDirac and CI: Automated testing for distributed computing |
title_short | iLCDirac and CI: Automated testing for distributed computing |
title_sort | ilcdirac and ci: automated testing for distributed computing |
topic | Computing and Computers |
url | https://dx.doi.org/10.23727/CERN-Proceedings-2017-001.103 http://cds.cern.ch/record/2225427 |
work_keys_str_mv | AT ebbingjanhendrik ilcdiracandciautomatedtestingfordistributedcomputing |