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Buffering Strategies for Large-Scale Data-Acquisition Systems

Data acquisition systems for particle physics experiments produce vasts amounts of data. It is sometimes unfeasible to store it all since the storage requirements will be enormous. For this reason, an on-line filtering system selects the relevant pieces of information according to the goals of the e...

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Autor principal: Santos, Alejandro
Publicado: 2018
Acceso en línea:https://dx.doi.org/10.1145/3210284.3219500
http://cds.cern.ch/record/2800822
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author Santos, Alejandro
author_facet Santos, Alejandro
author_sort Santos, Alejandro
collection CERN
description Data acquisition systems for particle physics experiments produce vasts amounts of data. It is sometimes unfeasible to store it all since the storage requirements will be enormous. For this reason, an on-line filtering system selects the relevant pieces of information according to the goals of the experiment, before finally sending them to permanent storage. While data is being analyzed, it is temporarily stored in a large high-speed buffering system. Data production follows a cycle, with long periods of many hours where no data is being produced by the experiment. Also, data production is not constant, and there are fluctuations in the input rate. This offers the possibility of over-provisioning the buffering system and trading processing power for storage space. This buffer can be used for storage for periods of many days. In this work, a model was created to study the behavior of some aspects of the ATLAS data acquisition system, and specifically the buffering system for the on-line filter.
id cern-2800822
institution Organización Europea para la Investigación Nuclear
publishDate 2018
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spelling cern-28008222022-02-01T19:44:26Zdoi:10.1145/3210284.3219500http://cds.cern.ch/record/2800822Santos, AlejandroBuffering Strategies for Large-Scale Data-Acquisition SystemsData acquisition systems for particle physics experiments produce vasts amounts of data. It is sometimes unfeasible to store it all since the storage requirements will be enormous. For this reason, an on-line filtering system selects the relevant pieces of information according to the goals of the experiment, before finally sending them to permanent storage. While data is being analyzed, it is temporarily stored in a large high-speed buffering system. Data production follows a cycle, with long periods of many hours where no data is being produced by the experiment. Also, data production is not constant, and there are fluctuations in the input rate. This offers the possibility of over-provisioning the buffering system and trading processing power for storage space. This buffer can be used for storage for periods of many days. In this work, a model was created to study the behavior of some aspects of the ATLAS data acquisition system, and specifically the buffering system for the on-line filter.oai:cds.cern.ch:28008222018
spellingShingle Santos, Alejandro
Buffering Strategies for Large-Scale Data-Acquisition Systems
title Buffering Strategies for Large-Scale Data-Acquisition Systems
title_full Buffering Strategies for Large-Scale Data-Acquisition Systems
title_fullStr Buffering Strategies for Large-Scale Data-Acquisition Systems
title_full_unstemmed Buffering Strategies for Large-Scale Data-Acquisition Systems
title_short Buffering Strategies for Large-Scale Data-Acquisition Systems
title_sort buffering strategies for large-scale data-acquisition systems
url https://dx.doi.org/10.1145/3210284.3219500
http://cds.cern.ch/record/2800822
work_keys_str_mv AT santosalejandro bufferingstrategiesforlargescaledataacquisitionsystems