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Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage
Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Co...
Autores principales: | , , , , , , , , , , |
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Lenguaje: | eng |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1051/epjconf/202024510004 http://cds.cern.ch/record/2752945 |
_version_ | 1780969329099014144 |
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author | Abed Abud, Adam Cicalese, Danilo Jereczek, Grzegorz Goff, Fabrice Le Lehmann Miotto, Giovanna Love, Jeremy Maciejewski, Maciej Mommsen, Remigius K Radtke, Jakub Schmiegel, Jakub Szychowska, Malgorzata |
author_facet | Abed Abud, Adam Cicalese, Danilo Jereczek, Grzegorz Goff, Fabrice Le Lehmann Miotto, Giovanna Love, Jeremy Maciejewski, Maciej Mommsen, Remigius K Radtke, Jakub Schmiegel, Jakub Szychowska, Malgorzata |
author_sort | Abed Abud, Adam |
collection | CERN |
description | Data acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment. |
id | oai-inspirehep.net-1832155 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
record_format | invenio |
spelling | oai-inspirehep.net-18321552022-08-17T13:56:01Zdoi:10.1051/epjconf/202024510004http://cds.cern.ch/record/2752945engAbed Abud, AdamCicalese, DaniloJereczek, GrzegorzGoff, Fabrice LeLehmann Miotto, GiovannaLove, JeremyMaciejewski, MaciejMommsen, Remigius KRadtke, JakubSchmiegel, JakubSzychowska, MalgorzataLet’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storageComputing and ComputersData acquisition systems are a key component for successful data taking in any experiment. The DAQ is a complex distributed computing system and coordinates all operations, from the data selection stage of interesting events to storage elements. For the High Luminosity upgrade of the Large Hadron Collider, the experiments at CERN need to meet challenging requirements to record data with a much higher occupancy in the detectors. The DAQ system will receive and deliver data with a significantly increased trigger rate, one million events per second, and capacity, terabytes of data per second. An effective way to meet these requirements is to decouple real-time data acquisition from event selection. Data fragments can be temporarily stored in a large distributed key-value store. Fragments belonging to the same event can be then queried on demand, by the data selection processes. Implementing such a model relies on a proper combination of emerging technologies, such as persistent memory, NVMe SSDs, scalable networking, and data structures, as well as high performance, scalable software. In this paper, we present DAQDB (Data Acquisition Database) — an open source implementation of this design that was presented earlier, with an extensive evaluation of this approach, from the single node to the distributed performance. Furthermore, we complement our study with a description of the challenges faced and the lessons learned while integrating DAQDB with the existing software framework of the ATLAS experiment.oai:inspirehep.net:18321552020 |
spellingShingle | Computing and Computers Abed Abud, Adam Cicalese, Danilo Jereczek, Grzegorz Goff, Fabrice Le Lehmann Miotto, Giovanna Love, Jeremy Maciejewski, Maciej Mommsen, Remigius K Radtke, Jakub Schmiegel, Jakub Szychowska, Malgorzata Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage |
title | Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage |
title_full | Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage |
title_fullStr | Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage |
title_full_unstemmed | Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage |
title_short | Let’s get our hands dirty: a comprehensive evaluation of DAQDB, key-value store for petascale hot storage |
title_sort | let’s get our hands dirty: a comprehensive evaluation of daqdb, key-value store for petascale hot storage |
topic | Computing and Computers |
url | https://dx.doi.org/10.1051/epjconf/202024510004 http://cds.cern.ch/record/2752945 |
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