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Towards Green Big Data at CERN

High-energy physics studies collisions of particles traveling near the speed of light. For statistically significant results, physicists need to analyze a huge number of such events. One analysis job can take days and process tens of millions of collisions. Today the experiments of the large hadron...

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Detalles Bibliográficos
Autores principales: Niemi, Tapio, Nurminen, Jukka K, Liukkonen, Juha-Matti, Hameri, Ari-Pekka
Lenguaje:eng
Publicado: 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1016/j.future.2017.11.001
http://cds.cern.ch/record/2625094
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author Niemi, Tapio
Nurminen, Jukka K
Liukkonen, Juha-Matti
Hameri, Ari-Pekka
author_facet Niemi, Tapio
Nurminen, Jukka K
Liukkonen, Juha-Matti
Hameri, Ari-Pekka
author_sort Niemi, Tapio
collection CERN
description High-energy physics studies collisions of particles traveling near the speed of light. For statistically significant results, physicists need to analyze a huge number of such events. One analysis job can take days and process tens of millions of collisions. Today the experiments of the large hadron collider (LHC) create 10 GB of data per second and a future upgrade will cause a ten-fold increase in data. The data analysis requires not only massive hardware but also a lot of electricity. In this article, we discuss energy efficiency in scientific computing and review a set of intermixed approaches we have developed in our Green Big Data project to improve energy efficiency of CERN computing. These approaches include making energy consumption visible to developers and users, architectural improvements, smarter management of computing jobs, and benefits of cloud technologies. The open and innovative environment at CERN is an excellent playground for different energy efficiency ideas which can later find use in mainstream computing.
id oai-inspirehep.net-1678601
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
record_format invenio
spelling oai-inspirehep.net-16786012019-09-30T06:29:59Zdoi:10.1016/j.future.2017.11.001http://cds.cern.ch/record/2625094engNiemi, TapioNurminen, Jukka KLiukkonen, Juha-MattiHameri, Ari-PekkaTowards Green Big Data at CERNComputing and ComputersHigh-energy physics studies collisions of particles traveling near the speed of light. For statistically significant results, physicists need to analyze a huge number of such events. One analysis job can take days and process tens of millions of collisions. Today the experiments of the large hadron collider (LHC) create 10 GB of data per second and a future upgrade will cause a ten-fold increase in data. The data analysis requires not only massive hardware but also a lot of electricity. In this article, we discuss energy efficiency in scientific computing and review a set of intermixed approaches we have developed in our Green Big Data project to improve energy efficiency of CERN computing. These approaches include making energy consumption visible to developers and users, architectural improvements, smarter management of computing jobs, and benefits of cloud technologies. The open and innovative environment at CERN is an excellent playground for different energy efficiency ideas which can later find use in mainstream computing.oai:inspirehep.net:16786012018
spellingShingle Computing and Computers
Niemi, Tapio
Nurminen, Jukka K
Liukkonen, Juha-Matti
Hameri, Ari-Pekka
Towards Green Big Data at CERN
title Towards Green Big Data at CERN
title_full Towards Green Big Data at CERN
title_fullStr Towards Green Big Data at CERN
title_full_unstemmed Towards Green Big Data at CERN
title_short Towards Green Big Data at CERN
title_sort towards green big data at cern
topic Computing and Computers
url https://dx.doi.org/10.1016/j.future.2017.11.001
http://cds.cern.ch/record/2625094
work_keys_str_mv AT niemitapio towardsgreenbigdataatcern
AT nurminenjukkak towardsgreenbigdataatcern
AT liukkonenjuhamatti towardsgreenbigdataatcern
AT hameriaripekka towardsgreenbigdataatcern