Fine-Grained Processing Towards HL-LHC Computing in ATLAS

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During LHC's Run-2 ATLAS has been developing and evaluating new fine-grained approaches to workflows and dataflows able to better utilize computing resources in terms of storage, processing and networks. The compute-limited physics of ATLAS has driven the collaboration to aggressively harvest o...

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Autores principales: Benjamin, Doug, Calafiura, Paolo, Childers, Taylor, De, Kaushik, Di Girolamo, Alessandro, Fullana, Esteban, Guan, Wen, Maeno, Tadashi, Magini, Nicolo, Nilsson, Paul, Oleynik, Danila, Sun, Shaojun, Tsulaia, Vakho, Van Gemmeren, Peter, Wenaus, Torre, Yang, Wei
Lenguaje:eng
Publicado: 2018
Materias:
Computing and Computers
Detectors and Experimental Techniques
Acceso en línea:https://dx.doi.org/10.1109/eScience.2018.00083
http://cds.cern.ch/record/2674724
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author Benjamin, Doug
Calafiura, Paolo
Childers, Taylor
De, Kaushik
Di Girolamo, Alessandro
Fullana, Esteban
Guan, Wen
Maeno, Tadashi
Magini, Nicolo
Nilsson, Paul
Oleynik, Danila
Sun, Shaojun
Tsulaia, Vakho
Van Gemmeren, Peter
Wenaus, Torre
Yang, Wei
author_facet Benjamin, Doug
Calafiura, Paolo
Childers, Taylor
De, Kaushik
Di Girolamo, Alessandro
Fullana, Esteban
Guan, Wen
Maeno, Tadashi
Magini, Nicolo
Nilsson, Paul
Oleynik, Danila
Sun, Shaojun
Tsulaia, Vakho
Van Gemmeren, Peter
Wenaus, Torre
Yang, Wei
author_sort Benjamin, Doug
collection CERN
description During LHC's Run-2 ATLAS has been developing and evaluating new fine-grained approaches to workflows and dataflows able to better utilize computing resources in terms of storage, processing and networks. The compute-limited physics of ATLAS has driven the collaboration to aggressively harvest opportunistic cycles from what are often transiently available resources, including HPCs, clouds, volunteer computing, and grid resources in transitional states. Fine-grained processing (with typically a few minutes' granularity, corresponding to one event for the present ATLAS full simulation) enables agile workflows with a light footprint on the resource such that cycles can be more fully and efficiently utilized than with conventional workflows processing O(GB) files per job.
id oai-inspirehep.net-1721169
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2018
record_format invenio
spelling oai-inspirehep.net-17211692019-09-30T06:29:59Zdoi:10.1109/eScience.2018.00083http://cds.cern.ch/record/2674724engBenjamin, DougCalafiura, PaoloChilders, TaylorDe, KaushikDi Girolamo, AlessandroFullana, EstebanGuan, WenMaeno, TadashiMagini, NicoloNilsson, PaulOleynik, DanilaSun, ShaojunTsulaia, VakhoVan Gemmeren, PeterWenaus, TorreYang, WeiFine-Grained Processing Towards HL-LHC Computing in ATLASComputing and ComputersDetectors and Experimental TechniquesDuring LHC's Run-2 ATLAS has been developing and evaluating new fine-grained approaches to workflows and dataflows able to better utilize computing resources in terms of storage, processing and networks. The compute-limited physics of ATLAS has driven the collaboration to aggressively harvest opportunistic cycles from what are often transiently available resources, including HPCs, clouds, volunteer computing, and grid resources in transitional states. Fine-grained processing (with typically a few minutes' granularity, corresponding to one event for the present ATLAS full simulation) enables agile workflows with a light footprint on the resource such that cycles can be more fully and efficiently utilized than with conventional workflows processing O(GB) files per job.oai:inspirehep.net:17211692018
spellingShingle Computing and Computers
Detectors and Experimental Techniques
Benjamin, Doug
Calafiura, Paolo
Childers, Taylor
De, Kaushik
Di Girolamo, Alessandro
Fullana, Esteban
Guan, Wen
Maeno, Tadashi
Magini, Nicolo
Nilsson, Paul
Oleynik, Danila
Sun, Shaojun
Tsulaia, Vakho
Van Gemmeren, Peter
Wenaus, Torre
Yang, Wei
Fine-Grained Processing Towards HL-LHC Computing in ATLAS
title Fine-Grained Processing Towards HL-LHC Computing in ATLAS
title_full Fine-Grained Processing Towards HL-LHC Computing in ATLAS
title_fullStr Fine-Grained Processing Towards HL-LHC Computing in ATLAS
title_full_unstemmed Fine-Grained Processing Towards HL-LHC Computing in ATLAS
title_short Fine-Grained Processing Towards HL-LHC Computing in ATLAS
title_sort fine-grained processing towards hl-lhc computing in atlas
topic Computing and Computers
Detectors and Experimental Techniques
url https://dx.doi.org/10.1109/eScience.2018.00083
http://cds.cern.ch/record/2674724
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