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Harnessing the power of supercomputers using the PanDA Pilot 2 in the ATLAS Experiment
/ Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Benjamin, Douglas (Argonne National Laboratory) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Anisenkov, Alexey (Budker Institute of Nuclear Physics and Novosibirsk State University, Siberian Branch of Russian Academy of Sciences) ; Guan, Wen (Department of Physics, University of Wisconsin) ; Javurek, Tomas (CERN)
/ATLAS Collaboration
The unprecedented computing resource needs of the ATLAS experiment have motivated the Collaboration to become a leader in exploiting High Performance Computers (HPCs). To meet the requirements of HPCs, the PanDA system has been equipped with two new components; Pilot 2 and Harvester, that were designed with HPCs in mind. [...]
ATL-SOFT-SLIDE-2019-821.-
Geneva : CERN, 2019 - 12 p.
Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019
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Global heterogeneous resource harvesting: the next-generation PanDA Pilot for ATLAS
/ Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Guan, Wen (Department of Physics, University of Wisconsin) ; Anisenkov, Alexey (Budker Institute of Nuclear Physics, Siberian Branch of Russian Academy of Sciences) ; Lassnig, Mario (European Laboratory for Particle Physics, CERN) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Drizhuk, Daniil (NRC Kurchatov Institute Tier site)
The Production and Distributed Analysis system (PanDA), used for workload management in the ATLAS Experiment for over a decade, has in recent years expanded its reach to diverse new resource types such as HPCs, and innovative new workflows such as the Event Service. [...]
ATL-SOFT-PROC-2017-074.
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2018-10-18. - 5 p.
Original Communication (restricted to ATLAS) - Full text - Full text
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Global heterogeneous resource harvesting: the next-generation PanDA pilot for ATLAS
/ Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Anisenkov, Alexey (Budker Institute of Nuclear Physics, Siberian Branch of Russian Academy of Sciences) ; Drizhuk, Daniil (NRC Kurchatov Institute Tier site) ; Guan, Wen (Department of Physics, University of Wisconsin) ; Lassnig, Mario (European Laboratory for Particle Physics, CERN) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Svirin, Pavlo (Brookhaven National Laboratory (BNL))
/ATLAS Collaboration
The Production and Distributed Analysis system (PanDA), used for workload management in the ATLAS Experiment for over a decade, has in recent years expanded its reach to diverse new resource types such as HPCs, and innovative new workflows such as the event service. PanDA meets the heterogeneous resources it harvests in the PanDA pilot, which has embarked on a next-generation reengineering to efficiently integrate and exploit the new platforms and workflows. [...]
ATL-SOFT-SLIDE-2017-658.-
Geneva : CERN, 2017 - 1 p.
Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Seattle, WA, USA, 21 - 25 Aug 2017
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The next generation PanDA Pilot for and beyond the ATLAS experiment
/ Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Anisenkov, Alexey (Budker Institute of Nuclear Physics, Siberian Branch of Russian Academy of Sciences) ; Benjamin, Douglas (Duke University, Department of Physics) ; Drizhuk, Daniil (NRC Kurchatov Institute Tier site) ; Guan, Wen (Department of Physics, University of Wisconsin) ; Lassnig, Mario (European Laboratory for Particle Physics, CERN) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Svirin, Pavlo (Brookhaven National Laboratory (BNL)) ; Wegner, Tobias Thomas (European Laboratory for Particle Physics, CERN)
/ATLAS Collaboration
The Production and Distributed Analysis system (PanDA) is a pilot-based workload management system that was originally designed for the ATLAS Experiment at the LHC to operate on grid sites. Since the coming LHC data taking runs will require more resources than grid computing alone can provide, the various LHC experiments are engaged in an ambitious program to extend the computing model to include opportunistically used resources such as High Performance Computers (HPCs), clouds and volunteer computers. [...]
ATL-SOFT-SLIDE-2018-408.-
Geneva : CERN, 2018 - 1 p.
Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018
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The next generation PanDA Pilot for and beyond the ATLAS experiment
/ Nilsson, Paul (Brookhaven) ; Anisenkov, Alexey (Novosibirsk, IYF ; Novosibirsk State U.) ; Benjamin, Douglas (Argonne (main)) ; Drizhuk, Daniil (Kurchatov Inst., Moscow) ; Guan, Wen (Wisconsin U., Madison) ; Lassnig, Mario (CERN) ; Oleynik, Danila (Dubna, JINR ; Texas U., Arlington) ; Svirin, Pavlo (Brookhaven) ; Wegner, Tobias Thomas (CERN)
The Production and Distributed Analysis system (PanDA) is a pilot-based workload management system that was originally designed for the ATLAS Experiment at the LHC and to use with grid sites. [...]
ATL-SOFT-PROC-2018-023.
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2019. - 6 p.
Original Communication (restricted to ATLAS) - ATLAS Note - Fulltext from publisher
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Integration of PanDA workload management system with Titan supercomputer at OLCF
/ Panitkin, Sergey (Brookhaven National Laboratory (BNL)) ; De, Kaushik (The University of Texas at Arlington) ; Klimentov, Alexei (Brookhaven National Laboratory (BNL)) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Petrosyan, Artem (Joint Institute for Nuclear Research) ; Schovancova, Jaroslava (The University of Texas at Arlington) ; Vaniachine, Alexandre (Argonne National Laboratory) ; Wenaus, Torre (Brookhaven National Laboratory (BNL))
The PanDA (Production and Distributed Analysis) workload management system (WMS) was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. While PanDA currently uses more than 100,000 cores at well over 100 Grid sites with a peak performance of 0.3 petaFLOPS, next LHC data taking run will require more resources than Grid computing can possibly provide. [...]
ATL-SOFT-SLIDE-2015-112.-
Geneva : CERN, 2015 - 20 p.
Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 21st International Conference on Computing in High Energy and Nuclear Physics, Okinawa, Japan, 13 - 17 Apr 2015
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