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Managing the ATLAS Grid through Harvester
/ Barreiro Megino, Fernando Harald (The University of Texas at Arlington) ; Alekseev, Aleksandr (Universidad Andres Bello) ; Berghaus, Frank (University of Victoria) ; Cameron, David (University of Oslo) ; De, Kaushik (The University of Texas at Arlington) ; Filipcic, Andrej (Jozef Stefan Institute) ; Glushkov, Ivan (The University of Texas at Arlington) ; Lin, Fahui (Academia Sinica, Taipei) ; Maeno, Tadashi (Brookhaven National Laboratory (BNL)) ; Magini, Nicolo (Iowa State University)
ATLAS Computing Management has identified the migration of all computing resources to Harvester, PanDA’s new workload submission engine, as a critical milestone for Run 3 and 4. [...]
ATL-SOFT-PROC-2020-006.
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2020. - 7 p.
Original Communication (restricted to ATLAS) - Full text - Full text - Fulltext from publisher - Full text
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PanDA for ATLAS Distributed Computing in the Next Decade
/ Barreiro Megino, Fernando Harald (The University of Texas at Arlington) ; Klimentov, Alexei (Brookhaven National Laboratory (BNL)) ; De, Kaushik (The University of Texas at Arlington) ; Maeno, Tadashi (Brookhaven National Laboratory (BNL)) ; Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Padolski, Siarhei (Brookhaven National Laboratory (BNL)) ; Panitkin, Sergey (Brookhaven National Laboratory (BNL)) ; Wenaus, Torre (Brookhaven National Laboratory (BNL))
/ATLAS Collaboration
The Production and Distributed Analysis (PanDA) system has been developed to meet ATLAS production and analysis requirements for a data-driven workload management system capable of operating at the Large Hadron Collider (LHC) data processing scale. Heterogeneous resources used by the ATLAS experiment are distributed worldwide at hundreds of sites, thousands of physicists analyse the data remotely, the volume of processed data is beyond the exabyte scale, dozens of scientific applications are supported, while data processing requires more than a few billion hours of computing usage per year. [...]
ATL-SOFT-SLIDE-2016-699.-
Geneva : CERN, 2016 - 14 p.
Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
In : 22nd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2016, San Francisco, Usa, 10 - 14 Oct 2016
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BigPanDA Experience on LCF and HPC for the ATLAS Experiment at the LHC and data intensive science
/ De, Kaushik (The University of Texas at Arlington) ; Barreiro Megino, Fernando Harald (The University of Texas at Arlington) ; Maeno, Tadashi (Brookhaven National Laboratory (BNL)) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Mashinistov, Ruslan (P.N. Lebedev Physical Institute) ; Svirin, Pavlo (Brookhaven National Laboratory (BNL))
/ATLAS Collaboration
The PanDA software is used for workload management on distributed grid resources by the ATLAS experiment at the LHC. An effort was launched to extend PanDA, called BigPanDA, to access HPC resources, funded by the US Department of Energy (DOE-ASCR) [...]
ATL-SOFT-SLIDE-2018-710.-
Geneva : CERN, 2018
Fulltext: PDF; External link: Original Communication (restricted to ATLAS)
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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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PanDA: Exascale Federation of Resources for the ATLAS Experiment
/ Barreiro Megino, Fernando Harald (The University of Texas at Arlington) ; De, Kaushik (The University of Texas at Arlington) ; Maeno, Tadashi (Brookhaven National Laboratory (BNL)) ; Wenaus, Torre (Brookhaven National Laboratory (BNL)) ; Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Klimentov, Alexei (Brookhaven National Laboratory (BNL)) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Panitkin, Sergey (Brookhaven National Laboratory (BNL)) ; Petrosyan, Artem (Joint Institute for Nuclear Research) ; Vukotic, Ilija (University of Chicago, Enrico Fermi Institute)
After a scheduled maintenance and upgrade period, the world’s largest and most powerful machine - the Large Hadron Collider(LHC) - is about to enter its second run at unprecedented energies. In order to exploit the scientific potential of the ma- chine, the experiments at the LHC face computational challenges with enormous data volumes that need to be analysed by thousand of physics users and compared to simulated data. [...]
ATL-SOFT-SLIDE-2015-372.-
Geneva : CERN, 2015
Fulltext: PPTX; External link: Original Communication (restricted to ATLAS)
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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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