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1.
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Prototype of the Russian Scientific Data Lake
/ Alekseev, Aleksandr (Moscow State U. ; Moscow, INR ; Andres Bello Natl. U.) ; Espinal, Xavier (CERN) ; Jezequel, Stephane (Annecy, LAPP) ; Kiryanov, Andrey (Moscow State U. ; St. Petersburg, INP) ; Klimentov, Alexei (Brookhaven) ; Korchuganova, Tatiana (Moscow State U. ; Moscow, INR ; Andres Bello Natl. U.) ; Mitsyn, Valeri (Dubna, JINR) ; Oleynik, Danila (Moscow State U. ; Dubna, JINR) ; Smirnov, Alexander (Moscow State U. ; Moscow Phys. Eng. Inst.) ; Smirnov, Sergei (Moscow Phys. Eng. Inst.) et al.
The High Luminosity phase of the LHC, which aims for a tenfold increase in the luminosity of proton-proton collisions is expected to start operation in eight years. An unprecedented scientific data volume at the multiexabyte scale will be delivered to particle physics experiments at CERN. [...]
2021 - 10 p.
- Published in : EPJ Web Conf. 251 (2021) 02031
Fulltext: PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.02031
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On the road to a scientific data lake for the High Luminosity LHC era
/ Alekseev, Aleksandr (Moscow State U. ; Andres Bello Natl. U. ; Moscow, INR) ; Campana, Simone (CERN) ; Espinal, Xavier (CERN) ; Jezequel, Stephane (Annecy, LAPP) ; Kirianov, Andrey (St. Petersburg, INP) ; Klimentov, Alexei (Brookhaven) ; Korchuganova, Tatiana (Moscow State U. ; Andres Bello Natl. U. ; Moscow, INR) ; Mitsyn, Valeri (Dubna, JINR) ; Oleynik, Danila (Dubna, JINR) ; Smirnov, Serge (Dubna, JINR ; Moscow Phys. Eng. Inst.) et al.
The experiments at CERN’s Large Hadron Collider use the Worldwide LHC Computing Grid, the WLCG, for its distributed computing infrastructure. Through the distributed workload and data management systems, they provide seamless access to hundreds of grid, HPC and cloud based computing and storage resources that are distributed worldwide to thousands of physicists. [...]
2020 - 11 p.
- Published in : Int. J. Mod. Phys. A 35 (2020) 2030022
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3.
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Building and using containers at HPC centres for the ATLAS experiment
/ Benjamin, Douglas (Duke U.) ; Childers, Taylor (Argonne (main)) ; Lesny, David (Illinois U., Urbana) ; Oleynik, Danila (Texas U., Arlington) ; Panitkin, Sergey (Brookhaven) ; Tsulaia, Vakho (LBL, Berkeley) ; Yang, Wei (SLAC) ; Zhao, Xin (Brookhaven)
/ATLAS Collaboration
The HPC environment presents several challenges to the ATLAS experiment in running their automated computational workflows smoothly and efficiently, in particular regarding issues such as software distribution and I/O load. A vital component of the LHC Computing Grid, CVMFS, is not always available in HPC environments. [...]
EDP Sciences, 2019 - 8 p.
- Published in : EPJ Web Conf. 214 (2019) 07005
Fulltext: PDF;
In : 23rd International Conference on Computing in High Energy and Nuclear Physics, CHEP 2018, Sofia, Bulgaria, 9 - 13 Jul 2018, pp.07005
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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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7.
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Large scale fine grain simulation workflows ("Jumbo Jobs") on HPC's
/ Benjamin, Douglas (Argonne National Laboratory) ; Maeno, Tadashi (Brookhaven National Laboratory (BNL)) ; Nilsson, Paul (Brookhaven National Laboratory (BNL)) ; Tsulaia, Vakhtang (Lawrence Berkeley National Laboratory and University of California, Berkeley) ; Guan, Wen (Department of Physics, University of Wisconsin) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Javurkova, Martina (University of Massachusetts, Amherst) ; Magini, Nicolo (Iowa State University) ; Childers, John Taylor (Argonne National Laboratory)
/ATLAS Collaboration
The ATLAS experiment is using large High Performance Computers (HPC's) and fine grained simulation workflows (Event Service) to produce fully simulated events in an efficient manner. ATLAS has developed a new software component (Harvester) which provides resource provisioning and workload shaping. [...]
ATL-SOFT-SLIDE-2019-807.-
Geneva : CERN, 2019 - 13 p.
Fulltext: PPTX; 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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8.
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Fine-Grained Processing Towards HL-LHC Computing in ATLAS
/ Benjamin, Doug (Duke U.) ; Calafiura, Paolo (LBNL, Berkeley) ; Childers, Taylor (Argonne) ; De, Kaushik (Texas U., Arlington) ; Di Girolamo, Alessandro (CERN) ; Fullana, Esteban (Valencia U.) ; Guan, Wen (Wisconsin U., Madison) ; Maeno, Tadashi (Brookhaven Natl. Lab.) ; Magini, Nicolo (U. Genoa (main)) ; Nilsson, Paul (Brookhaven Natl. Lab.) et al.
/ATLAS
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. [...]
2018 - 1 p.
- Published in : 10.1109/eScience.2018.00083
In : 14th eScience IEEE International Conference, Amsterdam, Netherlands, 29 Oct - 1 Nov 2018, pp.338
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9.
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Building and Using Containers on HPCs for the ATLAS Experiment
/ Yang, Wei (SLAC National Accelerator Laboratory) ; Benjamin, Douglas (Argonne National Laboratory) ; Childers, John Taylor (Argonne National Laboratory) ; Lesny, David (University of Illinois at Urbana-Champaign) ; Oleynik, Danila (Joint Institute for Nuclear Research) ; Panitkin, Sergey (Brookhaven National Laboratory (BNL)) ; Tsulaia, Vakhtang (Lawrence Berkeley National Laboratory and University of California, Berkeley) ; Zhao, Xin (Brookhaven National Laboratory (BNL))
The HPC environment presents several challenges to the ATLAS experiment in running their automated computational workflow smoothly and efficiently, in particular on issues such as software distribution and IO load. [...]
ATL-SOFT-PROC-2018-047.
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2018.
Original Communication (restricted to ATLAS) - Full text
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