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CERN Document Server 找到 11 筆記錄  1 - 10下一個  跳到記錄: 檢索需時 0.69 秒. 
1.
The ATLAS experiment at the CERN Large Hadron Collider: a description of the detector configuration for Run 3 / ATLAS Collaboration
The ATLAS detector is installed in its experimental cavern at Point 1 of the CERN Large Hadron Collider. During Run 2 of the LHC, a luminosity of $\mathcal{L}=2\times 10^{34}\mathrm{cm}^{-2}\mathrm{s}^{-1}$ was routinely achieved at the start of fills, twice the design luminosity. [...]
arXiv:2305.16623; CERN-EP-2022-259.- Geneva : CERN, 2024-05-23 - 233 p. - Published in : JINST 19 (2024) P05063 Fulltext: 2305.16623 - PDF; document - PDF; External link: Previous draft version
In : The Large Hadron Collider and The Experiments for Run 3
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2.
Adapting ATLAS@Home to trusted and semi-trusted resources / Cameron, David (University of Oslo) ; Garonne, Vincent (University of Oslo) ; Millar, Paul ; Sun, Shaojun (Department of Physics, University of Wisconsin) ; Wu, Wenjing (University of Michigan, Department of Physics)
ATLAS@Home is a volunteer computing project which enables members of the public to contribute computing power to run simulations of the ATLAS experiment at CERN. [...]
ATL-SOFT-PROC-2020-011. - 2020. - 6 p.
Original Communication (restricted to ATLAS) - Full text - Fulltext from publisher
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3.
Adapting ATLAS@Home to trusted and semi-trusted resources / Cameron, David (University of Oslo) ; Garonne, Vincent (University of Oslo) ; Millar, Paul ; Sun, Shaojun (Department of Physics, University of Wisconsin) ; Wu, Wenjing (University of Michigan, Department of Physics) /ATLAS Collaboration
ATLAS@Home is a volunteer computing project which enables members of the public to contribute computing power to run simulations of the ATLAS experiment at CERN. The computing resources provided to ATLAS@Home increasingly come not only from traditional volunteers, but from data centres or office computers at institutes associated to ATLAS. [...]
ATL-SOFT-SLIDE-2019-767.- Geneva : CERN, 2019 - 13 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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4.
Backfilling the Grid with Containerized BOINC in the ATLAS computing / Wu, Wenjing (Institute of High Energy Physics, Chinese Academy of Sciences) ; Cameron, David (University of Oslo)
Virtualization is a commonly used solution for utilizing the opportunistic computing resources in the HEP field, as it provides a unified software and OS layer that the HEP computing tasks require over the heterogeneous opportunistic computing resources. [...]
ATL-SOFT-PROC-2018-060. - 2018. - 7 p.
Original Communication (restricted to ATLAS) - Full text
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5.
Advances in ATLAS@Home towards a major ATLAS computing resource / Cameron, David (University of Oslo) ; Wu, Wenjing (Institute of High Energy Physics, Chinese Academy of Sciences) ; Bogdanchikov, Alexander (Budker Institute of Nuclear Physics, Siberian Branch of Russian Academy of Sciences) ; Bianchi, Riccardo-Maria (University of Pittsburgh)
The volunteer computing project ATLAS@Home has been providing a stable computing resource for the ATLAS experiment since 2013. [...]
ATL-SOFT-PROC-2018-032. - 2018. - 8 p.
Original Communication (restricted to ATLAS) - Full text
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6.
Machine Learning in High Energy Physics Community White Paper / Albertsson, Kim (Lulea U.) ; Altoe, Piero (NVIDIA, Santa Clara) ; Anderson, Dustin (Caltech) ; Anderson, John ; Andrews, Michael (Carnegie Mellon U.) ; Araque Espinosa, Juan Pedro (LIP, Lisbon) ; Aurisano, Adam (Cincinnati U.) ; Basara, Laurent (INFN, Padua ; Padua U.) ; Bevan, Adrian (University Coll. London) ; Bhimji, Wahid (LBL, Berkeley) et al.
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. [...]
arXiv:1807.02876; FERMILAB-PUB-18-318-CD-DI-PPD.- 2018-10-18 - 27 p. - Published in : J. Phys.: Conf. Ser. 1085 (2018) 022008 Fulltext: 1807.02876 - PDF; Albertsson_2018_J._Phys.__Conf._Ser._1085_022008 - PDF; fulltext1681439 - PDF; fermilab-pub-18-318-cd-di-ppd - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server (fulltext available)
In : 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Seattle, WA, USA, 21 - 25 Aug 2017, pp.022008
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7.
Backfilling the Grid with Containerized BOINC in the ATLAS computing / Wu, Wenjing (Institute of High Energy Physics, Chinese Academy of Sciences) ; Cameron, David (University of Oslo) /ATLAS Collaboration
Virtualization is a commonly used solution for utilizing the opportunistic computing resources in the HEP field, as it provides a unified software and OS layer that the HEP computing tasks require over the heterogeneous opportunistic computing resources. However there is always performance penalty with virtualization, especially for short jobs which are always the case for volunteer computing tasks, the overhead of virtualization becomes a big portion in the wall time, hence it leads to low CPU efficiency of the jobs. [...]
ATL-SOFT-SLIDE-2018-410.- Geneva : CERN, 2018 - 22 p. Fulltext: ATL-SOFT-SLIDE-2018-410 - PPT; Backfilling the Grid with Containerized BOINC in the ATLAS computing - PDF; External link: Original Communication (restricted to ATLAS)
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8.
Advances in ATLAS@Home towards a major ATLAS computing resource / Cameron, David (University of Oslo) ; Wu, Wenjing (Institute of High Energy Physics, Chinese Academy of Sciences) ; Bogdanchikov, Alexander (Budker Institute of Nuclear Physics, Siberian Branch of Russian Academy of Sciences) ; Bianchi, Riccardo-Maria (University of Pittsburgh) /ATLAS Collaboration
The volunteer computing project ATLAS@Home has been providing a stable computing resource for the ATLAS experiment since 2013. It has recently undergone some significant developments and as a result has become one of the largest resources contributing to ATLAS computing, by expanding its scope beyond traditional volunteers and into exploitation of idle computing power in ATLAS data centres. [...]
ATL-SOFT-SLIDE-2018-409.- Geneva : CERN, 2018 - 12 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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9.
Volunteer computing experience with ATLAS@Home / Adam-Bourdarios, Claire (LAL, Univ. Paris-Sud, IN2P3/CNRS, Universite Paris-Saclay) ; Bianchi, Riccardo-Maria (University of Pittsburgh) ; Cameron, David (University of Oslo) ; Filipčič, Andrej (Jozef Stefan Institute) ; Lançon, Eric (Brookhaven National Laboratory (BNL)) ; Wu, Wenjing (Institute of High Energy Physics, Chinese Academy of Sciences)
ATLAS@Home is a volunteer computing project which allows the public to contribute to computing for the ATLAS experiment through their home or office computers. [...]
ATL-SOFT-PROC-2016-015. - 2017. - 8 p.
Original Communication (restricted to ATLAS) - IOP Open Access Article - Full text
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10.
Volunteer Computing Experience with ATLAS@Home / Cameron, David (University of Oslo) ; Filipcic, Andrej (Jozef Stefan Institute (SI)) ; Bourdarios, Claire (LAL, Univ. Paris-Sud, IN2P3/CNRS, Universite Paris-Saclay) ; Lan\c con, Eric (Brookhaven National Laboratory (BNL)) ; Wu, Wenjing (Institute of High Energy Physics, Chinese Academy of Sciences) /ATLAS Collaboration
ATLAS@Home is a volunteer computing project which allows the public to contribute to computing for the ATLAS experiment through their home or office computers. The project has grown continuously since its creation in mid-2014 and now counts almost 100,000 volunteers. [...]
ATL-SOFT-SLIDE-2016-637.- Geneva : CERN, 2016 - 12 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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