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CERN Document Server 2,026 ჩანაწერია ნაპოვნი  1 - 10შემდეგიდასასრული  ჩანაწერთან გადასვლა: ძიებას დასჭირდა 0.45 წამი. 
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Accelerating Machine Learning Inference with GPUs in ProtoDUNE Data Processing / Cai, Tejin (York U., Canada) ; Herner, Kenneth (Fermilab) ; Yang, Tingjun (Fermilab) ; Wang, Michael (Fermilab) ; Flechas, Maria Acosta (Fermilab) ; Harris, Philip (MIT) ; Holzman, Burt (Fermilab) ; Pedro, Kevin (Fermilab) ; Tran, Nhan (Fermilab)
We study the performance of a cloud-based GPU-accelerated inference server to speed up event reconstruction in neutrino data batch jobs. Using detector data from the ProtoDUNE experiment and employing the standard DUNE grid job submission tools, we attempt to reprocess the data by running several thousand concurrent grid jobs, a rate we expect to be typical of current and future neutrino physics experiments. [...]
arXiv:2301.04633; FERMILAB-PUB-22-944-ND-PPD-SCD.- 2023 - 13 p. - Published in : Comput. Softw. Big Sci. 7 (2023) 11 Fulltext: 2301.04633 - PDF; Publication - PDF; FERMILAB-PUB-22-944-ND-PPD-SCD - PDF; External link: Fermilab Accepted Manuscript
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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Deep Learning strategies for ProtoDUNE raw data denoising / Rossi, Marco (Università degli Studi e INFN Milano (IT)) ; Vallecorsa, Sofia (CERN)
In this work we investigate different machine learning based strategies for denoising raw simulation data from ProtoDUNE experiment. [...]
CERN-IT-2021-001. - 2021. - 9 p.
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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FPGA-accelerated machine learning inference as a service for particle physics computing / Duarte, Javier (Fermilab) ; Harris, Philip (MIT) ; Hauck, Scott (Washington U., Seattle) ; Holzman, Burt (Fermilab) ; Hsu, Shih-Chieh (Washington U., Seattle) ; Jindariani, Sergo (Fermilab) ; Khan, Suffian (Microsoft, Redmond) ; Kreis, Benjamin (Fermilab) ; Lee, Brian (Microsoft, Redmond) ; Liu, Mia (Fermilab) et al.
New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains. The growing applications of machine learning algorithms in particle physics for simulation, reconstruction, and analysis are naturally deployed on such platforms. [...]
arXiv:1904.08986; FERMILAB-PUB-19-170-CD-CMS-E-ND.- 2019-10-14 - 16 p. - Published in : Comput. Softw. Big Sci. 3 (2019) 13 Fulltext: 1904.08986 - PDF; fermilab-pub-19-170-cd-cms-e-nd - PDF; Fulltext from Publisher: PDF; External link: Fermilab Accepted Manuscript
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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Deep Learning strategies for ProtoDUNE raw data denoising / Rossi, Marco (speaker) (CERN)
In this work we investigate different machine learning based strategies for denoising raw simulation data from ProtoDUNE experiment. ProtoDUNE detector is hosted by CERN and it aims to test and calibrate the technologies for DUNE, a forthcoming experiment in neutrino physics. [...]
2021 - 1537. Conferences; 25th International Conference on Computing in High Energy & Nuclear Physics External links: Talk details; Event details In : 25th International Conference on Computing in High Energy & Nuclear Physics
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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Deep Learning strategies for ProtoDUNE raw data denoising / Rossi, Marco (CERN ; INFN, Milan ; Milan U.) ; Vallecorsa, Sofia (CERN)
In this work, we investigate different machine learning-based strategies for denoising raw simulation data from the ProtoDUNE experiment. The ProtoDUNE detector is hosted by CERN and it aims to test and calibrate the technologies for DUNE, a forthcoming experiment in neutrino physics. [...]
arXiv:2103.01596.- 2022-01-07 - 9 p.
- Published in : Comput. Softw. Big Sci.: 6 (2022) , no. 1, pp. 2 Fulltext: 2103.01596 - PDF; document - PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.2
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation / Holzman, Burt (Fermilab) ; Bauerdick, Lothar A.T. (Fermilab) ; Bockelman, Brian (Nebraska U.) ; Dykstra, Dave (Fermilab) ; Fisk, Ian (New York U.) ; Fuess, Stuart (Fermilab) ; Garzoglio, Gabriele (Fermilab) ; Girone, Maria (CERN) ; Gutsche, Oliver (Fermilab) ; Hufnagel, Dirk (Fermilab) et al.
Historically, high energy physics computing has been performed on large purpose-built computing systems. These began as single-site compute facilities, but have evolved into the distributed computing grids used today. [...]
arXiv:1710.00100; FERMILAB-PUB-17-092-CD.- 2017-09-29 - 15 p. - Published in : Comput. Softw. Big Sci. 1 (2017) 1 Fulltext: arxiv:1710.00100 - PDF; fermilab-pub-17-092-cd - PDF; External link: Fermilab Accepted Manuscript
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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ProtoDUNE revealed
Published in: CERN Courier Volume 57, Number 2, March 2017
Geneva : CERN, 2017
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP / Amadio, G. (CERN) ; Ananya, A. (CERN) ; Apostolakis, J. (CERN) ; Bandieramonte, M. (CERN ; Pittsburgh U.) ; Banerjee, S. (Fermilab) ; Bhattacharyya, A. (Bhabha Atomic Res. Ctr.) ; Bianchini, C. (Sao Paulo, IFT ; Mackenzie Presbiteriana U.) ; Bitzes, G. (CERN) ; Canal, P. (Fermilab) ; Carminati, F. (CERN) et al.
Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. [...]
arXiv:2005.00949; FERMILAB-PUB-20-200-SCD.- 2021-01-03 - 34 p. - Published in : Comput. Softw. Big Sci. 5 (2021) 3 Fulltext: fermilab-pub-20-200-scd - PDF; 2005.00949 - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server (fulltext available)
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC / DUNE Collaboration
DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6x6x6m3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. [...]
arXiv:2203.16134; CERN-EP-DRAFT-MISC-2022-003; FERMILAB-PUB-22-242-LBNF; CERN-EP-DRAFT-MISC-2022-003; FERMILAB-PUB-22-242-LBNF.- 2022-07-16 - 31 p. - Published in : Eur. Phys. J. C 82 (2022) 618 Fulltext: 2203.16134 - PDF; jt - PDF; Publication - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server
დეტალური ჩანაწერი - მსგავსი ჩანაწერები
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 PROTODUNE DETECTORS AT CERN
LES DÉTECTEURS PROTODUNE AU CERN
Reference: Poster-2019-939
Keywords:  opendays2019
Original source: OD19_PR_ProtoDUNE_2.pdf
Created: 2019. -1 p

Dual-phase ProtoDUNE and inside the cryostat.ProtoDUNE à phase double et à l'intérieur du cryostat.

 		© CERN Geneva

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