CERN Accelerating science

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1.
Reinforcement Learning for Smart Caching at the CMS experiment / Tedeschi, Tommaso (INFN, Perugia ; Perugia U.) ; Tracolli, Mirco (INFN, Perugia ; Perugia U. ; Florence U.) ; Ciangottini, Diego (INFN, Perugia) ; Spiga, Daniele (INFN, Perugia ; Perugia U.) ; Storchi, Loriano (INFN, Perugia) ; Baioletti, Marco (Perugia U.) ; Poggioni, Valentina (Perugia U.) /CMS Collaboration
In the near future, High Energy Physics experiments’ storage and computing needs will go far above what can be achieved by only scaling current computing models or current infrastructures. Considering the LHC case, for 10 years a federated infrastructure (Worldwide LHC Computing Grid, WLCG) has been successfully developed. [...]
2021 - 16 p. - Published in : PoS ISGC2021 (2021) 009 Fulltext: PDF;
In : International Symposium on Grids & Clouds 2021 (ISGC 2021), Taipei, Taiwan, 22 - 26 Mar 2021, pp.009
2.
Strategies and performance of the CMS silicon tracker alignment during LHC Run 2 / CMS Collaboration
The strategies for and the performance of the CMS silicon tracking system alignment during the 2015-2018 data-taking period of the LHC are described. The alignment procedures during and after data taking are explained. [...]
arXiv:2111.08757; CMS-TRK-20-001; CERN-EP-2021-203; CMS-TRK-20-001-003.- Geneva : CERN, 2022-08-11 - 45 p. - Published in : Nucl. Instrum. Methods Phys. Res., A 1037 (2022) 166795 Fulltext: 2111.08757 - PDF; Publication - PDF; fermilab-pub-21-673-cms - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server
3.
The BondMachine toolkit: Enabling Machine Learning on FPGA / Mariotti, Mirko (U. Perugia (main) ; INFN, Perugia) ; Storchi, Loriano (INFN, Perugia ; U. Pescara (main)) ; Spiga, Daniele (INFN, Perugia) ; Salomoni, Davide (INFN, CNAF) ; Boccali, Tommaso (INFN, Pisa) ; Bonacorsi, Daniele (Bologna U.)
The BondMachine (BM) is an innovative prototype software ecosystem aimed at creating facilities where both hardware and software are co-designed, guaranteeing a full exploitation of fabric capabilities (both in terms of concurrency and heterogeneity) with the smallest possible power dissipation. In the present paper we will provide a technical overview of the key aspects of the BondMachine toolkit, highlighting the advancements brought about by the porting of Go code in hardware. [...]
SISSA, 2019 - 12 p. - Published in : PoS ISGC2019 (2019) 020 Fulltext: PDF;
In : International Symposium on Grids & Clouds 2019, Taipei, Taiwan, 31 Mar - 5 Apr 2019, pp.020
4.
A Real-Time Demonstrator for Track Reconstruction in the CMS L1 Track-Trigger System Based on Custom Associative Memories and High-Performance FPGAs / Fedi, Giacomo (INFN, Pisa ; Pisa U.) ; Palla, Fabrizio (INFN, Pisa ; Pisa U.) ; Gentsos, Christos (INFN, Perugia ; Perugia U.) ; Magalotti, Daniel (INFN, Perugia ; Perugia U.) ; Modak, Atanu (INFN, Perugia ; Perugia U.) ; Bilei, Gian Mario (INFN, Perugia ; Perugia U.) ; Roy Chowdhury, Suvankar (Saha Inst.) ; Checcucci, Bruno (INFN, Perugia ; Perugia U.) ; Tcherniakhovski, Denis (KIT, Karlsruhe) ; Galbit, Geoffrey Christian (Lyon, IPN) et al.
A Real-Time demonstrator based on the ATCA Pulsar-IIB custom board and on the Pattern Recognition Mezzanine (PRM) board has been developed as a flexible platform to test and characterize low-latency algorithms for track reconstruction and L1 Trigger generation in future High Energy Physics experiments. The demonstrator has been extensively used to test and characterize the Track-Trigger algorithms and architecture based on the use of the Associative Memory ASICs and of the PRM cards. [...]
SISSA, 2018 - 5 p. - Published in : PoS TWEPP-17 (2018) 138 Fulltext: PDF; External link: PoS server
In : Topical Workshop on Electronics for Particle Physics, Santa Cruz, Ca, United States Of America, 11 - 15 Sep 2017, pp.138
5.
Precision measurement of the structure of the CMS inner tracking system using nuclear interactions / CMS Collaboration
The structure of the CMS inner tracking system has been studied using nuclear interactions of hadrons striking its material. Data from proton-proton collisions at a center-of-mass energy of 13 TeV recorded in 2015 at the LHC are used to reconstruct millions of secondary vertices from these nuclear interactions. [...]
arXiv:1807.03289; CMS-TRK-17-001; CERN-EP-2018-144; CMS-TRK-17-001-003.- Geneva : CERN, 2018-10-29 - 41 p. - Published in : JINST 13 (2018) P10034 Fulltext: 1807.03289 - PDF; fulltext1682069 - PDF; Fulltext from Publisher: PDF; External link: Figures, tables and other information
6.
Track finding mezzanine for Level-1 triggering in HL-LHC experiments / Gentsos, Christos (INFN, Perugia ; Perugia U.) ; Fedi, Giacomo (INFN, Pisa ; Pisa U.) ; Magazzù, Guido (INFN, Pisa ; Pisa U.) ; Magalotti, Daniel (INFN, Perugia ; Perugia U.) ; Modak, Atanu (INFN, Perugia ; Perugia U.) ; Storchi, Loriano (INFN, Perugia ; Perugia U.) ; Palla, Fabrizio (INFN, Pisa ; Pisa U.) ; Bilei, Gian Mario (INFN, Perugia ; Perugia U.) ; Biesuz, Nicolò (INFN, Pisa ; Pisa U.) ; Roy Chowdhury, Suvankar (Saha Inst.) et al.
The increase of the luminosity in the High Luminosity upgrade of the CERN Large Hadron Collider (HL-LHC) will require the use of Tracker information in the evaluation of the Level-1 trigger in order to keep the trigger rate acceptable (i.e.: <;1MHz). In order to extract the track information within the latency constraints (<;5μs), a custom real-time system is necessary. [...]
2017 - 4 p. - Published in : 10.1109/MOCAST.2017.7937676

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