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CERN Document Server 2,047 elementer funnet  1 - 10nesteslutt  gå til element: Søket tok 0.42 sekunder. 
1.
Real-time reconstruction of pixel vertex detectors with FPGAs / LHCb Real-Time Analysis project Collaboration
The LHCb experiment is undergoing a major upgrade in view of Run-3, in which the complete detector will be read out, and events fully reconstructed, at the full LHC crossing rate (averaging 30 MHz). One of the key steps of event reconstruction is finding tracks in the new, high precision pixel vertex detector (VELOPIX) [...]
SISSA, 2020 - 10 p. - Published in : PoS Vertex2019 (2020) 047 Fulltext: PDF;
In : Vertex 2019: 28th International Workshop on Vertex Detectors, Lopud Island, Croatia, 13 - 18 Oct 2019, pp.047
2.
Real-time cluster finding for LHCb silicon pixel VELO detector using FPGA / Lazzari, Federico (U. Siena (main) ; INFN, Pisa) ; Bassi, Giovanni (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Cenci, Riccardo (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Morello, Michael J (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Punzi, Giovanni (INFN, Pisa ; Pisa U.)
In the Run-3 of LHCb, the High Level Trigger will have to process events at full LHC collision rate (30 MHz). This is a very challenging goal, and delegating some low-level tasks to FPGA accelerators can be very helpful by saving precious computing time. [...]
2020 - 6 p. - Published in : J. Phys.: Conf. Ser. 1525 (2020) 012044
In : 19th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Saas Fee, Switzerland, 11 - 15 Mar 2019, pp.012044
3.
An 'artificial retina' processor for track reconstruction at the full LHC crossing rate / Abba, A (INFN, Milan ; Milan Polytechnic) ; Bedeschi, F (INFN, Pisa) ; Caponio, F (INFN, Milan ; Milan Polytechnic) ; Cenci, R (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Citterio, M (INFN, Milan) ; Cusimano, A (INFN, Milan ; Milan Polytechnic) ; Fu, J (INFN, Milan) ; Geraci, A (INFN, Milan ; Milan Polytechnic) ; Grizzuti, M (INFN, Milan ; Milan Polytechnic) ; Lusardi, N (INFN, Milan ; Milan Polytechnic) et al.
We present the latest results of an R&D; study for a specialized processor capable of reconstructing, in a silicon pixel detector, high-quality tracks from high-energy collision events at 40 MHz. The processor applies a highly parallel pattern-recognition algorithm inspired to quick detection of edges in mammals visual cortex. [...]
FERMILAB-PUB-16-184-CMS.- 2016 - 3 p. - Published in : Nucl. Instrum. Methods Phys. Res., A 824 (2016) 260-262 Fulltext: PDF;
In : Frontier Detectors for Frontier Physics: 13th Pisa Meeting on Advanced Detectors, La Biodola, Isola D'elba, Italy, 24 - 30 May 2015, pp.260-262
4.
First Results of an “Artificial Retina” Processor Prototype / Cenci, Riccardo (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Bedeschi, Franco (Pisa, Scuola Normale Superiore) ; Marino, Pietro (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Morello, Michael J (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Ninci, Daniele (INFN, Pisa ; Pisa U.) ; Piucci, Alessio (INFN, Pisa ; Pisa U.) ; Punzi, Giovanni (INFN, Pisa ; Pisa U.) ; Ristori, Luciano (Fermilab) ; Spinella, Franco (INFN, Pisa) ; Stracka, Simone (INFN, Pisa ; Pisa U.) et al.
We report on the performance of a specialized processor capable of reconstructing charged particle tracks in a realistic LHC silicon tracker detector, at the same speed of the readout and with sub-microsecond latency. The processor is based on an innovative pattern-recognition algorithm, called “artificial retina algorithm”, inspired from the vision system of mammals. [...]
FERMILAB-CONF-16-623-CMS.- 2016 - 10 p. - Published in : EPJ Web Conf. 127 (2016) 00005 EDP Science Open Access Article: PDF; External link: FERMILABCONF
In : Connecting the Dots, Vienna, Austria, 22 - 24 Feb 2016, pp.00005
5.
A real-time FPGA-based cluster finding algorithm for LHCb silicon pixel detector / Bassi, Giovanni (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Giambastiani, Luca (Padua U.) ; Lazzari, Federico (INFN, Pisa ; INFN, Siena ; Siena U.) ; Morello, Michael J (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Pajero, Tommaso (Oxford U.) ; Punzi, Giovanni (INFN, Pisa ; Pisa U.)
Starting from the next LHC run, the upgraded LHCb High Level Trigger will process events at the full LHC collision rate (averaging 30 MHz). This challenging goal, tackled using a large and heterogeneous computing farm, can be eased addressing lowest-level, more repetitive tasks at the earliest stages of the data acquisition chain. [...]
2021 - 8 p. - Published in : EPJ Web Conf. 251 (2021) 04016 Fulltext: PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.04016
6.
A Specialized Processor for Track Reconstruction at the LHC Crossing Rate / Abba, A. (Milan Polytechnic ; INFN, Milan) ; Bedeschi, F. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Citterio, M. (Milan Polytechnic ; INFN, Milan) ; Caponio, F. (Milan Polytechnic ; INFN, Milan) ; Cusimano, A. (Milan Polytechnic ; INFN, Milan) ; Geraci, A. (Milan Polytechnic ; INFN, Milan) ; Marino, P. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Morello, M.J. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Neri, N. (Milan Polytechnic ; INFN, Milan) ; Punzi, G. (INFN, Pisa ; Pisa, Scuola Normale Superiore) et al.
We present the results of an R&D; study of a specialized processor capable of precisely reconstructing events with hundreds of charged-particle tracks in pixel detectors at 40 MHz, thus suitable for processing LHC events at the full crossing frequency. For this purpose we design and test a massively parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature. [...]
arXiv:1406.7220.- 2014 - 12 p. - Published in : JINST 9 (2014) C09001 Fulltext: PDF; IOP Open Access article: PDF; External link: Preprint
In : International Conference on Instrumentation for Colliding Beam Physics 2014, Novosibirsk, Russia, 24 Feb - 1 Mar 2014, pp.C09001
7.
Real-time reconstruction of long-lived particles at LHCb using FPGAs / Cenci, Riccardo (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Di Luca, Andrea (INFN, Pisa ; Pisa U.) ; Lazzari, Federico (INFN, Pisa ; Siena U.) ; Morello, Michael J. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Punzi, Giovanni (INFN, Pisa ; Pisa U.) /LHCb Collaboration
Finding tracks downstream of the magnet at the earliest LHCb trigger level is not part of the baseline plan of the upgrade trigger, on account of the significant CPU time required to execute the search. Many long-lived particles, such as $K^0_S$ and strange baryons, decay after the vertex track detector, so that their reconstruction efficiency is limited. [...]
arXiv:2006.11067.- 2020-07-08 - 7 p. - Published in : J. Phys.: Conf. Ser. 1525 (2020) 012101 Fulltext: J Phys Conf Ser 1525 012101 - PDF; 2006.11067 - PDF;
In : 19th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Saas Fee, Switzerland, 11 - 15 Mar 2019, pp.012101
8.
The artificial retina processor for track reconstruction at the LHC crossing rate / Abba, A. (INFN, Milan ; Milan Polytechnic) ; Bedeschi, F. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Citterio, M. (INFN, Milan ; Milan Polytechnic) ; Caponio, F. (INFN, Milan ; Milan Polytechnic) ; Cusimano, A. (INFN, Milan ; Milan Polytechnic) ; Geraci, A. (INFN, Milan ; Milan Polytechnic) ; Marino, P. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Morello, M.J. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Neri, N. (INFN, Milan ; Milan Polytechnic) ; Punzi, G. (INFN, Pisa ; Pisa, Scuola Normale Superiore) et al.
We present results of an R&D; study for a specialized processor capable of precisely reconstructing, in pixel detectors, hundreds of charged-particle tracks from high-energy collisions at 40 MHz rate. We apply a highly parallel pattern-recognition algorithm, inspired by studies of the processing of visual images by the brain as it happens in nature, and describe in detail an efficient hardware implementation in high-speed, high-bandwidth FPGA devices. [...]
arXiv:1409.1565; FERMILAB-CONF-14-610-CMS.- 2015-03-16 - 9 p. - Published in : JINST 10 (2015) C03018 Fulltext: arXiv:1409.1565 - PDF; fermilab-conf-14-610-cms - PDF; External link: Fermilab Accepted Manuscript
In : WIT2014 Workshop on Intelligent Trackers, Philadelphia, USA, 14 - 16 May 2014, pp.C03018
9.
FPGA-based real-time data processing for accelerating reconstruction at LHCb / LHCb Collaboration
In Run-3, beginning in 2022, the LHCb software trigger will start reconstructing events at the LHC average crossing rate of 30 MHz. Within the upgraded DAQ system, LHCb established a testbed for new heterogeneous computing solutions for real-time event reconstruction, in view of future runs at even higher luminosities. [...]
arXiv:2201.08119.- 2022-04-06 - 8 p.
- Published in : JINST Fulltext: PDF;
In : TWEPP 2021 Topical Workshop on Electronics for Particle Physics, Online, Online, 20 - 24 Sep 2021, pp.C04011
10.
Simulation and performance of an artificial retina for 40 MHz track reconstruction / Abba, A. (INFN, Milan ; Milan Polytechnic) ; Bedeschi, F. (INFN, Pisa ; U. Pisa (main)) ; Citterio, M. (INFN, Milan ; Milan Polytechnic) ; Caponio, F. (INFN, Milan ; Milan Polytechnic) ; Cusimano, A. (INFN, Milan ; Milan Polytechnic) ; Geraci, A. (INFN, Milan ; Milan Polytechnic) ; Marino, P. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Morello, M.J. (INFN, Pisa ; Pisa, Scuola Normale Superiore) ; Neri, N. (INFN, Milan ; Milan Polytechnic) ; Punzi, G. (INFN, Pisa ; U. Pisa (main)) et al.
We present the results of a detailed simulation of the artificial retina pattern-recognition algorithm, designed to reconstruct events with hundreds of charged-particle tracks in pixel and silicon detectors at LHCb with LHC crossing frequency of 40MHz. The detailed geometry and charged-particle activity of a large tracking detector are simulated and used to assess the performance of the artificial retina algorithm. [...]
arXiv:1409.0898.- 2015-03-05 - 9 p. - Published in : JINST 10 (2015) C03008 Fulltext: PDF; External link: FERMILABCONF
In : WIT2014 Workshop on Intelligent Trackers, Philadelphia, USA, 14 - 16 May 2014, pp.C03008

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