Title
Highly-parallelized simulation of a pixelated LArTPC on a GPU
Date Issued
01 April 2023
Access level
open access
Resource Type
journal article
Author(s)
Abed Abud A.
Abi B.
Acciarri R.
Acero M.A.
Adames M.R.
Adamov G.
Adamowski M.
Adams D.
Adinolfi M.
Adriano C.
Aduszkiewicz A.
Aguilar J.
Ahmad Z.
Ahmed J.
Aimard B.
Akbar F.
Allison K.
Alonso Monsalve S.
Alrashed M.
Alt C.
Alton A.
Alvarez R.
Amedo P.
Anderson J.
Andrade D.A.
Andreopoulos C.
Andreotti M.
Andrews M.P.
Andrianala F.
Andringa S.
Anfimov N.
Anicézio Campanelli W.L.
Ankowski A.
Antoniassi M.
Antonova M.
Antoshkin A.
Antusch S.
Aranda-Fernandez A.
Arellano L.
Arnold L.O.
Arroyave M.A.
Asaadi J.
Ashkenazi A.
Asquith L.
Aurisano A.
Aushev V.
Autiero D.
Ayala-Torres M.
Azfar F.
Back A.
Back H.
Back J.J.
Bagaturia I.
Bagby L.
Balashov N.
Balasubramanian S.
Baldi P.
Baldini W.
Baller B.
Bambah B.
Barao F.
Barenboim G.
Barham Alzás P.
Barker G.J.
Barkhouse W.
Barnes C.
Barr G.
Barranco Monarca J.
Barros A.
Barros N.
Barrow J.L.
Basharina-Freshville A.
Bashyal A.
Basque V.
Batchelor C.
Battat J.B.R.
Battisti F.
Bay F.
Bazetto M.C.Q.
Bazo Alba J.L.L.
Beacom J.F.
Bechetoille E.
Behera B.
Belchior E.
Bellantoni L.
Bellettini G.
Bellini V.
Beltramello O.
Benekos N.
Benitez Montiel C.
Benjamin D.
Bento Neves F.
Berger J.
Berkman S.
Bernardini P.
Berner R.M.
Bersani A.
Bertolucci S.
Betancourt M.
Betancur Rodríguez A.
Publisher(s)
Institute of Physics
Abstract
The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 103 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype.
Volume
18
Issue
4
Language
English
OCDE Knowledge area
Ingeniería eléctrica, Ingeniería electrónica
Ingeniería de sistemas y comunicaciones
Física y Astronomía
Subjects
Scopus EID
2-s2.0-85160013107
Source
Journal of Instrumentation
ISSN of the container
17480221
Sponsor(s)
This work was supported by CNPq, FAPERJ, FAPEG and FAPESP, Brazil; CFI, IPP and NSERC, Canada; CERN; MŠMT, Czech Republic; ERDF, H2020-EU and MSCA, European Union; CNRS/IN2P3 and CEA, France; INFN, Italy; FCT, Portugal; NRF, South Korea; CAM, Fundación “La Caixa”, Junta de Andalucía-FEDER, MICINN, and Xunta de Galicia, Spain; SERI and SNSF, Switzerland; TÜBİTAK, Turkey; The Royal Society and UKRI/STFC, United Kingdom; DOE and NSF, United States of America. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231.
Sources of information:
Directorio de Producción Científica
Comisión Nacional de Investigación y Desarrollo Aeroespacial