Highly-parallelized simulation of a pixelated LArTPC on a GPU

The DUNE collaboration

doi:10.1088/1748-0221/18/04/P04034

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The DUNE collaboration

Earth and Space Sciences Research Group

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

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.

Original language	English
Article number	P04034
Journal	Journal of Instrumentation
Volume	18
Issue number	4
DOIs	https://doi.org/10.1088/1748-0221/18/04/P04034
State	Published - 1 Apr 2023

Keywords

Detector modelling and simulations II (electric fields, charge transport, multiplication and induction, pulse formation, electron emission, etc)
Noble liquid detectors (scintillation, ionization, double-phase
Simulation methods and programs
Time projection Chambers (TPC)

Product types of Minciencias

A2 article - Q2

Access to Document

10.1088/1748-0221/18/04/P04034

Cite this

@article{5df01c1489004d069a894dba8d86368a,

title = "Highly-parallelized simulation of a pixelated LArTPC on a GPU",

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.",

keywords = "Detector modelling and simulations II (electric fields, charge transport, multiplication and induction, pulse formation, electron emission, etc), Noble liquid detectors (scintillation, ionization, double-phase, Simulation methods and programs, Time projection Chambers (TPC)",

author = "{The DUNE collaboration} and {Abed Abud}, A. and B. Abi and R. Acciarri and Acero, {M. A.} and Adames, {M. R.} and G. Adamov and M. Adamowski and D. Adams and M. Adinolfi and C. Adriano and A. Aduszkiewicz and J. Aguilar and Z. Ahmad and J. Ahmed and B. Aimard and F. Akbar and K. Allison and {Alonso Monsalve}, S. and M. Alrashed and C. Alt and A. Alton and R. Alvarez and P. Amedo and J. Anderson and Andrade, {D. A.} and C. Andreopoulos and M. Andreotti and Andrews, {M. P.} and F. Andrianala and S. Andringa and N. Anfimov and {Anic{\'e}zio Campanelli}, {W. L.} and A. Ankowski and M. Antoniassi and M. Antonova and A. Antoshkin and S. Antusch and A. Aranda-Fernandez and L. Arellano and Arnold, {L. O.} and Arroyave, {M. A.} and J. Asaadi and A. Ashkenazi and L. Asquith and A. Aurisano and V. Aushev and D. Autiero and M. Ayala-Torres and F. Azfar and A. Back and H. Back and Back, {J. J.} and I. Bagaturia and L. Bagby and N. Balashov and S. Balasubramanian and P. Baldi and W. 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Zambelli and B. Zamorano and A. Zani and L. Zazueta and Zeller, {G. P.} and J. Zennamo and K. Zeug and C. Zhang and S. Zhang and Y. Zhang and M. Zhao and E. Zhivun and Zimmerman, {E. D.} and S. Zucchelli and J. Zuklin and V. Zutshi and R. Zwaska",

note = "Funding Information: This work was supported by CNPq, FAPERJ, FAPEG and FAPESP, Brazil; CFI, IPP and NSERC, Canada; CERN; M{\v S}MT, Czech Republic; ERDF, H2020-EU and MSCA, European Union; CNRS/IN2P3 and CEA, France; INFN, Italy; FCT, Portugal; NRF, South Korea; CAM, Fundaci{\'o}n “La Caixa”, Junta de Andaluc{\'i}a-FEDER, MICINN, and Xunta de Galicia, Spain; SERI and SNSF, Switzerland; T{\"U}BİTAK, 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. Publisher Copyright: {\textcopyright} 2023 CERN.",

year = "2023",

month = apr,

day = "1",

doi = "10.1088/1748-0221/18/04/P04034",

language = "Ingl{\'e}s",

volume = "18",

journal = "Journal of Instrumentation",

issn = "1748-0221",

publisher = "IOP Publishing Ltd.",

number = "4",

}

TY - JOUR

T1 - Highly-parallelized simulation of a pixelated LArTPC on a GPU

AU - The DUNE collaboration

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N1 - Funding Information: 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. Publisher Copyright: © 2023 CERN.

PY - 2023/4/1

Y1 - 2023/4/1

N2 - 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.

AB - 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.

KW - Detector modelling and simulations II (electric fields, charge transport, multiplication and induction, pulse formation, electron emission, etc)

KW - Noble liquid detectors (scintillation, ionization, double-phase

KW - Simulation methods and programs

KW - Time projection Chambers (TPC)

UR - http://www.scopus.com/inward/record.url?scp=85160013107&partnerID=8YFLogxK

U2 - 10.1088/1748-0221/18/04/P04034

DO - 10.1088/1748-0221/18/04/P04034

M3 - Artículo

AN - SCOPUS:85160013107

SN - 1748-0221

VL - 18

JO - Journal of Instrumentation

JF - Journal of Instrumentation

IS - 4

M1 - P04034

ER -

Highly-parallelized simulation of a pixelated LArTPC on a GPU

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