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Highly-parallelized simulation of a pixelated LArTPC on a GPU
Journal article   Open access   Peer reviewed

Highly-parallelized simulation of a pixelated LArTPC on a GPU

DUNE Collaboration, A. Abed Abud, B. Abi, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, D. Adams, M. Adinolfi, …
Journal of instrumentation, v 18(4)
26 Apr 2023
url
https://doi.org/10.1088/1748-0221/18/04/p04034View
Published, Version of Record (VoR)CC BY V4.0 Open
url
https://doi.org/10.1088/1748-0221/18/04/P04034View
Published, Version of Record (VoR) Open

Abstract

computing INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY PHYSICS OF ELEMENTARY PARTICLES AND FIELDS simulation methods and programs time projection chambers
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 10^3 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.

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Domestic collaboration
International collaboration
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Instruments & Instrumentation
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