Skip to main content
Article
Highly-parallelized simulation of a pixelated LArTPC on a GPU
Journal of Instrumentation (2023)
  • Michael A Kordosky, William & Mary
  • The DUNE Collaboration, The DUNE Collaboration
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 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.
Disciplines
Publication Date
April, 2023
DOI
https://www.doi.org/10.1088/1748-0221/18/04/P04034
Citation Information
Michael A Kordosky and The DUNE Collaboration. "Highly-parallelized simulation of a pixelated LArTPC on a GPU" Journal of Instrumentation Vol. 18 (2023)
Available at: http://works.bepress.com/michael-kordosky/22/