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Published January 1, 2023 | Version v1
Journal article Open

Highly-parallelized simulation of a pixelated LArTPC on a GPU

Creators

  • 1. European Org Nucl Res, CERN, F-1211 Meyrin, France
  • 2. Univ Oxford, Oxford OX1 3RH, England
  • 3. Fermilab Natl Accelerator Lab, Batavia, IL 60510 USA
  • 4. Univ Atlantico, Barranquilla, Atlantico, Colombia
  • 5. Univ Tecnol Fed Parana, Curitiba, Brazil
  • 6. Georgian Tech Univ, Tbilisi, Georgia
  • 7. Brookhaven Natl Lab, Upton, NY 11973 USA
  • 8. Univ Bristol, Bristol BS8 1TL, England
  • 9. Univ Estadual Campinas, BR-13083970 Campinas, SP, Brazil
  • 10. Univ Houston, Houston, TX 77204 USA
  • 11. Lawrence Berkeley Natl Lab, Berkeley, CA 94720 USA
  • 12. Variable Energy Cyclotron Ctr, Kolkata 700064, W Bengal, India
  • 13. Univ Warwick, Coventry CV4 7AL, England
  • 14. Univ Savoie Mt Blanc, Uni Grenoble Alpes, CNRS, Lab Annecy Phys Particules,LAPP IN2P3, F-74000 Annecy, France
  • 15. Univ Rochester, Rochester, NY 14627 USA
  • 16. Univ Colorado Boulder, Boulder, CO 80309 USA
  • 17. Kansas State Univ, Manhattan, KS 66506 USA
  • 18. Swiss Fed Inst Technol, Zurich, Switzerland

Description

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.

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