Highly-parallelized simulation of a pixelated LArTPC on a GPU

TL;DR

This paper introduces a GPU-accelerated, highly-parallelized microphysical simulator for liquid argon time projection chambers, significantly speeding up the simulation process for pixelated charge readouts in particle physics experiments.

Contribution

It presents the first full GPU-based microphysical simulator for LArTPCs with pixelated readout, achieving four orders of magnitude speedup over CPU implementations.

Findings

GPU simulation runs in about 1 ms for 1000 pixels

Achieves four orders of magnitude speedup compared to CPU

Results validated against prototype data

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.