Highly-parallelized simulation of a pixelated LArTPC on a GPU
Highly-parallelized simulation of a pixelated LArTPC on a GPU
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DOI：
10.1088/1748-0221/18/04/p04034
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发表时间：
2022-12
影响因子：
1.3
通讯作者：
D. C. A. A. Abud-D.-C.-A.-A.-Abud-2120181467;B. Abi;R. Acciarri;M. A. Acero;M. Adames;G. Adamov;M. Adamowski;D. Adams
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文献类型：
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作者：
D. C. A. A. Abud-D.-C.-A.-A.-Abud-2120181467;B. Abi;R. Acciarri;M. A. Acero;M. Adames;G. Adamov;M. Adamowski;D. Adams
图形处理单元（GPGPU）上通用计算的快速发展使得在粒子物理实验中能够实现高度并行化的蒙特卡罗模拟链。鉴于这种技术所使用的大量通道，该技术特别适用于对时间投影室的像素化电荷读出进行模拟。在此，我们介绍了为DUNE近探测器开发的配备光读出和像素化电荷读出的液态氩时间投影室（LArTPC）的首个完整微观物理模拟器的实现。该软件采用了一套端到端的GPU优化算法来实现。这些算法是用Python编写的，并使用Numba（一种针对Python和NumPy指令子集的即时编译器）转换为CUDA内核。与等效的CPU版本相比，GPU实现的速度提高了四个数量级。在GPU上模拟10³个像素上感应的电流大约需要1毫秒，而在CPU上则大约需要10秒。模拟结果与来自像素读出LArTPC原型的数据进行了比较。
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.