Accelerating IceCube’s Photon Propagation Code with CUDA

Author:

Schwanekamp Hendrik,Hohl Ramona,Chirkin Dmitry,Gibbs Tom,Harnisch Alexander,Kopper Claudio,Messmer Peter,Mehta Vishal,Olivas Alexander,Riedel BenediktORCID,Rongen Martin,Schultz David,van Santen Jakob

Abstract

AbstractThe IceCube Neutrino Observatory is a cubic kilometer neutrino detector located at the geographic South Pole designed to detect high-energy astrophysical neutrinos. To thoroughly understand the detected neutrinos and their properties, the detector response to signal and background has to be modeled using Monte Carlo techniques. An integral part of these studies are the optical properties of the ice the observatory is built into. The simulated propagation of individual photons from particles produced by neutrino interactions in the ice can be greatly accelerated using graphics processing units (GPUs). In this paper, we (a collaboration between NVIDIA and IceCube) reduced the propagation time per photon by a factor of up to 3 on the same GPU. We achieved this by porting the OpenCL parts of the program to CUDA and optimizing the performance. This involved careful analysis and multiple changes to the algorithm. We also ported the code to NVIDIA OptiX to handle the collision detection. The hand-tuned CUDA algorithm turned out to be faster than OptiX. It exploits detector geometry and only a small fraction of photons ever travel close to one of the detectors.

Funder

Division of Antarctic Sciences

Publisher

Springer Science and Business Media LLC

Subject

Nuclear and High Energy Physics,Computer Science (miscellaneous),Software

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Search for Galactic Core-collapse Supernovae in a Decade of Data Taken with the IceCube Neutrino Observatory;The Astrophysical Journal;2024-01-01

2. Using Parallel Computing to Optimize Optical Anisotropy Detection Methods Using OpenCL Technology;2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON);2022-11-11

3. Advances in Computing in High Energy and Nuclear Physics—Invited Papers from vCHEP 2021;Computing and Software for Big Science;2022-05-10

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