EPJ Web Conf.
Volume 214, 201923rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|Number of page(s)||9|
|Section||T5 - Software development|
|Published online||17 September 2019|
Performance optimization of the air shower simulation program for the Cherenkov Telescope Array
Laboratoire Univers et Particules, Université de Montpellier Place Eugène Bataillon - CC 72,
2 Max-Planck-Institut für Kernphysik, P.O.Box 103980, D-69029 Heidelberg, Germany
3 Deutsches Elektronen-Synchrotron, Platanenallee 6, 15738 Zeuthen, Germany
4 Université de Perpignan Via Domitia, Digits, Architectures et Logiciels Informatiques, F-66860, Perpignan, Université de Montpellier, Laboratoire d’Informatique Robotique, CNRS, , France
* e-mail: firstname.lastname@example.org
Published online: 17 September 2019
The Cherenkov Telescope Array (CTA), currently under construction, is the next-generation instrument in the field of very high energy gamma-ray astronomy. The first data are expected by the end of 2018, while the scientific operations will start in 2022 for a duration of about 30 years. In order to characterize the instrument response to the Cherenkov light emitted when cosmic ray showers develop in the atmosphere, detailed Monte Carlo simulations will be regularly performed in parallel to CTA operation. The estimated CPU time associated to these simulations is very high, of the order of 200 millions HS06 hours per year. Reducing the CPU time devoted to simulations would allow either to reduce infrastructure cost or to better cover the large phase space. In this paper, we focus on the main computing step (70% of the whole CPU time) implemented in the CORSIKA program, and specifically on the mod-ule responsible for the propagation of Cherenkov photons in the atmosphere. We present our preliminary studies about different options of code optimization, with a particular focus on vectorization facilities (SIMD instructions). Our proposals take care, as automatically as possible, of the hardware portability constraints introduced by the grid computing environment that hosts these simulations. Performance evaluation in terms of running-time and accuracy is provided.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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