doi: 10.17706/ijapm.2023.13.1.1-9
A Cloud Demonstrator for Belle II, T2K and Hyper-K
- 1 Istituto Nazionale di Fisica Nucleare (INFN) Sezione di Napoli, Napoli, Italy
- 2 King’s College London (KCL), London, UK
- 3 Laboratoire de Physique NucléAire et des Hautes éNergies (LPNHE), Sorbonne Université, Université Paris Cité, CNRS/IN2P3, Paris, France
- 4 Institut Jožef Stefan, Ljubljana, Slovenia.
Abstract
The international physics community has spent large efforts in the last decade to utilize different types of resources in their computing model, in order to increase the available computing power and involve more people and institutions in the activities. In this paper we present the work done to define and implement a set of common tools for integrating cloud computing resources into the computing framework of the Belle II, T2K and Hyper-Kamiokande (Hyper-K) experiments to produce Monte Carlo simulations and run user analyses. Starting with the virtual machine lifecycle tool VCYCLE, we create a custom setup able to support and manage the environment of the three experiments, then integrate the machinery into the DIRAC infrastructure of Belle II and in the GridPP DIRAC service used by T2K and Hyper-K. In order to expand the number of usable cloud infrastructures, we extended the software capability by integrating token based authentication in the Openstack module of VCYCLE. With this modification we are able to run Monte Carlo production jobs on the European Grid Infrastructure (EGI) Federated Infrastructure demonstrating the flexibility of implemented the solution.
Keywords
- Cloud
- high energy physics
- Monte Carlo simulations
How to Cite
Silvio Pardi, Sophie King, Mathieu Guigue, Aurélien Bailly-Reyre, and Marko Bracko, "A Cloud Demonstrator for Belle II, T2K and Hyper-K," International Journal of Applied Physics and Mathematics, vol. 13, no. 1, pp. 1-9, 2023. https://doi.org/ 10.17706/ijapm.2023.13.1.1-9
Copyright & License
Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).