Poster Abstract

P.55 Thomas Vuillaume (LAPP, CNRS)

hipeCTA: a high performance library for the Cherenkov Telescope Array data analysis

The Cherenkov Telescope Array (CTA) is the next-generation observatory for ground-based gamma-ray astronomy. CTA's baseline layout comprises two arrays of gamma-ray telescopes
in both hemispheres, with 19 telescopes on the island of La Palma (Spain) and 99 telescopes in Paranal (Chile). Due to its large number of telescopes, CTA will record a tremendous amount of data (more than 3PB/year) that represents a computing challenge requiring a performant reconstruction software. We have developed a high-performance algorithm able to tackle these challenges and to perform the reconstruction of CTA raw data maximizing the usage of computing resources and thus minimizing their cost.
As Python is becoming the standard language in gamma-ray astronomy for data processing, we developed a Python library, hipeCTA, using wrapped optimized C++ code, thus ensuring efficiency, ease of use and integrability with other common libraries, especially ctapipe, the prototype library for CTA low-level data processing.
Here we present hipeCTA and show that the obtained physics and computing performances could allow a real-time analysis consistent with CTA requirements with reasonable computing resources.