Poster Abstract

P9.12 Cees Carels (University of Oxford)

Theme: Evolution of software development and management

Development of production-ready GPU data processing pipeline software for AstroAccelerate

Upcoming large scale telescope projects such as the Square Kilometre Array (SKA) will see high data rates and large data volumes; requiring tools that can analyse telescope event data quickly and accurately. In modern radio telescopes, analysis software forms a core part of the data read out, and long-term software stability and maintainability are essential.

AstroAccelerate is a many core accelerated software package that uses NVIDIA GPUs to perform real-time analysis of radio telescope data and it has been shown to be substantially faster than real-time at processing simulated SKA-like data. AstroAccelerate contains optimised GPU implementations of signal processing tools used in radio astronomy, such as de-dispersion, Fourier domain acceleration search, single pulse detection, and others.

This poster describes the transformation of AstroAccelerate from a C-like prototype to a production-ready C++ API and a Python interface; while preserving compatibility with legacy software that is implemented in C. The design of the software library interfaces, refactoring aspects, and coding techniques will be discussed.