High performance w-stacking for imaging radio astronomy data: a parallel and accelerated solution

Abstract

Current and upcoming radio-interferometers are expected to produce volumes of data of increasing size that need to be processed in order to generate the corresponding sky brightness distributions through imaging. This represents an outstanding computational challenge, especially when large fields of view and/or high-resolution observations are processed. We have investigated the adoption of modern high performance computing systems specifically addressing the gridding, fast Fourier transform, and w-correction of imaging, combining parallel and accelerated solutions. We have demonstrated that the code we have developed can support data set and images of any size compatible with the available hardware, efficiently scaling up to thousands of cores or hundreds of graphic processing units, keeping the time to solution <1 h even when images of the size of the order of billions or tens of billions of pixels are generated. In addition, portability has been targeted as a primary objective, both in terms of usability on different computing platforms and in terms of performance. The presented results have been obtained on two different state-of-the-art high performance computing architectures.