Accelerating radio astronomy imaging with RICK: a step towards SKA-Mid and SKA-Low

TL;DR

This paper introduces RICK 2.0, a scalable, high-performance radio astronomy imaging software leveraging distributed FFTs with HeFFTe, significantly improving efficiency and scalability for large data volumes from modern interferometers like SKA.

Contribution

The paper presents RICK 2.0, a novel, portable implementation using HeFFTe for distributed FFTs, overcoming previous scaling limitations and enhancing performance on diverse HPC architectures.

Findings

RICK 2.0 achieves substantial performance gains on GPUs.

The new architecture reduces communication overheads drastically.

Scales effectively with large pixel resolutions and many frequency planes.

Abstract

The data volumes generated by modern radio interferometers, such as the SKA precursors, present significant computational challenges for imaging pipelines. Addressing the need for high-performance, portable, and scalable software, we present RICK 2.0 (Radio Imaging Code Kernels). This work introduces a novel implementation that leverages the HeFFTe library for distributed Fast Fourier Transforms, ensuring portability across diverse HPC architectures, including multi-core CPUs and accelerators. We validate RICK's correctness and performance against real observational data from both MeerKAT and LOFAR. Our results demonstrate that the HeFFTe-based implementation offers substantial performance advantages, particularly when running on GPUs, and scales effectively with large pixel resolutions and a high number of frequency planes. This new architecture overcomes the critical scaling limitations identified in previous work (Paper II, Paper III), where communication overheads consumed up to 96% of the runtime due to the necessity of communicating the entire grid. This new RICK version drastically reduces this communication impact, representing a scalable and efficient imaging solution ready for the SKA era.