Streaming distributed Fourier transform for large-scale interferometry imaging

Imaging data from upcoming radio telescopes requires distributing processing at large scales. This paper presents a distributed Fourier transform algorithm for radio interferometry processing. It generates arbitrary grid chunks with full non-coplanarity corrections while minimising memory residency, data transfer and compute work. We utilise window functions to isolate the influence between regions of grid and image space. This allows us to distribute image data between nodes and construct parts of grid space exactly when and where needed. The developed prototype easily handles image data terabytes in size, while generating visibilities at great throughput and accuracy. Scaling is demonstrated to be better than cubic in baseline length, reducing the risk involved in growing radio astronomy processing to the Square Kilometre Array and similar telescopes.