Imaging swiFTly: streaming widefield Fourier Transformations for large-scale interferometry

We present a scalable distributed imaging framework for next-generation radio telescopes, managing the Fourier transformation from apertures to sky (or vice-versa) with a focus on minimising memory load, data transfers and compute work. We use smooth window functions to isolate the influence between specific regions of spatial-frequency and image space. This allows distribution of image data between nodes and constructing segments of frequency space exactly when and where needed. The developed prototype distributes terabytes of image data across many nodes, while generating visibilities at throughput and accuracy competitive with existing software. Scaling is demonstrated to be better than cubic in problem complexity (baseline length / field of view), reducing the risk involved in growing radio astronomy processing to large telescopes like the Square Kilometre Array.Comment: Second revisio