Faster GPU-based convolutional gridding via thread coarsening

Convolutional gridding is a processor-intensive step in interferometric imaging. While it is possible to use graphics processing units (GPUs) to accelerate this operation, existing methods use only a fraction of the available flops. We apply thread coarsening to improve the efficiency of an existing algorithm, and observe performance gains of up to 3.2×3.2× for single-polarization gridding and 1.9×1.9× for quad-polarization gridding on a GeForce GTX 980, and smaller but still significant gains on a Radeon R9 290X.