15920

Faster GPU-based convolutional gridding via thread coarsening

Bruce Merry
SKA South Africa, 3rd Floor, The Park, Park Road, 7405 South Africa
arXiv:1605.07023 [astro-ph.IM], (23 May 2016)
@article{merry2016faster,

   title={Faster GPU-based convolutional gridding via thread coarsening},

   author={Merry, Bruce},

   year={2016},

   month={may},

   archivePrefix={"arXiv"},

   primaryClass={astro-ph.IM}

}

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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 3.2x for single-polarization gridding and 1.9x for quad-polarization gridding on a GeForce GTX 980, and smaller but still significant gains on a Radeon R9 290X.
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