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}

}

Download Download (PDF)   View View   Source Source   

348

views

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.
VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: