cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs

@article{Shih2021cuFINUFFTAL,
  title={cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTs},
  author={Yu-hsuan Shih and Garrett Wright and Joakim And'en and Johannes Blaschke and Alex H. Barnett},
  journal={2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},
  year={2021},
  pages={688-697}
}
Nonuniform fast Fourier transforms dominate the computational cost in many applications including image reconstruction and signal processing. We thus present a general-purpose GPU-based CUDA library for type 1 (nonuniform to uniform) and type 2 (uniform to nonuniform) transforms in dimensions 2 and 3, in single or double precision. It achieves high performance for a given user-requested accuracy, regardless of the distribution of nonuniform points, via cache-aware point reordering, and load… 

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