Non-equispaced FFT computation with CUDA and GPU

Xiangwen Lyu, Jian Min Zuo, Haiyong Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Non-equispaced fast Fourier transform (NFFT) has attracted significant interest for its applications in tomography and remote sensing where visualization and image reconstruction require non-equispaced data. Here we present an efficient implementation of high accuracy NFFT on an NVIDIA GPU (Graphic Processing Unit). We focused on the convolution step in the computation of NFFT, since it is the most time consuming portion of the algorithm. In order to achieve high efficiency in on-chip memory usage, we used pre-computed compressed datasets to avoid the write-conflict. The performance was measured by comparing with the available GPU version called CUNFFT1. We demonstrate an improved performance ratio of 4X (random dataset) and 2X (radial dataset) in single precision. When compared to the CPU version, we measured 78X in the peak performance. Furthermore, to illustrate the potential of NFFT in tomography visualization applications, we evaluated the forward NFFT performance for a three dimensional (3D) object constructed of atoms in a nanoparticle.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 International Conference on Virtual Reality and Visualization, ICVRV 2016
EditorsDandan Ding, Dangxiao Wang, Jian Chen, Xun Luo
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages227-234
Number of pages8
ISBN (Electronic)9781509051885
DOIs
StatePublished - Jun 1 2017
Event6th International Conference on Virtual Reality and Visualization, ICVRV 2016 - Hangzhou, Zhejiang, China
Duration: Sep 24 2016Sep 26 2016

Publication series

NameProceedings - 2016 International Conference on Virtual Reality and Visualization, ICVRV 2016

Other

Other6th International Conference on Virtual Reality and Visualization, ICVRV 2016
CountryChina
CityHangzhou, Zhejiang
Period9/24/169/26/16

Keywords

  • CUDA
  • FFT
  • GPU
  • Non-equispaced
  • Tomography

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Modeling and Simulation
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction

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