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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 52, Iss. 26 — Sep. 10, 2013
  • pp: 6562–6571

Fast distributed large-pixel-count hologram computation using a GPU cluster

Yuechao Pan, Xuewu Xu, and Xinan Liang  »View Author Affiliations

Applied Optics, Vol. 52, Issue 26, pp. 6562-6571 (2013)

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Large-pixel-count holograms are one essential part for big size holographic three-dimensional (3D) display, but the generation of such holograms is computationally demanding. In order to address this issue, we have built a graphics processing unit (GPU) cluster with 32.5Tflop/s computing power and implemented distributed hologram computation on it with speed improvement techniques, such as shared memory on GPU, GPU level adaptive load balancing, and node level load distribution. Using these speed improvement techniques on the GPU cluster, we have achieved 71.4 times computation speed increase for 186M-pixel holograms. Furthermore, we have used the approaches of diffraction limits and subdivision of holograms to overcome the GPU memory limit in computing large-pixel-count holograms. 745M-pixel and 1.80G-pixel holograms were computed in 343 and 3326 s, respectively, for more than 2 million object points with RGB colors. Color 3D objects with 1.02M points were successfully reconstructed from 186M-pixel hologram computed in 8.82 s with all the above three speed improvement techniques. It is shown that distributed hologram computation using a GPU cluster is a promising approach to increase the computation speed of large-pixel-count holograms for large size holographic display.

© 2013 Optical Society of America

OCIS Codes
(090.0090) Holography : Holography
(090.1760) Holography : Computer holography
(090.2870) Holography : Holographic display

ToC Category:

Original Manuscript: May 22, 2013
Manuscript Accepted: July 8, 2013
Published: September 9, 2013

Yuechao Pan, Xuewu Xu, and Xinan Liang, "Fast distributed large-pixel-count hologram computation using a GPU cluster," Appl. Opt. 52, 6562-6571 (2013)

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