GPU-accelerated compressive holography | Zendy

Yutaka Endo | Zendy; Tomoyoshi Shimobaba | Zendy; Takashi Kakue | Zendy; Tomoyoshi Ito | Zendy

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GPU-accelerated compressive holography

Author(s) -

Yutaka Endo,

Tomoyoshi Shimobaba,

Takashi Kakue,

Tomoyoshi Ito

Publication year - 2016

Publication title -

optics express

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 1.394

H-Index - 271

ISSN - 1094-4087

DOI - 10.1364/oe.24.008437

Subject(s) - graphics processing unit , computer science , holography , compressed sensing , digital holography , cuda , graphics , computational science , thresholding , parallel computing , central processing unit , matrix (chemical analysis) , general purpose computing on graphics processing units , sparse matrix , algorithm , iterative reconstruction , computer graphics (images) , optics , computer vision , image (mathematics) , computer hardware , physics , materials science , composite material , quantum mechanics , gaussian

In this paper, we show fast signal reconstruction for compressive holography using a graphics processing unit (GPU). We implemented a fast iterative shrinkage-thresholding algorithm on a GPU to solve the ℓ 1 and total variation (TV) regularized problems that are typically used in compressive holography. Since the algorithm is highly parallel, GPUs can compute it efficiently by data-parallel computing. For better performance, our implementation exploits the structure of the measurement matrix to compute the matrix multiplications. The results show that GPU-based implementation is about 20 times faster than CPU-based implementation.

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