Decomposition method for fast computation of
giga-pixel sized Fresnel holograms on a GPU-cluster
Posted on 2018-04-13 - 21:35
A parallel computation method for large-size Fresnel computer generated hologram (CGH) is reported.
The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from
2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The
scale of the computation problem is also expanded to 2-giga pixels, making is closer to real application
requirements. The significant feature of the reported method its ability to avoid communication overhead
and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of
parallelism that favors small to large scale parallel computing machines. Simulation and optical experiments
were conducted to demonstrate the working and evaluate the efficiency of the proposed technique.
A two times improvement in computation speed has been achieved compared to conventional method,
on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20 times improvement
in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel
machine with 16-nodes, where each node has 16 GPU’s.
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Jessie, Jackin Boaz; Watanabe, Shinpei; Ootsu, Kanemitsu; Ohkawa, Takeshi; Yokota, Takashi; Hayasaki, Yoshio; et al. (2018). Decomposition method for fast computation of
giga-pixel sized Fresnel holograms on a GPU-cluster. Optica Publishing Group. Collection. https://doi.org/10.6084/m9.figshare.c.3938266.v1
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AUTHORS (8)
JJ
Jackin Boaz Jessie
SW
Shinpei Watanabe
KO
Kanemitsu Ootsu
TO
Takeshi Ohkawa
TY
Takashi Yokota
YH
Yoshio Hayasaki
TY
Toyohiko Yatagai
TB
Takanobu Baba