Decomposition method for fast computation of giga-pixel sized Fresnel holograms on a GPU-cluster

Published on 2018-04-13T21:35:23Z (GMT) by
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; Yatagai, Toyohiko; Baba, Takanobu (2018): Decomposition method for fast computation of

giga-pixel sized Fresnel holograms on a GPU-cluster. The Optical Society. Collection.