Paper Abstract and Keywords |
Presentation |
2014-07-29 15:40
Consideration of 2D-FFT by Decomposition of Large Scale Data on Multi-GPU Hiroaki Miyata, BoazJessie Jackin, Takeshi Ohkawa, Kanemitsu Ootsu, Takashi Yokota, Yoshio Hayasaki, Toyohiko Yatagai, Takanobu Baba (Utsunomiya Univ.) CPSY2014-27 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Acceleration for Fast Fourier Transform (FFT) of large computation is an important issue.
Until today, acceleration for FFT has been studied by various ways.
There is a parallel processing using a GPU as one of the way to accelerate of FFT.
Acceleration for FFT is an important issue for calculation to generate the CGH in background of the present study.
CGH need high clarity to get enough view angle, but the scale of data become very large.
As the data become large, since the data is not completery place on a GPU, we do the processing by distribute the data to Multi-GPU in this study.
In this paper, we consider 2D-FFT by data decomposition as effective FFT processing method of large scale data in Multi-GPU.
Result of the initial evaluation by simulation assumed Multi-GPU, we confirmed speed improvement up to 1.3 times compared to the conventional method using FFTW library. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Multi-GPU / large scale data / 2D-FFT / internode communication / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 114, no. 155, CPSY2014-27, pp. 103-108, July 2014. |
Paper # |
CPSY2014-27 |
Date of Issue |
2014-07-21 (CPSY) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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CPSY2014-27 |
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