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Title:
mpfft: an auto-tuning fft library for opencl gpus
Author: Li Yan ; Zhang Yun-Quan ; Liu Yi-Qun ; Long Guo-Ping ; Jia Hai-Peng
Source: Journal of Computer Science and Technology
Issued Date: 2013
Keyword: Medical imaging ; Program processors
Indexed Type: EI
ISSN: 1000-9000
Department: (1) Institute of Software Chinese Academy of Sciences Beijing 100190 China; (2) Graduate University of Chinese Academy of Sciences Beijing 100049 China; (3) School of Information Science and Engineering Ocean University of China Qingdao 266000 China
Abstract: Fourier methods have revolutionized many fields of science and engineering, such as astronomy, medical imaging, seismology and spectroscopy, and the fast Fourier transform (FFT) is a computationally efficient method of generating a Fourier transform. The emerging class of high performance computing architectures, such as GPU, seeks to achieve much higher performance and efficiency by exposing a hierarchy of distinct memories to software. However, the complexity of GPU programming poses a significant challenge to developers. In this paper, we propose an automatic performance tuning framework for FFT on various OpenCL GPUs, and implement a high performance library named MPFFT based on this framework. For power-of-two length FFTs, our library substantially outperforms the clAmdFft library on AMD GPUs and achieves comparable performance as the CUFFT library on NVIDIA GPUs. Furthermore, our library also supports non-power-of-two size. For 3D non-power-of-two FFTs, our library delivers 1.5x to 28x faster than FFTW with 4 threads and 20.01x average speedup over CUFFT 4.0 on Tesla C2050. © 2013 Springer Science+Business Media New York & Science Press, China.
English Abstract: Fourier methods have revolutionized many fields of science and engineering, such as astronomy, medical imaging, seismology and spectroscopy, and the fast Fourier transform (FFT) is a computationally efficient method of generating a Fourier transform. The emerging class of high performance computing architectures, such as GPU, seeks to achieve much higher performance and efficiency by exposing a hierarchy of distinct memories to software. However, the complexity of GPU programming poses a significant challenge to developers. In this paper, we propose an automatic performance tuning framework for FFT on various OpenCL GPUs, and implement a high performance library named MPFFT based on this framework. For power-of-two length FFTs, our library substantially outperforms the clAmdFft library on AMD GPUs and achieves comparable performance as the CUFFT library on NVIDIA GPUs. Furthermore, our library also supports non-power-of-two size. For 3D non-power-of-two FFTs, our library delivers 1.5x to 28x faster than FFTW with 4 threads and 20.01x average speedup over CUFFT 4.0 on Tesla C2050. © 2013 Springer Science+Business Media New York & Science Press, China.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15976
Appears in Collections:软件所图书馆_会议论文

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Li Yan,Zhang Yun-Quan,Liu Yi-Qun,et al. mpfft: an auto-tuning fft library for opencl gpus[C]. 见:.
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