Presentation 2009-05-15
Performance comparison of GPU and FPGA in image processing
Shuichi ASANO, Tutomu MARUYAMA,
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Abstract(in English) Many applications in image processing have high inherent parallelism. FPGAs have shown very high performance in spite of their low operational frequency by fully extracting the parallelism. In recent micro processors, it also becomes possible to utilize the parallelism using multi-cores which support improved SIMD instructions. Recent GPUs support a large number of cores, and have a potential for high performance in many applications. In this paper, we compare the performance of FPGA, GPU and CPU using three applications in image processing; two-dimensional filters, stereo-vision and k-means clustering, and make it clear which platform is faster under which conditions.
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Keyword(in English) GPU / CUDA / FPGA / two-dimensional filters / stereo-vision / k-means clustering
Paper # RECONF2009-15
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Committee RECONF
Conference Date 2009/5/7(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Performance comparison of GPU and FPGA in image processing
Sub Title (in English)
Keyword(1) GPU
Keyword(2) CUDA
Keyword(3) FPGA
Keyword(4) two-dimensional filters
Keyword(5) stereo-vision
Keyword(6) k-means clustering
1st Author's Name Shuichi ASANO
1st Author's Affiliation Systems and Information Engineering, University of Tsukuba()
2nd Author's Name Tutomu MARUYAMA
2nd Author's Affiliation Systems and Information Engineering, University of Tsukuba
Date 2009-05-15
Paper # RECONF2009-15
Volume (vol) vol.109
Number (no) 26
Page pp.pp.-
#Pages 6
Date of Issue