An Attempt of CUDA Implementation of PCA-SIFT(Internationa Session 6)

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概要

• 論文の詳細を見る

• GPGPU (General-Purpose computation on GPUs) is a paradigm to use GPUs (graphics processing units) for general computation. Due to recent remarkable improvement of GPU, GPU outperforms CPU in computation ability. However, most people could not use the ability for general computation because existing programming languages require knowledge about GPU hardware architectures and computer graphics for GPGPU computing. Recently, a new GPU language CUDA (Compute Unified Device Architecture) has been released from NVIDIA. The CUDA code is C language style and has less computational restriction. Thus, usual operations of C language can run on GPU without much special knowledge. In this report, we briefly introduce CUDA language programming and report a CUDA implemented of PCA-SIFT. Compared to a CPU implementation, our CUDA implementation reduced the processing time to around 1/4. In addition, we also report an interesting phenomenon results useful for practical use of CUDA.

• 2007-10-18

著者

• Kise Koichi

  Department Of Computer Science And Intelligent Systems Osaka Prefecture University

• Kise Koichi

  Graduate School Of Engineering Osaka Prefecture University

• Iwamura Masakazu

  Graduate School Of Engineering Osaka Prefecture University

• Iwamura Masakazu

  Department Of Computer Science And Intelligent Systems Osaka Prefecture University

• Noguchi Kazuto

  Graduate School Of Engineering Osaka Prefecture University

• HONDO Takayuki

  Graduate School of Engineering, Osaka Prefecture University

• Hondo Takayuki

  Graduate School Of Engineering Osaka Prefecture University

関連論文

• An Attempt of CUDA Implementation of PCA-SIFT(Internationa Session 6)
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