English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 55184/89457 (62%)
造訪人次 : 10667494      線上人數 : 23
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/96254

    題名: Acceleration of vertex component analysis for spectral unmixing with CUDA
    作者: Wei, Shih-Chieh;Huang, Bormin;Antonio Plaza
    貢獻者: 淡江大學資訊管理學系
    關鍵詞: Computer programming;Graphics processing units;Matrices;Parallel computing
    日期: 2013-10
    上傳時間: 2014-03-06 17:08:40 (UTC+8)
    摘要: Hyperspectral images can be used to identify the unique materials present in an area.Due to the limited spatial resolution, each pixel of the image is considered as a mixture of several different pure substances or endmembers. Several spectral unmixing methods have been developed for endmember extraction in an image. Among them, the vertex component analysis (VCA) algorithm is a popular one for its superior performance. As there are a lot of matrix/vector operations involved in the VCA algorithm, this work aims to apply the highly parallel computing power of recent GPUs which are reported to have good success in acceleration of many compute intensive applications. In the experiment, the compute unified device architecture (CUDA) which provide more convenient programming model is used. The speedup is measured with respect to standard C code on a single core CPU for evaluation.Our experiments are performed on a typical case where the number of extracted endmembers is 30 from the 188-band Cuprite hyperspectral dataset.The results show that a speedup of 42x can be achieved on a pure GPU implementation using CULA and CUBLAS libraries. As VCA involves Singular Value Decomposition (SVD) operation and SVD is faster on CPU than GPU for small data sizes as is our case, a speedup of 58x can be achieved on a hybrid implementation when SVD is carried out on CPU.
    關聯: Proc. SPIE 8895, High-Performance Computing in Remote Sensing III, 889509
    DOI: 10.1117/12.2031527
    顯示於類別:[資訊管理學系暨研究所] 會議論文





    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋