{"id":51417,"date":"2024-10-08T18:26:18","date_gmt":"2024-10-08T10:26:18","guid":{"rendered":"https:\/\/server.hk\/cnblog\/51417\/"},"modified":"2024-11-14T10:43:20","modified_gmt":"2024-11-14T02:43:20","slug":"ubuntu-16-04-%e5%ae%89%e8%a3%9d-cuda-8-0-cudnn-8-0-opencv-3-1-0-python-2-7-matlab-2014b-blas-mkl","status":"publish","type":"post","link":"https:\/\/server.hk\/cnblog\/51417\/","title":{"rendered":"Ubuntu 16.04 \u5b89\u88dd CUDA 8.0 + cuDNN 8.0 + OpenCV 3.1.0 + Python 2.7 + Matlab 2014b + blas (mkl)"},"content":{"rendered":"

\u5728 Ubuntu 16.04 \u4e0a\u5b89\u88dd CUDA 8.0\u3001cuDNN 8.0\u3001OpenCV 3.1.0\u3001Python 2.7\u3001Matlab 2014b \u53ca BLAS (MKL)<\/h1>\n

\u96a8\u8457\u6df1\u5ea6\u5b78\u7fd2\u548c\u8a08\u7b97\u6a5f\u8996\u89ba\u7684\u5feb\u901f\u767c\u5c55\uff0c\u8a31\u591a\u958b\u767c\u8005\u548c\u7814\u7a76\u4eba\u54e1\u9700\u8981\u5728\u5176\u7cfb\u7d71\u4e0a\u5b89\u88dd\u4e00\u7cfb\u5217\u5de5\u5177\u548c\u5eab\uff0c\u4ee5\u4fbf\u9032\u884c\u9ad8\u6548\u7684\u8a08\u7b97\u548c\u6578\u64da\u8655\u7406\u3002\u672c\u6587\u5c07\u6307\u5c0e\u60a8\u5982\u4f55\u5728 Ubuntu 16.04 \u4e0a\u5b89\u88dd CUDA 8.0\u3001cuDNN 8.0\u3001OpenCV 3.1.0\u3001Python 2.7\u3001Matlab 2014b \u53ca BLAS (MKL)\u3002<\/p>\n

\u5b89\u88dd CUDA 8.0<\/h2>\n

CUDA\uff08Compute Unified Device Architecture\uff09\u662f NVIDIA \u63d0\u4f9b\u7684\u4e00\u500b\u5e73\u884c\u8a08\u7b97\u5e73\u53f0\u548c\u7de8\u7a0b\u6a21\u578b\u3002\u8981\u5b89\u88dd CUDA 8.0\uff0c\u8acb\u6309\u7167\u4ee5\u4e0b\u6b65\u9a5f\u64cd\u4f5c\uff1a<\/p>\n

    \n
  1. \u9996\u5148\uff0c\u66f4\u65b0\u60a8\u7684\u7cfb\u7d71\uff1a<\/li>\n
    sudo apt-get update\nsudo apt-get upgrade<\/code><\/pre>\n
  2. \u4e0b\u8f09 CUDA 8.0 \u5b89\u88dd\u5305\uff1a<\/li>\n
    \u8a2a\u554f NVIDIA CUDA Downloads<\/a>\uff0c\u9078\u64c7\u60a8\u7684\u64cd\u4f5c\u7cfb\u7d71\u548c\u7248\u672c\uff0c\u7136\u5f8c\u4e0b\u8f09\u76f8\u61c9\u7684\u5b89\u88dd\u5305\u3002<\/p>\n
  3. \u5b89\u88dd CUDA\uff1a<\/li>\n
    sudo sh cuda_8.0.XX_linux.run<\/code><\/pre>\n
    \u5728\u5b89\u88dd\u904e\u7a0b\u4e2d\uff0c\u8acb\u9078\u64c7\u4e0d\u5b89\u88dd\u9a45\u52d5\u7a0b\u5e8f\uff08\u5982\u679c\u60a8\u5df2\u7d93\u5b89\u88dd\u4e86\u6700\u65b0\u7684 NVIDIA \u9a45\u52d5\u7a0b\u5e8f\uff09\u3002<\/p>\n
  4. \u8a2d\u7f6e\u74b0\u5883\u8b8a\u91cf\uff1a<\/li>\n
    echo 'export PATH=\/usr\/local\/cuda-8.0\/bin:$PATH' >> ~\/.bashrc\necho 'export LD_LIBRARY_PATH=\/usr\/local\/cuda-8.0\/lib64:$LD_LIBRARY_PATH' >> ~\/.bashrc\nsource ~\/.bashrc<\/code><\/pre>\n<\/ol>\n
    \u5b89\u88dd cuDNN 8.0<\/h2>\n
    cuDNN \u662f NVIDIA \u63d0\u4f9b\u7684\u6df1\u5ea6\u5b78\u7fd2\u52a0\u901f\u5eab\u3002\u8981\u5b89\u88dd cuDNN 8.0\uff0c\u8acb\u9075\u5faa\u4ee5\u4e0b\u6b65\u9a5f\uff1a<\/p>\n
      \n
    1. \u8a2a\u554f NVIDIA cuDNN<\/a>\uff0c\u8a3b\u518a\u4e26\u4e0b\u8f09 cuDNN 8.0 \u7684 tar \u6587\u4ef6\u3002<\/li>\n
    2. \u89e3\u58d3\u4e26\u5b89\u88dd cuDNN\uff1a<\/li>\n
      tar -xzvf cudnn-8.0-linux-x64-v5.1.tgz\nsudo cp cuda\/include\/cudnn.h \/usr\/local\/cuda\/include\nsudo cp cuda\/lib64\/libcudnn* \/usr\/local\/cuda\/lib64\nsudo chmod a+r \/usr\/local\/cuda\/include\/cudnn.h \/usr\/local\/cuda\/lib64\/libcudnn*<\/code><\/pre>\n<\/ol>\n
      \u5b89\u88dd OpenCV 3.1.0<\/h2>\n
      OpenCV \u662f\u4e00\u500b\u958b\u6e90\u7684\u8a08\u7b97\u6a5f\u8996\u89ba\u5eab\u3002\u5b89\u88dd OpenCV 3.1.0 \u7684\u6b65\u9a5f\u5982\u4e0b\uff1a<\/p>\n
        \n
      1. \u5b89\u88dd\u5fc5\u8981\u7684\u4f9d\u8cf4\u9805\uff1a<\/li>\n
        sudo apt-get install build-essential cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev\nsudo apt-get install libjpeg-dev libpng-dev libtiff-dev libatlas-base-dev gfortran<\/code><\/pre>\n
      2. \u4e0b\u8f09 OpenCV 3.1.0 \u6e90\u78bc\uff1a<\/li>\n
        git clone https:\/\/github.com\/opencv\/opencv.git\ncd opencv\ngit checkout 3.1.0<\/code><\/pre>\n
      3. \u7de8\u8b6f\u548c\u5b89\u88dd OpenCV\uff1a<\/li>\n
        mkdir build\ncd build\ncmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=\/usr\/local ..\nmake -j4\nsudo make install<\/code><\/pre>\n<\/ol>\n
        \u5b89\u88dd Python 2.7<\/h2>\n
        Python 2.7 \u662f\u4e00\u500b\u5ee3\u6cdb\u4f7f\u7528\u7684\u7de8\u7a0b\u8a9e\u8a00\u3002\u8981\u5b89\u88dd Python 2.7\uff0c\u8acb\u57f7\u884c\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n
        sudo apt-get install python2.7 python-pip<\/code><\/pre>\n
        \u5b89\u88dd Matlab 2014b<\/h2>\n
        Matlab \u662f\u4e00\u500b\u5f37\u5927\u7684\u6578\u64da\u5206\u6790\u548c\u8a08\u7b97\u5de5\u5177\u3002\u8981\u5b89\u88dd Matlab 2014b\uff0c\u60a8\u9700\u8981\u64c1\u6709\u5408\u6cd5\u7684\u5b89\u88dd\u5305\u3002\u8acb\u6309\u7167\u4ee5\u4e0b\u6b65\u9a5f\u9032\u884c\u5b89\u88dd\uff1a<\/p>\n
          \n
        1. \u5c07 Matlab \u5b89\u88dd\u5305\u4e0a\u50b3\u5230\u60a8\u7684\u4f3a\u670d\u5668\u3002<\/li>\n
        2. \u89e3\u58d3\u4e26\u904b\u884c\u5b89\u88dd\u7a0b\u5e8f\uff1a<\/li>\n
          tar -xvf matlab_R2014b_glnxa64.tar.gz\ncd matlab_R2014b_glnxa64\nsudo .\/install<\/code><\/pre>\n<\/ol>\n
          \u5b89\u88dd BLAS (MKL)<\/h2>\n
          BLAS\uff08Basic Linear Algebra Subprograms\uff09\u662f\u7dda\u6027\u4ee3\u6578\u7684\u57fa\u672c\u5b50\u7a0b\u5e8f\u3002\u8981\u5b89\u88dd MKL\uff0c\u8acb\u57f7\u884c\u4ee5\u4e0b\u547d\u4ee4\uff1a<\/p>\n
          sudo apt-get install intel-mkl<\/code><\/pre>\n
          \u7e3d\u7d50<\/h2>\n
          \u901a\u904e\u4ee5\u4e0a\u6b65\u9a5f\uff0c\u60a8\u61c9\u8a72\u80fd\u5920\u5728 Ubuntu 16.04 \u4e0a\u6210\u529f\u5b89\u88dd CUDA 8.0\u3001cuDNN 8.0\u3001OpenCV 3.1.0\u3001Python 2.7\u3001Matlab 2014b \u53ca BLAS (MKL)\u3002\u9019\u4e9b\u5de5\u5177\u548c\u5eab\u5c07\u5e6b\u52a9\u60a8\u5728\u6df1\u5ea6\u5b78\u7fd2\u548c\u8a08\u7b97\u6a5f\u8996\u89ba\u9818\u57df\u4e2d\u9032\u884c\u9ad8\u6548\u7684\u958b\u767c\u548c\u7814\u7a76\u3002\u5982\u679c\u60a8\u9700\u8981\u7a69\u5b9a\u7684\u4f3a\u670d\u5668\u74b0\u5883\u4f86\u904b\u884c\u9019\u4e9b\u61c9\u7528\uff0c\u8003\u616e\u4f7f\u7528\u6211\u5011\u7684 \u9999\u6e2fVPS<\/a> \u89e3\u6c7a\u65b9\u6848\uff0c\u4ee5\u7372\u5f97\u6700\u4f73\u6027\u80fd\u548c\u652f\u6301\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
          Learn how to install CUDA 8.0, cuDNN 8.0, OpenCV 3.1.0, Python 2.7, Matlab 2014b, and MKL on Ubuntu 16.04 for optimized performance.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4924],"tags":[],"class_list":["post-51417","post","type-post","status-publish","format-standard","hentry","category-setup-tutorials"],"_links":{"self":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/51417","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/comments?post=51417"}],"version-history":[{"count":1,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/51417\/revisions"}],"predecessor-version":[{"id":51418,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/posts\/51417\/revisions\/51418"}],"wp:attachment":[{"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/media?parent=51417"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/categories?post=51417"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/server.hk\/cnblog\/wp-json\/wp\/v2\/tags?post=51417"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}