一 安装ubuntu14.04
1 下载14.04.2的iso文件,双击打开文件,将wubi.exe拷贝到外面(我的是拷到和iso文件同一个目录下),双击拷出来的wubi.exe文件,运行即可(如果是先前卸载了,重新安装的,可能会提示错误,解决方法:在windows目录下,将C盘下的ubuntu目录删除即可)
2 由于ubuntu14.04有bug,不能直接登陆,所以要按照一下方法处理:(网址:http://jingyan.baidu.com/article/0aa22375bbffbe88cc0d6419.html)
(1)进入Ubuntu启动菜单时,光标选中 *Ubuntu 后,按键盘上的e键,即可进入启动项编辑模式
(2)在界面上,将 ro 改成 rw 后,按 F10 键,即可按照修改后的参数引导进入系统
(3)在终端中输入以下命令:
sudo gedit /etc/grub.d/10_lupin(4)在打开的文档中查找 ro ${args} ,找到后,将ro改成rw,然后保存并退出
(5)再在终端中输入以下命令:
sudo update-grub耐心等待系统更新启动项完成。等到提示 done 时,表示更新结束,重新回到命令符状态。关闭终端程序。
(6)重启电脑即可成功登陆(命令后重启电脑命令:reboot或shutdown -r now)
二 更新软件源
1 备份原有的软件源
sudo cp /etc/apt/sources.list /etc/apt/sources.list.bak
sudo gedit /etc/apt/sources.list删除该文件中原有的内容,将新的源粘贴进去(即将下面的内容全部粘贴进去)
deb http://mirror.bit.edu.cn/ubuntu/ trusty main restricted universe multiverse deb http://mirror.bit.edu.cn/ubuntu/ trusty-security main restricted universe multiverse deb http://mirror.bit.edu.cn/ubuntu/ trusty-updates main restricted universe multiverse deb http://mirror.bit.edu.cn/ubuntu/ trusty-backports main restricted universe multiverse deb http://mirror.bit.edu.cn/ubuntu/ trusty-proposed main restricted universe multiverse deb-src http://mirror.bit.edu.cn/ubuntu/ trusty main restricted universe multiverse deb-src http://mirror.bit.edu.cn/ubuntu/ trusty-security main restricted universe multiverse deb-src http://mirror.bit.edu.cn/ubuntu/ trusty-updates main restricted universe multiverse deb-src http://mirror.bit.edu.cn/ubuntu/ trusty-backports main restricted universe multiverse deb-src http://mirror.bit.edu.cn/ubuntu/ trusty-proposed main restricted universe multiverse
apt-get update
注:不需要先下载一个nvidia驱动安装,再安装cuda6.5(但不安装cuda中自带的驱动)
正确做法:只需要直接安装cuda6.5即可,其中需要安装三个东西cuda6.5驱动(driver),tookit,samples
1 执行下面的操作,然后验证硬件支持GPU CUDA,只要型号存在于https://developer.nvidia.com/cuda-gpus,就没问题了
lspci | grep -i nvidia2 执行下面命令,验证linux版本是否支持caffe(重点是“x86_64”这一项,保证是x86架构,64bit系统)
uname -m && cat /etc/*release3 执行下面命令,验证系统是否具有gcc,ubuntu14.04默认安装有gcc
gcc --version4 下载cuda6.5
下载地址:developer.download.nvidia.com/compute/cuda/6_5/rel/installers/cuda_6.5.14_linux_64.run
5 安装cuda(可参考官网教程:http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/index.html#runfile-nouveau)
(1)依次执行下列命令,将已有的驱动nouveau禁用:
cd /etc/modprobe.d
sudo vi blacklist-nouveau.conf也可以用下面的命令替代上面两条命令
sudo apt-get install vim sudo vim /etc/modprobe.d/blacklist-nouveau.conf在打开的文件中写入下列内容:
blacklist nouveau options nouveau modeset=0执行下列命令,重新生成initrd文件:
sudo update-initramfs -u之后执行下列命令重启电脑:
sudo reboot(2)重启并登陆后,按ctrl+alt+F1进入tty1(F1-F6对应于tty1-tty6),输入用户名和密码,登陆进去后,执行下列命令,将lightdm禁用:
sudo stop lightdm切换到已经下载好的cuda6.5的存放地址:
cd /home/liuxiabing/给cuda6.5可执行权限:
chmod +x *.run
sudo sh ./cuda_6.5.14_linux_64.run
安装成功后,执行下列命令,打开lightdm:
sudo start lightdm
输入下列命令,查找路径:
cd /usr/local/cuda-6.5/bin/ pwd由pwd命令获得当前路径,然后运行下列命令:
sudo vim /etc/profile在打开的文件中将下面的内容写到该文件的最后面:
export PATH=$PATH:/usr/local/cuda-6.5/bin写完之后保存推出,然后执行下列命令:
cd ../lib64/ pwd
获得当前路径后,运行下列命令:
sudo vim /etc/ld.so.conf在打开的文件中将下面的内容写到该文件的最后面(有点儿记不清了,反正这个文件里只有下面这两句话,少哪句话就把哪句话写进去):
include /etc/ld.so.conf.d/*.conf /usr/local/cuda-6.5/lib64然后执行下列命令,使更改立即生效:
sudo ldconfig source /etc/profile执行下列命令可以查看nvidia信息:
nvidia-smi然后执行下列命令安装必要的包:
sudo apt-get install build-essential
然后转到下面这个目录下:
cd /home/liuxiabing/NVIDIA_CUDA-6.5_Samples/执行下列命令进行编译:
make -j16注:如果报错,可能是没有安装编译器g++,执行下列命令安装,安装完重新编译即可:
sudo apt-get install build-essential编译完,执行下列命令判断是否安装成功:
cd /home/liuxiabing/NVIDIA_CUDA-6.5_Samples/bin/x86_64/linux/release ./deviceQuery如果出现下列的显卡信息,则说明安装成功:
./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "GeForce GTX 670" CUDA Driver Version / Runtime Version 6.5 / 6.5 CUDA Capability Major/Minor version number: 3.0 Total amount of global memory: 4095 MBytes (4294246400 bytes) ( 7) Multiprocessors, (192) CUDA Cores/MP: 1344 CUDA Cores GPU Clock rate: 1098 MHz (1.10 GHz) Memory Clock rate: 3105 Mhz Memory Bus Width: 256-bit L2 Cache Size: 524288 bytes Maximum Texture Dimension Size (x,y,z) 1D=(65536), 2D=(65536, 65536), 3D=(4096, 4096, 4096) Maximum Layered 1D Texture Size, (num) layers 1D=(16384), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 2048 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 1 copy engine(s) Run time limit on kernels: Yes Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device PCI Bus ID / PCI location ID: 1 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 6.5, CUDA Runtime Version = 6.5, NumDevs = 1, Device0 = GeForce GTX 670 Result = PASS四 caffe的安装过程,可以参考这篇博客:caffe+Ubuntu14.0.4 64bit 环境配置说明(无CUDA,caffe在CPU下运行)
1 安装OpenCV时,会出现这样的错误:
opencv-2.4.9/modules/gpu/src/nvidia/core/NCVPixelOperations.hpp(51): error: a storage class is not allowed in an explicit specialization解决方法:
(1)在下列网址下载NCVPixelOperations.hpp文件:
http://code.opencv.org/projects/opencv/repository/revisions/feb74b125d7923c0bc11054b66863e1e9f753141
(2)用该文件替换解压后的Install-OpenCV-master文件夹下的NCVPixelOperations.hpp文件(可以用查找的方法找到这个文件,然后用mv命令先删除,再用cp命令将下载下来的文件拷贝过去)。
cd /home/liuxiabing/Install-OpenCV-master/Ubuntu/2.4/OpenCV/opencv-2.4.9/modules/gpu/src/nvidia/core sudo rm NCVPixelOperations.hpp sudo cp /home/liuxiabing/下载/NCVPixelOperations.hpp /home/liuxiabing/Install-OpenCV-master/Ubuntu/2.4/OpenCV/opencv-2.4.9/modules/gpu/src/nvidia/core
(3)修改/home/liuxiabing/Install-OpenCV-master/Ubuntu/2.4目录下的opencv2_4_9.sh文件,将下载和解压的代码删除,修改后的文件如下所示:
arch=$(uname -m) if [ "$arch" == "i686" -o "$arch" == "i386" -o "$arch" == "i486" -o "$arch" == "i586" ]; then flag=1 else flag=0 fi echo "Installing OpenCV 2.4.9" mkdir OpenCV cd OpenCV echo "Removing any pre-installed ffmpeg and x264" sudo apt-get -y remove ffmpeg x264 libx264-dev echo "Installing Dependenices" sudo apt-get -y install libopencv-dev sudo apt-get -y install build-essential checkinstall cmake pkg-config yasm sudo apt-get -y install libtiff4-dev libjpeg-dev libjasper-dev sudo apt-get -y install libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev sudo apt-get -y install python-dev python-numpy sudo apt-get -y install libtbb-dev sudo apt-get -y install libqt4-dev libgtk2.0-dev sudo apt-get -y install libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev sudo apt-get -y install x264 v4l-utils ffmpeg sudo apt-get -y install libgtk2.0-dev echo "Installing OpenCV 2.4.9" cd opencv-2.4.9 mkdir build cd build cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON .. make -j4 sudo make install sudo sh -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf' sudo ldconfig echo "OpenCV 2.4.9 ready to be used"修改完保存退出,然后按照之前的方法安装OpenCV即可:
sudo ./opencv2_4_9.sh2 python的安装过程中,安装scipy包时,会报错:
building 'dfftpack' library error: library dfftpack has Fortran sources but no Fortran compiler found
解决方法:执行下列命令:
sudo apt-get install gfortran然后再重新安装即可:
sudo pip install scipy五 按照我的那篇博客全部安装后,编译caffe,并测试,成功啦!
注:编译caffe时,复制一份Makefile.config,什么都不需要修改,直接编译即可
附:参考资料
Caffe + Ubuntu 14.04 64bit + CUDA 6.5 配置说明
http://www.cnblogs.com/platero/p/3993877.html
Caffe+Ubuntu14.04+CUDA6.5新手安装配置指南
http://www.haodaima.net/art/2823705
cuda官网文档说明
http://docs.nvidia.com/cuda/cuda-getting-started-guide-for-linux/index.html#runfile-nouveau
安装Caffe的Python wrapper时出现问题的解决方法
http://blog.csdn.net/u011333059/article/details/38078617