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一、安装CUDA1、查看显卡驱动是否安装好:$nvidia-settings 2、安装OpenGL:sudo apt-get install build-essential libgl1-mesa-dev sudo apt-get install freeglut3-dev sudo apt-get install libglew-dev libsdl2-dev libsdl2-image-dev libglm-devlibfreetype6-dev 3、进入下载好的.run文件目录,依次执行:sudo sh cuda_9.0.176_384.81_linux.run sudo sh cuda_9.0.176.1_linux.run sudo sh cuda_9.0.176.2_linux.run (按空格键直至协议许可部分,按提示进行安装,不用再次安装显卡驱动) 安装结束后的显示: =========== =Summary = =========== Driver: Not Selected Toolkit: Installed in /usr/local/cuda-9.0 Samples: Installed in /home/zili, but missing recommended libraries Pleasemake sure that - PATH includes /usr/local/cuda-9.0/bin - LD_LIBRARY_PATH includes /usr/local/cuda-9.0/lib64, or, add/usr/local/cuda-9.0/lib64 to /etc/ld.so.conf and run ldconfig as root Touninstall the CUDA Toolkit, run the uninstall script in/usr/local/cuda-9.0/bin Pleasesee CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-9.0/doc/pdffor detailed information on setting up CUDA. ***WARNING:Incomplete installation! This installation did not install the CUDADriver. A driver of version at least 384.00 is required for CUDA 9.0functionality to work. Toinstall the driver using this installer, run the following command,replacing <CudaInstaller> with the name of this run file: sudo<CudaInstaller>.run -silent -driver 4、将CUDA添加到Path:sudo gedit ~/.bashrc 在该文件最后加入以下两行并保存: export PATH=/usr/local/cuda-9.0/bin:$PATH export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH 使该配置生效:source ~/.bashrc 注意:安装cuda时,不要修改/etc/profile,所有的环境变量均写在~/.bashrc里,修改前者容易出现系统错误。 5、cudnn动态库更换:解压后进入include文件夹,执行: sudo cp cudnn.h /usr/local/cuda/include cd .. 再将lib64目录下的动态文件进行复制 sudo cp lib64/* /usr/local/cuda/lib64/ sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* 6、验证CUDA是否安装成功:进入Samples文件夹,执行 sudo make -j8 cd 1_Utilities/deviceQuery ./deviceQuery 出现以下输出表示安装成功: ./deviceQueryStarting... CUDADevice Query (Runtime API) version (CUDART static linking) Detected1 CUDA Capable device(s) Device0: "GeForce GTX 1080" CUDADriver Version / Runtime Version 9.0 / 9.0 CUDACapability Major/Minor version number: 6.1 Totalamount of global memory: 8114 MBytes (8508145664bytes) (20)Multiprocessors, (128) CUDA Cores/MP: 2560 CUDA Cores GPUMax Clock rate: 1771 MHz (1.77 GHz) MemoryClock rate: 5005 Mhz MemoryBus Width: 256-bit L2Cache Size: 2097152 bytes MaximumTexture Dimension Size (x,y,z) 1D=(131072), 2D=(131072,65536), 3D=(16384, 16384, 16384) MaximumLayered 1D Texture Size, (num) layers 1D=(32768), 2048 layers MaximumLayered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Totalamount of constant memory: 65536 bytes Totalamount of shared memory per block: 49152 bytes Totalnumber of registers available per block: 65536 Warpsize: 32 Maximumnumber of threads per multiprocessor: 2048 Maximumnumber of threads per block: 1024 Maxdimension size of a thread block (x,y,z): (1024, 1024, 64) Maxdimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximummemory pitch: 2147483647 bytes Texturealignment: 512 bytes Concurrentcopy and kernel execution: Yes with 2 copy engine(s) Runtime limit on kernels: Yes IntegratedGPU sharing Host Memory: No Supporthost page-locked memory mapping: Yes Alignmentrequirement for Surfaces: Yes Devicehas ECC support: Disabled Devicesupports Unified Addressing (UVA): Yes SupportsCooperative Kernel Launch: Yes SupportsMultiDevice Co-op Kernel Launch: Yes DevicePCI Domain ID / Bus ID / location ID: 0 / 1 / 0 ComputeMode: <Default (multiple host threads can use ::cudaSetDevice() with devicesimultaneously) > deviceQuery,CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version= 9.0, NumDevs = 1 Result= PASS 二、BLAS安装与配置BLAS(基础线性代数集合)是一个应用程序接口的标准。caffe官网上推荐了三种实现:ATLAS,MKL, orOpenBLAS。其中atlas可以直接通过命令行安装,在此不再介绍。我采用的是intel的mkl库,首先,通过链接https://software.intel.com/en-us/qualify-for-free-software/student在intel官网申请学生版的**ParallelStudio XE Cluster Edition **,下载完成之后cd到下载目录进行安装: $tar zxvf parallel_studio_xe_2018_update2_cluster_edition.tgz #解压下载文件 $chmod 777 parallel_studio_xe_2018_update2_cluster_edition -R #获取文件权限 $cd parallel_studio_xe_2018_update2_cluster_edition/ $sudo ./install_GUI.sh ***:ST5V-XXXXXXXX,选择自定义安装MKL。 安装完成之后,进行相关文件的链接: $sudo gedit /etc/ld.so.conf.d/intel_mkl.conf 在打开的文件中添加库文件: /opt/intel/lib/intel64 /opt/intel/mkl/lib/intel64 添加完成之后,编译链接使lib文件立即生效: $sudo ldconfig 三、安装Javahttp://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html 将下载下来的jdk-8u101-linux-x64.tar.gz文件解压。使用如下命令解压: sudo tar zxvf ./jdk-8u101-linux-x64.tar.gz 为了方便管理,可将解压后的文件移至/usr/java目录下。 设置环境变量: 编辑.bashrc文件sudo gedit ~/.bashrc 在该文件中添加如下内容: JAVA_HOME=/usr/java JRE_HOME=$JAVA_HOME/jre JAVA_BIN=$JAVA_HOME/bin CLASSPATH=.:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar:$JRE_HOME/lib PATH=$PATH:$JAVA_HOME/bin:$JRE_HOME/bin export JAVA_HOME JRE_HOME PATH CLASSPATH 为了让更改立即生效,请在终端执行如下命令: source ~/.bashrc 通过以上步骤,JDK已安装完成。输入以下命令验证java -version 四、安装MATLAB2015b注意不要安装Matlab2016b、2017b等较新的版本,否则编译出的matcaffe库无法通过makemattest。 1、挂载映像文件:cd~ mkdir matlab_iso sudo mount -t auto -o loop LinuxMatlab/R2015b_glnxa64.iso matlab_iso/ 2、安装Matlab:sudo ./matlab_iso/install 输入安装**:09806-07443-53955-64350-21751-41297 结束安装后取消iso挂载: umount matlab_iso/ sudo rm -r matlab_iso/ #删除空的文件夹 3、**:cd /usr/local/MATLAB/R2015b/bin sudo ./matlab 首先选择无internet手动**,选择license_standalone.lic。 然后将*****文件夹中的3个*.so文件复制到/usr/local/MATLAB/R2015b/bin/glnxa64目录下: [email protected]:~/LinuxMatlab/Linux64_*****$ sudo cp R2015b/bin/glnxa64/libcufft.so.7.0.28 /usr/local/MATLAB/R2015b/bin/glnxa64 sudo cp R2015b/bin/glnxa64/libinstutil.so /usr/local/MATLAB/R2015b/bin/glnxa64 sudo cp R2015b/bin/glnxa64/libmwservices.so /usr/local/MATLAB/R2015b/bin/glnxa64 4、创建快捷方式:打开Ubuntu软件中心,搜索matlab,点击install,在弹出的安装路径填入:/usr/local/MATLAB/R2015b 用户权限不用填,表示全部用户可用、gcc不填 完成安装,在启动栏可以看到有matlab图标。 注意首次打开MATLAB需在终端输入sudo /usr/local/MATLAB/R2015b/bin/matlab才行。 如果Ubuntu软件中心的MATLAB支持接口不是首次安装,出现路径错误,要修改MATLAB的路径可进入/etc/matlab/debconf文件修改。 如果点击启动栏上的MATLAB出现java.lang.runtime.Exception错误,只需要在终端中输入以下命令即可: sudo chmod -R a+rw ~/.matlab 设置matlab默认工作路径:预设-常规-初始工作文件夹-/home/zili/Programming/MATLAB 在caffe通过make mattest后,可选择设置matlab默认工作路径: sudo gedit /usr/local/MATLAB/R2015b/toolbox/local/matlabrc.m 在该文件最后加入以下语句: cd '/home/zili/Programming/MATLAB' Ubuntu下Matlab路径不能永久保存的问题及其解决方案 原因:pathdef.m文件的权限问题 解决方法: cd /usr/local/MATLAB/R2015b/toolbox/local sudo chmod 777 pathdef.m 五、安装Anaconda3到官网下载anaconda3地址:https://www.anaconda.com/download/#linux 下载好后执行: bash ~/Downloads/Anaconda3-5.1.0-Linux-x86_64.sh 注意选择将Anaconda加入Path中。 Anaconda换源:制定清华的源: conda config --add channelshttps://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/ 有资源显示源地址: conda config --set show_channel_urls yes 六、编译安装OpenCV3.4.0注意OpenCV版本!以下方式编译OpenCV3.4.1可能会出错。 1、安装依赖:sudo apt-get install --assume-yes libopencv-dev build-essential cmake gitlibgtk2.0-dev pkg-config python-dev python-numpy libdc1394-22 libdc1394-22-dev libjpeg-dev libpng12-dev libtiff5-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libxine2-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev libtbb-dev libqt4-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip sudo apt-get install ffmpeg libgtk-3-dev python3-numpy qtbase5-dev unzip 2、下载和编译
2023-10-27 2022-08-15 2022-08-17 2022-09-23 2022-08-13 |
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