Ubuntu18.04下安装CUDA

作者: foochane | 来源:发表于2018-07-30 10:21 被阅读1077次

    1.下载 cuda.xxx.run 文件

    https://developer.nvidia.com/cuda-downloads,下载 cuda_9.1.85_387.26_linux.run文件


    2.在终端运行该条指令即可:

    $ sudo sh cuda_9.1.85_387.26_linux.run --no-opengl-libs

    之后是一些提示信息,ctrl+c 直接结束后输入 accept。
    在提示是否安装显卡驱动时,一定选择 no(之前安装过对应显卡版本的驱动).
    其他各项提示选择是,并默认安装路径即可。提示有 y 的输入 y,没有则按 enter 键。

    $ sudo sh cuda_9.1.85_387.26_linux.run 
    [sudo] password for fc: 
    Logging to /tmp/cuda_install_8138.log
    Using more to view the EULA.
    End User License Agreement
    --------------------------
    
    
    Preface
    -------
    
    The Software License Agreement in Chapter 1 and the Supplement
    in Chapter 2 contain license terms and conditions that govern
    the use of NVIDIA software. By accepting this agreement, you
    agree to comply with all the terms and conditions applicable
    to the product(s) included herein.
    
    
    NVIDIA Driver
    
    
    Description
    
    This package contains the operating system driver and
    fundamental system software components for NVIDIA GPUs.
    
    Do you accept the previously read EULA?
    accept/decline/quit: accept
    
    You are attempting to install on an unsupported configuration. Do you wish to continue?
    (y)es/(n)o [ default is no ]: y
    
    Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 387.26?
    (y)es/(n)o/(q)uit: n
    
    Install the CUDA 9.1 Toolkit?
    (y)es/(n)o/(q)uit: y
    
    Enter Toolkit Location
     [ default is /usr/local/cuda-9.1 ]: 
    
    Do you want to install a symbolic link at /usr/local/cuda?
    (y)es/(n)o/(q)uit: y
    
    Install the CUDA 9.1 Samples?
    (y)es/(n)o/(q)uit: y
    
    Enter CUDA Samples Location
     [ default is /home/fc ]: 
    
    Installing the CUDA Toolkit in /usr/local/cuda-9.1 ...
    Missing recommended library: libGLU.so
    Missing recommended library: libX11.so
    Missing recommended library: libXi.so
    Missing recommended library: libXmu.so
    Missing recommended library: libGL.so
    
    Installing the CUDA Samples in /home/fc ...
    Copying samples to /home/fc/NVIDIA_CUDA-9.1_Samples now...
    Finished copying samples.
    
    ===========
    = Summary =
    ===========
    
    Driver:   Not Selected
    Toolkit:  Installed in /usr/local/cuda-9.1
    Samples:  Installed in /home/fc, but missing recommended libraries
    
    Please make sure that
     -   PATH includes /usr/local/cuda-9.1/bin
     -   LD_LIBRARY_PATH includes /usr/local/cuda-9.1/lib64, or, add /usr/local/cuda-9.1/lib64 to /etc/ld.so.conf and run ldconfig as root
    
    To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-9.1/bin
    
    Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-9.1/doc/pdf for detailed information on setting up CUDA.
    
    ***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 9.1 functionality to work.
    To install the driver using this installer, run the following command, replacing <CudaInstaller> with the name of this run file:
        sudo <CudaInstaller>.run -silent -driver
    
    Logfile is /tmp/cuda_install_8138.log
    Signal caught, cleaning up
    
    

    之后声明一下环境变量,并将其写入到 ~/.bashrc 文件(在用户目录下)的尾部,输入内容如下

    export PATH=/usr/local/cuda-9.1/bin:$PATH
    export LD_LIBRARY_PATH=/usr/local/cuda-9.1/lib64:$LD_LIBRARY_PATH
    

    保存退出,并输入下面指令使环境变量立刻生效:

    $source ~/.bashrc
    



    3.设置环境变量和动态链接库,在命令行输入:

    $ sudo vim /etc/profile
    

    在打开的文件末尾加入:

    export PATH=/usr/local/cuda/bin:$PATH
    



    4.创建链接文件

    $ sudo vim /etc/ld.so.conf.d/cuda.conf
    

    在打开的文件中添加如下语句:

    /usr/local/cuda/lib64
    

    保存退出,然后执行

    $ sudo ldconfig 
    

    使链接立即生效。



    5.测试 cuda 的 Samples

    切换到 CUDA 9.1 Samples 默认安装路径(即在/home/用户/ work/NVIDIA_CUDA-9.1_Samples 目录下), 终端下输入

    $ cd NVIDIA_CUDA-9.1_Samples
    $ sudo make all -j4
    $ cd bin/x86_64/linux/release
    $ ./deviceQuery
    

    如果 CUDA 安装成功,则有:

    $ ./deviceQuery
    ./deviceQuery Starting...
    
     CUDA Device Query (Runtime API) version (CUDART static linking)
    
    Detected 1 CUDA Capable device(s)
    
    Device 0: "GeForce GT 635M"
      CUDA Driver Version / Runtime Version          9.0 / 8.0
      CUDA Capability Major/Minor version number:    2.1
      Total amount of global memory:                 1985 MBytes (2081619968 bytes)
      ( 2) Multiprocessors, ( 48) CUDA Cores/MP:     96 CUDA Cores
      GPU Max Clock rate:                            950 MHz (0.95 GHz)
      Memory Clock rate:                             900 Mhz
      Memory Bus Width:                              128-bit
      L2 Cache Size:                                 131072 bytes
      Maximum Texture Dimension Size (x,y,z)         1D=(65536), 2D=(65536, 65535), 3D=(2048, 2048, 2048)
      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: 32768
      Warp size:                                     32
      Maximum number of threads per multiprocessor:  1536
      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): (65535, 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:                     No
      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 Domain ID / Bus ID / location ID:   0 / 1 / 0
      Compute Mode:
         < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) >
    
    deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 9.0, CUDA Runtime Version = 8.0, NumDevs = 1, Device0 = GeForce GT 635M
    Result = PASS
    
    

    6.卸载CUDA

    在/usr/local/cuda/bin 目录下,有cuda 自带的卸载工具uninstall_cuda_9.1.pl

    $ cd /usr/local/cuda/bin
    $ sudo ./uninstall_cuda_9.1.pl
    

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