目录

一、安装CUDA

二、下载cuDNN

三、设置环境变量

四、查看安装是否成功

一、安装CUDA

1.博主这里选择9.0版本,CUDA历代版本下载的网址为：https://developer.nvidia.com/cuda-toolkit-archive

2.如下选择

3.执行指令：

      sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb
      sudo apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub
      sudo apt-get update
      sudo apt-get install cuda
  
 

二、下载cuDNN

1.网址：https://developer.nvidia.com/rdp/cudnn-archive

2.选择7.4.1的cuDNN Library for Linux下载

3.解压：

sudo tar -zxvf cudnn-9.0-linux-x64-v7.4.1.5.tgz
 

4.复制cuDNN的文件到已经安装好的目录中

      sudo cp cuda/include/cudnn.h /usr/local/cuda/include
      sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
      sudo chmod a+r /usr/local/cuda/include/cudnn.h
      sudo chmod a+r /usr/local/cuda/lib64/libcudnn*
  
 

三、设置环境变量

1.编辑环境变量文件.bashrc

sudo gedit ~/.bashrc
 

2.最下面添加这几句话

      export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
      export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
      export CUDA_HOME=/usr/local/cuda
  
 

四、查看安装是否成功

1.重启电脑/注销用户

2.打开终端，输入

nvcc -V
 

应该显示如下类似字样

      nvcc: NVIDIA (R) Cuda compiler driver
      Copyright (c) 2005-2017 NVIDIA Corporation
      Built on Fri_Sep__1_21:08:03_CDT_2017
      Cuda compilation tools, release 9.0, V9.0.176
  
 

3.输入

nvidia-smi
 

应该显示如下类似字样

      Wed May 15 19:50:57 2019
      +-----------------------------------------------------------------------------+
      | NVIDIA-SMI 384.130 Driver Version: 384.130 |
      |-------------------------------+----------------------+----------------------+
      | GPU  Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
      | Fan  Temp  Perf  Pwr:Usage/Cap| Memory-Usage | GPU-Util  Compute M. |
      |===============================+======================+======================|
      |   0  GeForce GTX 108...  Off  | 00000000:01:00.0 On | N/A |
      | 20%   39C P8 16W / 250W | 387MiB / 11169MiB | 1% Default |
      +-------------------------------+----------------------+----------------------+
      +-----------------------------------------------------------------------------+
      | Processes: GPU Memory |
      |  GPU PID   Type   Process name Usage |
      |=============================================================================|
      | 0 1105 G   /usr/lib/xorg/Xorg 219MiB |
      | 0 2062 G   compiz 41MiB |
      | 0 2464 G   /proc/self/exe 99MiB |
      | 0 3256 G   ...passed-by-fd --v8-snapshot-passed-by-fd 24MiB |
      +-----------------------------------------------------------------------------+
  
 

说明CUDA和cuDNN安装成功~(没有很可能是环境变量设置出了问题）

文章来源: nickhuang1996.blog.csdn.net，作者：悲恋花丶无心之人，版权归原作者所有，如需转载，请联系作者。

原文链接：nickhuang1996.blog.csdn.net/article/details/90243205