lspci | grep -i nvidia
uname -m && cat /etc/*release
#for case1: original driver installed by apt-get: sudo apt-get remove --purge nvidia* #for case2: original driver installed by runfile: sudo chmod +x *.run sudo ./NVIDIA-Linux-x86_64-384.59.run --uninstall
sudo gedit /etc/modprobe.d/blacklist.conf
在文本最後添加:html
blacklist nouveau options nouveau modeset=0
而後執行:linux
sudo update-initramfs -u
重啓以後,能夠查看nouveau有沒有運行:ubuntu
lsmod | grep nouveau # 沒輸出表明禁用生效
sudo service lightdm stop #這會關閉圖形界面
按Ctrl-Alt+F1進入命令行界面,輸入用戶名和密碼登陸。bash
驅動網址https://www.nvidia.cn/Download/index.aspx?lang=cnide
#給驅動run文件賦予執行權限: sudo chmod +x NVIDIA-Linux-x86_64-384.59.run #後面的參數很是重要,不可省略: sudo ./NVIDIA-Linux-x86_64-384.59.run –no-opengl-files
nvidia-smi #若列出GPU的信息列表,表示驅動安裝成功 nvidia-settings #若彈出設置對話框,亦表示驅動安裝成功
網址http://developer.nvidia.com/cuda-downloads 選擇runfile安裝post
sudo sh cuda_<version>_linux.run
開始安裝以後,須要閱讀說明,可使用Ctrl + C直接閱讀完成,或者使用空格鍵慢慢閱讀。下面爲安裝選項:測試
(是否贊成條款,必須贊成才能繼續安裝) accept/decline/quit: accept (這裏不要安裝驅動,由於已經安裝最新的驅動了,不然可能會安裝舊版本的顯卡驅動,致使重複登陸的狀況) Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 410.48? (y)es/(n)o/(q)uit: n Install the CUDA 10.0 Toolkit?(是否安裝CUDA 10 ,這裏必需要安裝) (y)es/(n)o/(q)uit: y Enter Toolkit Location(安裝路徑,使用默認,直接回車就行) [ default is /usr/local/cuda-10.0 ]: Do you want to install a symbolic link at /usr/local/cuda?(贊成建立軟連接) (y)es/(n)o/(q)uit: y Install the CUDA 10.0 Samples?(不用安裝測試,自己就有了) (y)es/(n)o/(q)uit: n Installing the CUDA Toolkit in /usr/local/cuda-10.0 ...(開始安裝)
sudo gedit ~/.bashrc
末尾加入ui
export PATH=/usr/local/cuda-8.0/bin:$PATH export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
更新命令行
source ~/.bashrc
查看cuda版本code
nvcc -V
CUDA Sample測試:
#編譯並測試設備 deviceQuery: cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery make ./deviceQuery #編譯並測試帶寬 bandwidthTest: cd ../bandwidthTest make ./bandwidthTest
若是這兩個測試的最後結果都是Result = PASS,說明CUDA安裝成功。
在命令行中輸入
sudo apt-get remove cuda sudo apt-get autoclean sudo apt-get remove cuda*
而後在目錄切換到usr/local/下
cd /usr/local/ sudo rm -r cuda-9.1
下載對應版本cuDNN https://developer.nvidia.com/cudnn
tar xvzf cudnn-9.2-linux-x64-v7.1 sudo cp -P cuda/include/cudnn.h /usr/local/cuda/include sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64 sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn* sudo ldconfig