Ubuntu 18.10 下安裝CUDA10/CUDA10.1

GPU：GeForce840M
顯卡驅動：預裝，版本390
筆記本
1.降級gcc 使用gcc5

sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install gcc-5 g++-5
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 60 --slave /usr/bin/g++ g++ /usr/bin/g++-5

2安裝python3.7

sudo apt update
sudo apt upgrade -y
sudo apt install software-properties-common
sudo add-apt-repository ppa:deadsnakes/ppa
sudo apt install python3.7 -y
sudo rm -rf  /usr/bin/python3
sudo ln -s /usr/bin/python3.7 /usr/bin/python3

查找python位置

 which python

3.安裝n卡驅動
第一種：

1. 更新apt-get源列表
sudo apt-get update
sudo apt-get upgrade
2. 添加驅動源
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt install nvidia-driver-410

3.安裝cuda10.0

sudo sh  *.run

一直按Enter直至把聲明看完

如果驅動是獨立安裝了，一定要選擇不安裝驅動！選擇如下：

有如下信息 可以忽略：
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of version at least 384.00 is required for CUDA 10.0 functionality to work.

To install the driver using this installer, run the following command, replacing with the name of this run file:

4.添加環境變量

sudo gedit ~/.bashrc
添加到最后
export PATH=$PATH:/usr/local/cuda/bin  
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64  
export LIBRARY_PATH=$LIBRARY_PATH:/usr/local/cuda/lib64  
保存退出
source ~/.bashrc

5.測試是否成功

sudo rm -rf /usr/local/cuda  
sudo ln -s /usr/local/cuda-10.0 /usr/local/cuda  
nvcc --version  

cd /usr/local/cuda/samples/1_Utilities/deviceQuery 
sudo make
./deviceQuery

第二種：

sudo add-apt-repository ppa:graphics-drivers
 sudo apt-get update
 ubuntu-drivers devices

如果系統中有老版本顯卡驅動，要先卸載
sudo apt-get remove --purge nvidia*
sudo ubuntu-drivers autoinstall
#這里我安裝了430，你可以選擇其他的
sudo apt-get install nvidia-430

重啟

#輸入
nvidia-smi

這個圖是正確結果

sudo sh cuda_10.1.105_418.39_linux.run

安裝完后，在.bashrc文件末尾添加環境變量

sudo vim ~/.bashrc

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

保存退出后，輸入以下命名
source ~/.bashrc

測試是否成功

sudo rm -rf /usr/local/cuda  
sudo ln -s /usr/local/cuda-10.0 /usr/local/cuda  
nvcc --version  

 cd /usr/local/cuda/samples/1_Utilities/deviceQuery 
sudo make
./deviceQuery

這樣的結果就ok 下邊有個pass

在去官網找linux 的cudnn https://developer.nvidia.com/rdp/cudnn-download

下載完成后，輸入以下命令解壓文件

 tar -zxvf cudnn-10.1-linux-x64-v7.5.1.10.tgz

sudo cp cuda/include/cudnn.h /usr/local/cuda/include/    #解壓后的文件夾名為cuda
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/ 
sudo chmod a+r /usr/local/cuda/include/cudnn.h           #增加所有用戶對文件的可執行權限
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

查看cudnn 版本

cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

至此安裝結束
可以玩玩tensorflow-gpu了

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