1. Driver Installation
Open software updates, click on the attached drive, select the drive N card
First, the source added$ sudo add-apt-repository ppa:graphics-drivers/ppa $ sudo apt update
Check system gpu device
$ ubuntu-drivers devices
in this installation nvidia-driver-410, execution
$ APT-GET the install the sudo NVIDIA-410-Driver
Change restart the computer to view the information GPU
At this point the driver installed
2.cuda10.0 installation
First installation environment dependent
$sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev
Download cuda10.0 and related https://developer.nvidia.com/cuda-10.0-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=runfilelocal
After downloading to enter the download folder, install
$ Sudo sh cuda_10.0.130_410.48_linux.run
first prompted to select no, the rest of the yes or default
Then edit the environment variable, add the following, and enable: source ~ / .bashrc
export CUDA_HOME=/usr/local/cuda
export PATH=$PATH:$CUDA_HOME/bin
export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
After that, enter
$ Nvcc -V
Display following the installation was successful
$cd /usr/local/cuda-9.0/samples $sudo make
$./bin/x86_64/linux/release/deviceQuery
显示如下内容
3.cudnn7.5的安装
下载:https://developer.nvidia.com/rdp/cudnn-download
得到文件:cudnn-10.0-linux-x64-v7.5.0.56.tgz
进入到文件目录,执行
$ tar zxvf cudnn-10.0-linux-x64-v7.5.0.56.tgz
解压后得到 名为 cuda 的文件夹,需要将里面的几个文件拷贝到已安装的cuda文件夹下面,并赋予相应的权限
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*
之后执行cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
source ~/.bashrc
若显示以下内容表明安装成功
4.anaconda 安装
下载得到文件 Anaconda3-2018.12-Linux-x86_64.sh
在文件目录中,执行+
sudo sh Anaconda3-2018.12-Linux-x86_64.sh
出现如下选择yes
最后选择不安装vs code
安装完后需要执行
anaconda change Source:
Tsinghua University to develop the source:
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
Have the resources to show the source address:
conda config --set
show_channel_urls yes
5.tensorflow-gpu installation
Before installing install bazel, see the official installation manual
After installing bazel execution
conda install tensorflow-gpu
import tensorflow as tf
tf.__version__
hello = tf.constant('hello tensorflow')
sess = tf.Session()
sess.run(hello)