GPU:
CPU:
RAM:
硬盘/SSD:
PSU:
散热:
主板:
CPU:i7-9700k
GPU:RTX-2080ti
RAM:DDR4 3000MHz 16G * 4
SSD:SATA SSD 512G
PSU:1000w
散热:塔式散热
主板:Z390
下载Ubuntu18.04LTS镜像,用UltraISO制作U盘启动盘,按照提示一步一步安装
备份配置文件:sudo mv /etc/apt/sources.list /etc/apt/sources.list.bak
将以下内容复制到/etc/apt/sources.list
文件中
deb http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-security main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-updates main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-backports main restricted universe multiverse
deb http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse
deb-src http://mirrors.aliyun.com/ubuntu/ bionic-proposed main restricted universe multiverse
更新
sudo apt update
sudo apt upgrade
将以下内容复制到~/.pip/pip.conf
文件中
[global]
index-url=http://mirrors.aliyun.com/pypi/simple/
trusted-host=mirrors.aliyun.com
chrome
sogou-linux
wps-linux
不需要先单独安装驱动
sudo apt install gcc
sudo apt install cmake
选择合适的cuda版本,tensorflow1.13不支持cuda10.1
选择合适的cuda版本,tensorflow1.13不支持cuda10.1
选择合适的cuda版本,tensorflow1.13不支持cuda10.1
从官网下载cuda安装脚本
Snipaste_2019-04-09_07-58-23.png
安装cuda的过程中会自动安装最新的驱动
安装完成后在.bashrc
中设置环境变量
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
运行source .bashrc
使其生效
从官网下载cudnn,需登录
Snipaste_2019-04-09_08-01-02.png
解压,复制文件到/usr/local/cuda
相关文件夹内
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 /usr/local/cuda/lib64/libcudnn*
下载miniconda3并安装,安装完成后source ~/.bashrc
新建python虚拟环境
conda create -n <env-name> python=3.6
进入python虚拟环境
conda activate <env-name>
安装python包
conda install <package-name>
tensorflow/pytorch
conda install tensorflow-gpu
conda install pytorch
numpy
pandas
pillow
jupyter
Pycharm
VS Code
Vim/Emacs/Sublime
监控CPU和RAM
htop
监控GPU
watch -n 1 nvidia-smi
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