【环境搭建】ubuntu工作站搭建全流程（显卡4090）

安装ubuntu22.04系统

首先，先压缩windows分区，按住Win + X快捷键，选择磁盘管理,压缩分区，压缩出新的分区用于安装ubuntu22.04

windows插入系统盘，点击重启，一直按F12,选择系统盘启动方式
语言选择chinese–>最小化安装，且安装时不进行更新–>分区(必备的分区:swap(20G)、efi(系统启动必备)100M足够、根目录(/)一般为系统盘越大越好、家目录(/home)选择额外的硬盘挂载)
启动目录选择刚刚制作efi的盘符目录
安装等待
新安装的ubuntu系统需要被远程连接
- 安装 SSH 服务器

sudo apt update
sudo apt install openssh-server

确认 SSH 服务已启动

sudo systemctl status ssh

出现下面信息表示处于激活状态

● ssh.service - OpenBSD Secure Shell serverLoaded: loaded (/lib/systemd/system/ssh.service; enabled; vendor preset: enabled)Active: active (running) since Sat 2024-04-06 09:32:08 UTC; 10min ago

配置防火墙

sudo ufw allow ssh

ubuntu安装driver,cuda,cudnn

安装驱动Nvidia(530.41)

ERROR: Unable to find the development tool `cc` in your path; please make sure that you have the package 'gcc' installed.  If gcc is installed on your system, then please check that `cc` is in your PATH.

解决方法：

查看gcc是否被安装

gcc --version

或者

g++ --version

如果显示命令未找到，表示未安装gcc

安装gcc

apt update  
apt install build-essential

 WARNING: The symbolic link '/usr/lib/libGL.so.1' does not exist.  This is necessary for correct operation of the NVIDIA Accelerated Graphics Driver for Linux-x86_64.  You can create this symbolic link manually by executing ln -sf /usr/lib/x86_64-linux-gnu/libGL.so.1 /usr/lib/libGL.so.1.

530.41驱动地址
bash ./NVIDIA-Linux-x86_64-530.41.03.run
输入nvidia-smi命令，出现以下信息，表明成功
在这里插入图片描述

问题：输入nvidia-smi命令，出现信息慢
解决方法：
打开持久模式
nvidia-smi -pm 1

安装cuda11.8

cuda地址

wget https://developer.download.nvidia.com/compute/cuda/11.8.0/local_installers/cuda_11.8.0_520.61.05_linux.run
sudo sh cuda_11.8.0_520.61.05_linux.run

添加cuda环境变量

vim ~/.bashrc
export PATH=/usr/local/cuda-11.8/bin:$PATH  
export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH
source ~/.bashrc

输入nvcc -V检查cuda变量是否成功

安装cudnn（8.9.6）

cudnn地址
选择下载的是tar包，解压后分别放到cuda相应位置就好

解压tar.xz文件

tar -xf cudnn-linux-x86_64-8.9.6.50_cuda11-archive.tar.xz

将该解压包cudnn-linux-x86_64-8.9.6.50_cuda11-archive重命名为cuda

mv cudnn-linux-x86_64-8.9.6.50_cuda11-archive cuda

将cuda下的头文件拷贝到/usr/local/cuda-11.8对应目录下

cp cuda/include/cudnn*.h /usr/local/cuda-11.8/include

将cuda下的库文件拷贝到/usr/local/cuda-11.8对应目录下

cp -P cuda/lib/libcudnn* /usr/local/cuda-11.8/lib64

赋予文件读取权限

chmod a+r /usr/local/cuda-11.8/include/cudnn*.h /usr/local/cuda-11.8/lib64/libcudnn*

建立软连接，将环境映射到miniconda3/envs下

cd /data/miniconda3/envs
ln -s /data/miniconda3/envs/* ./

执行conda activate env_name查看是否链接成功

supervisor(监督python程序)

安装supervisor

apt install supervisor

生成配置文件

echo_supervisord_conf > /etc/supervisord.conf

修改配置文件，指定工程配置

vim /etc/supervisord.conf

在末尾加上

[include]
files = /etc/supervisord.d/*.conf

启动supervisor

supervisord -c /etc/supervisord.conf

安装docker

安装基础docker
- 设置仓库

sudo apt update # 更新源sudo apt install ca-certificates curl gnupg lsb-release # 安装依赖curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg # 将官方Docker存储库的GPG密钥添加到系统
echo "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \$(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null # 设置稳定的仓库。

安装docker-ce及配套

sudo apt update # 上一步设置仓库后，要更新源
sudo apt install docker-ce docker-ce-cli containerd.io docker-compose-plugin # 安装docker-ce和配套

安装nvidia-container-toolkit

# Add the package repositories
distribution="ubuntu22.04"
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.listsudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo systemctl restart docker

在/etc/docker/daemon.json中写入下面镜像源

{"registry-mirrors": ["https://registry.docker-cn.com","https://docker.mirrors.ustc.edu.cn","https://hub-mirror.c.163.com"]
}

执行命令使得添加镜像源生效，并重启docker

安装Typora

sudo systemctl daemon-reload && sudo systemctl restart docker

安装企业微信

sudo apt-get install -f -y ./ukylin-wine_70.6.3.25_amd64.deb
sudo apt-get install -f -y ./ukylin-wxwork_1.0_amd64.deb

激活pycharm

激活码

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