顺德网站制作案例平台,WordPress设置评论通过,开发公司账务处理,app开发设计安装ubuntu22.04系统
首先#xff0c;先压缩windows分区#xff0c;按住Win X快捷键#xff0c;选择磁盘管理,压缩分区#xff0c;压缩出新的分区用于安装ubuntu22.04
windows插入系统盘#xff0c;点击重启#xff0c;一直按F12,选择系统盘启动方式语言选择chinese–…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 sshubuntu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-essentialWARNING: 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
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cudnn8.9.6
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 ar /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$(dpkg --print-architecture) signed-by/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \$(lsb_release -cs) stable | sudo tee /etc/apt/sources.list.d/docker.list /dev/null # 设置稳定的仓库。安装docker-ce及配套
sudo apt update # 上一步设置仓库后要更新源
sudo apt install docker-ce docker-ce-cli containerd.io docker-compose-plugin # 安装docker-ce和配套安装nvidia-container-toolkit
# Add the package repositories
distributionubuntu22.04
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$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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生成激活码 https://blog.csdn.net/weixin_73546177/article/details/132033297
参考文档 https://zhuanlan.zhihu.com/p/338507526 https://www.cnblogs.com/ksky-2023/p/17389977.html https://yinguobing.com/install-cudnn8-with-tar-file/
