linux配环境.md

基础信息

GPU: A100 40G

OS: ubuntu 22.04

安装cuda版本:11.8

1. 安装nvidia驱动

sudo add-apt-repository ppa:graphics-drivers/ppa

sudo apt update

ubuntu-drivers devices
# 安装需要的版本
sudo apt install nvidia-driver-535-server

重启后即可nvidia-smi看见

2. 安装cuda

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

# 去掉勾选的driver，只安装cuda
sudo sh cuda_11.8.0_520.61.05_linux.run

配置环境变量

1. 打开profile 文件

vim /etc/profile

2. 添加环境变量

export PATH="$PATH:/usr/local/cuda-11.8/bin"
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda-11.8/lib64/"

3. 安装cudnn

从cudnn官网下载tar包，上传后

tar -xvf cudnn-linux-x86_64-8.9.7.29_cuda11-archive.tar

cd cudnn-linux-x86_64-8.9.7.29_cuda11-archive/

sudo cp include/cudnn*    /usr/local/cuda-11.8/include

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

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

验证：

cat /usr/local/cuda-11.8/include/cudnn_version.h | grep CUDNN_MAJOR -A 2

4. 安装anaconda

curl -O https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Linux-x86_64.sh

chmod +x Anaconda3-2024.06-1-Linux-x86_64.sh

./Anaconda3-2024.06-1-Linux-x86_64.sh

配置环境变量

1. 打开profile 文件

vim /etc/profile

2. 添加环境变量

export PATH=/root/anaconda3/bin:$PATH