Contents

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NVIDIA&CUDA Environment Setup (Brief Intro)

• Update source

  vim /etc/apt/sources.list 
  sudo apt-get update
  

• Update host environment

  vim /etc/resolv.conf
  # nameserver 8.8.8.8
  /etc/init.d/networking restart
  apt update && apt install cmake make openssh-client openssh-server sshpass -y
  dpkg-reconfigure tzdata
  export LANG=C.UTF-8
  

• Install Nvidia driver

  sudo apt-get install nvidia-driver-xxx
  sudo reboot
  nvidia-smi
  

• Install CUDA

  # cuda toolkit
  sudo apt install nvidia-cuda-toolkit
  wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
  sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
  wget https://developer.download.nvidia.com/compute/cuda/11.4.1/local_installers/cuda-repo-ubuntu1804-11-4-local_11.4.1-470.57.02-1_amd64.deb
  sudo dpkg -i cuda-repo-ubuntu1804-11-4-local_11.4.1-470.57.02-1_amd64.deb
  sudo apt-key add /var/cuda-repo-ubuntu1804-11-4-local/7fa2af80.pub
  sudo apt-get update
  sudo apt-get -y install cuda
  nvcc -V 	# verify cuda version
  
  # cudnn lib
  tar -xvf cudnn-linux-x86_64-8.x.x.x_cudaX.Y-archive.tar.xz
  sudo cp cudnn-*-archive/include/cudnn*.h /usr/local/cuda/include 
  sudo cp -P cudnn-*-archive/lib/libcudnn* /usr/local/cuda/lib64 
  sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
  sudo dpkg -i cudnn-local-repo-${OS}-8.x.x.x_1.0-1_amd64.deb
  sudo apt-get install libfreeimage3 libfreeimage-dev
  

• Install docker

  sudo apt install curl
  curl -fsSL https://get.docker.com | bash -s docker --mirror Aliyun
  docker
  install nvidia-docker2
  curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | \
  sudo apt-key add -
  distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
  curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | \
  sudo tee /etc/apt/sources.list.d/nvidia-docker.list
  # nvidia-container-runtime
  sudo apt-get install -y nvidia-docker2
  sudo pkill -SIGHUP dockerd
  systemctl restart docker
  systemctl daemon-reload
  cat /etc/docker/daemon.json 
  sudo docker ps -a
  

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PYTHON Environment Setup (Brief Intro)

• Build container

  sudo docker pull nvcr.io/nvidia/pytorch:21.10-py3
  sudo docker run --runtime=nvidia --gpus all --net host -it -d --name test nvcr.io/nvidia/pytorch:21.09-py3
  # exit
  sudo docker exec it test bash
  dpkg-reconfigure tzdata
  vim /etc/bash.bashrc
  # export LANG=C.UTF-8
  source /etc/bash.bashrc
  which python
  nvidia-smi
  

• Install conda

  wget -4 -c http://mirrors.aliyun.com/anaconda/miniconda/Miniconda3-latest-Linux-x86_64.sh
  bash Miniconda3-latest-Linux-x86_64.sh
  source ~/miniconda3/bin/activate
  conda init
  

• Create virtual environment

  conda create -n test python=3.9
  conda activate test
  

• Install libraries

  sudo apt install python3-dev python3-pip python3-venv
  # https://pytorch.org/get-started/locally/
  conda install pytorch==2.0.0 torchvision==0.15.0 torchaudio==2.0.0 pytorch-cuda=11.8 -c pytorch -c nvidia
  pip install --upgrade tensorflow
  pip install transformers
  which python
  pip list
  conda list
  

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Y.Z.

2023-11-20