Cheatsheets
Install Docker: The following steps can be used to setup NVIDIA Container Toolkit on Ubuntu LTS - 16.04, 18.04, 20.4 and Debian - Stretch, Buster distributions 1:
curl https://get.docker.com | sh \
&& sudo systemctl --now enable docker
sudo usermod -aG docker $USER
Setting up NVIDIA Container Toolkit (after system reboot):
distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \
&& 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.list
To enable CUDA on WSL and MIG, refer to the guide 1. Install the nvidia-docker2 package:
sudo apt-get update
sudo apt-get install -y nvidia-docker2
sudo systemctl restart docker
Now test the installation:
docker run --rm --gpus all nvidia/cuda:11.1.1-base nvidia-smi
Tensorflow containers requires special arguments to bypass the system limit (increasing shared memory):
docker run \
--gpus all -it \
--shm-size=1g --ulimit memlock=-1 \
--ulimit stack=6710886 \
nvcr.io/nvidia/tensorflow:19.06-py3
Reference
Two options:
Chinese input:
Install sogou pinyin
Install wechat:
2021-8-3: Tested on Ubuntu 20.04.02 LTS with kernel 5.8.0-43-generic
Note: caution using xhost + as it also allows malicious access. Prefer --network=host when accessing your local x-server from docker. (Reference)
docker run -d \
--name wechat \
--device /dev/snd \
--ipc="host" \
--network=host \
-v /tmp/.X11-unix:/tmp/.X11-unix \
-v $HOME/Documents/wechat:/WeChatFiles \
-e DISPLAY=unix$DISPLAY \
-e XMODIFIERS=@im=fcitx \
-e QT_IM_MODULE=fcitx \
-e GTK_IM_MODULE=fcitx \
-e AUDIO_GID=`getent group audio | cut -d: -f3` \
-e GID=`id -g` \
-e UID=`id -u` \
bestwu/wechat
Icon extension
sudo apt install gnome-shell-extension-top-icons-plus
gnome-extensions-app
Compatibility
Pigz Supports only tar.gz files:
sudo apt install pigz
tar -c --use-compress-program=pigz -f <filename>.tar.gz <dir-to-zip>