Docker gpu and jupyter lab

도커에서 Container 포트와 Host 포트의 개념

if 8888 port is already in use

docker run -d -v `pwd`:/whale_test -it --name dev_jup --gpus all -p 8890:8890 --restart=always mydocker

and

jupyter lab --allow-root --ip 0.0.0.0 --port=8890

done.

Summary

docker run -d -v `pwd`:/whale_test -it --name dev_jup --gpus all -p 8888:8888 --restart=always mydocker

docker exec -it container_id bash

conda install -c conda-forge jupyterlab

jupyter lab --allow-root --ip 0.0.0.0

nvidia-docker (not necessarily)

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

sudo apt-get update

sudo apt-get install -y nvidia-docker2

sudo systemctl restart docker

sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi

run Docker (with or without nvidia-docker)

nvidia-docker run -d -v `pwd`:/whale_test -it --name dev123 --gpus all -p 8888:8888 --restart=always mydocker

docker run -d -v `pwd`:/whale_test -it --name dev123 --gpus all -p 8888:8888 --restart=always mydocker

Install jupyter lab in container

conda install -c conda-forge jupyterlab

Jupyter lab

jupyter lab --allow-root --ip 0.0.0.0

Appendix

Reference

docker with pytorch and jupyter: https://89douner.tistory.com/96
nvidia-docker installation: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker
Docker 컨테이너 안에 jupyter 접속하기: https://jybaek.tistory.com/812
docker container with jupyter labhttps://anweh.tistory.com/68
host port and container port: https://m.blog.naver.com/PostView.naver?isHttpsRedirect=true&blogId=alice_k106&logNo=220278762795