Jupyter Environment for Scientific Notebook & AI Research

This repository provides a Docker-based Jupyter environment specialized for scientific computing and AI research, equipped with PyTorch with CUDA 12.1 and Julia.

Owner

• Username: yspkm
• Email: yosepkim@snu.ac.kr

Features

• PyTorch 2.2.0 with CUDA 12.1 and cuDNN 8 support for high-performance GPU acceleration.
• Julia environment tailored for scientific computing.
• Easy to use and deploy with Docker.
• Licensed under GPL-3.0, ensuring freedom to share and modify the software while ensuring it remains free.

Getting Started

Prerequisites

• Docker installed on your system
• NVIDIA Docker runtime for GPU support

Build

To build the Docker image, run the following command in the terminal:

make build

This command reads environment variables from the .env file and builds a Docker image with the specified PyTorch and CUDA versions.

Run

To start the Jupyter Lab server:

make up

This command runs the container in detached mode, forwarding the necessary ports, and mounts your home directory (/home/yosepkim) to /workspace within the container.

Stop

To stop and remove the running container:

make down

Clean

To remove the Docker image:

make clean

Help

To view available commands:

make help

This will output:

Available commands:
  make build    - Build the Docker image.
  make up       - Run the Docker container.
  make down     - Stop and remove the Docker container.
  make clean    - Remove the Docker image.
  make help     - Display this help message.

How to Use

Once the container is up, access the Jupyter Lab interface by navigating to http://<ip address>:8888 in your web browser. The environment is pre-configured with PyTorch and Julia for scientific notebook and AI research purposes.

Font 위치: /usr/share/fonts/truetype/nanum/*.ttf

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.