{"repo":"iot-salzburg/gpu-jupyter","free":true,"listed":false,"github":"https://github.com/iot-salzburg/gpu-jupyter","clone":"git clone https://github.com/iot-salzburg/gpu-jupyter.git","description":"GPU-Jupyter: Your GPU-accelerated JupyterLab with a rich data science toolstack, TensorFlow and PyTorch for your reproducible deep learning experiments.","language":"Jupyter Notebook","stars":766,"topics":["reproducible-research","gpu-acceleration","gpu-computing","jupyter","jupyter-server","jupyterlab","pytorch","tensorflow","docker","environment"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"GPU-Jupyter GPU-Jupyter: Your GPU-accelerated JupyterLab with PyTorch, TensorFlow, and a rich data science toolstack for your reproducible deep learning experiments. TL;DR Open http://localhost:8848 using the token printed in the terminal. See Quickstart below for requirements and all configuration options. Welcome to this project, which provides a GPU-capable environment based on NVIDIA's official CUDA Docker image and the popular Jupyter's Docker Stacks. By utilizing version control for the source code, tagged data spaces, seeds for the random functions within isolated Docker containers, our solution empowers researchers to conduct fully reproducible and sharable machine-learning experiments . Architecture of the GPU-Jupyter Docker image on top of NVIDIA and Docker. Please find an example of how to use GPU-Jupyter to make your deep learning research reproducible with one single command on github.com/iot-salzburg/reproducible-research-with-gpu-jupyter . Contents 1. Quickstart 2. Configuration - Docker parameters - Available GPU-Jupyter Images - Set a Static Token - Deploy with Docker Compose - Adaptions for using Tensorboard - Customized installations - Share your customized Dockerfile 3. Build Your Image - Configuration of the Dockerfile-Generation - Set NVIDIA CUDA Base Image - Specify Jupyter Docker Stacks Version 4. Issues and Contributing - Frequent Issues - Contribution 5. Cite This Work Quickstart 1. Requirements: - NVIDIA GPU with drivers - CUDA - Docker - NVIDIA Con","default_branch":null,"files":null,"tree":[],"storefront":"/r/iot-salzburg","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/iot-salzburg/gpu-jupyter/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}