The End-to-End AI for Science Bootcamp provides a step-by-step overview of the fundamentals of deep neural networks, walks attendees through the hands-on experience of building and improving deep learning models using a framework that uses the fundamental laws of physics to model the behavior of complex systems, and enables attendees to visualize the physically accurate outputs of the trained model in near real-time.
To run this tutorial you will need a machine with NVIDIA GPU, a RTX enabled GPU is necessary for working with the NVIDIA Omniverse™.
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Install the latest Docker or Singularity.
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The base containers required for the lab may require users to create a NGC account and generate an API key (https://docs.nvidia.com/ngc/ngc-catalog-user-guide/index.html#registering-activating-ngc-account)
The material is also tested to be working with NVIDIA A100 and A800 GPUs, kindly contact us if you are looking for instructions to deploy it in A100/A800 environment.
This materials was tested with both Docker and Singularity on an NVIDIA RTX 3080Ti GPU in an x86-64 platform installed with a driver version of 535.104.05.
This material can be deployed with either Docker or Singularity container, refer to the respective sections for the instructions.
To build a docker container, run:
sudo docker build -t <imagename>:<tagnumber> .
For instance:
sudo docker build -t openhackathons:ai-for-science .
and to run the container, run:
sudo docker run --gpus all --ipc=host --ulimit memlock=-1 --ulimit stack=67108864 -p 8011:8011 -p 8888:8888 -p 8899:8899 -v ${PWD}/workspace/python/source_code/extension:/workspace/python/source_code/extension -it --rm openhackathons:ai-for-science
The container launches jupyter lab and runs on port 8888
jupyter-lab --ip 0.0.0.0 --port 8888 --no-browser --allow-root
Then, open the jupyter lab in browser: http://localhost:8888
Start working on the lab by clicking on the Start_Here.ipynb notebook.
To build the singularity container, run:
singularity build --fakeroot --sandbox End-to-End-AI-for-Science.sif Singularity
Then, run the container:
singularity run --writable --nv End-to-End-AI-for-Science.simg jupyter-lab --no-browser --allow-root --ip=0.0.0.0 --port=8888 --NotebookApp.token="" --notebook-dir=/workspace/python
Then, open the jupyter lab in browser: http://localhost:8888
Start working on the lab by clicking on the Start_Here.ipynb notebook.
- Please go through the list of exisiting bugs/issues or file a new issue at Github.