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Jupyter Notebook - Deep Neural Networks Demo (GPU)

The Notebook app will launch a Notebook session on a compute node and allow you to connect directly to it in a web browser. It can be used to run GPU applications such as Tensorflow and Keras. Below is a demo of this to get you started.

  • Select the queue to which you wish to submit and enter the number of wallclock hours you require. Your notebook will be terminated after this number of hoursr elapses.
  • Click Launch.
  • Wait for your interactive session to change to Running state. This may take some time depending on how busy the queue and system is.
  • Click on 'Connect to Jupyter' once the button appears.
  • Once in Jupyter, select 'Upload' in the upper right corner. You may wish to create a folder or change into a different directory to put the demo notebook first.
  • Select the demo notebook file you downloaded earlier. Click the blue Upload button to complete the upload. Then click the dnn.ipynb item from the file list to launch the notebook.
  • You should now have the notebook loaded and you should be able to re-execute the code cells, or modify them to your needs.