Create notebook_cuit.rst

docs/notebook_cuit.rst

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+=========================================
+Running jupyter notebook on CUIT machines
+=========================================
+
+Foreword: this is best run in a "screen" (virtual terminal) session.
+See https://linuxize.com/post/how-to-use-linux-screen/ for details.
+
+First, we need to get a compute node allocated for our notebook, either from the global pool::
+
+  salloc -N 1 -A ocpbgc --exclusive
+
+or from our own::
+
+  salloc -N 1 -A ocpbgc -p ocpbgc --exclusive
+
+You can ask for more than one node (-N 2 for 2 nodes,...). Once our node is allocated we can
+activate our conda environment::
+
+  source activate myenv
+  
+We also need to disable this environment variable::
+
+  unset XDG_RUNTIME_DIR
+  
+And find the ip of the node::
+
+  export ip=$( srun hostname -i )
+
+Note the ip address, will be refered to <nodeip> below.
+
+Now we can start the notebook (here I start it in my workspace, not home directory)::
+
+  srun jupyter notebook --no-browser --ip=$ip --notebook-dir=/rigel/ocpbgc/users/$whoami
+
+The notebook should be running on port 8888. If not adapt the next items to the current port.
+Leave this terminal alone, or detach the screen session. In a new terminal, we're gonna create
+a tunnel to the 8888 port of the compute node to the 8010 port of our workstation/laptop, bouncing off
+the login node (e.g. habanero)::
+
+  ssh -L 8010:<nodeip>:8888 <name_of_login_node>
+  
+ In your web browser, type::
+ 
+  localhost:8010
+  
+ And you should be connected to your notebook.