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Jupyter is installed in most of the python modules. To make use of it you would do something like:
jupyter-notebook
However using it effectively on the cluster is a bit more complicated…
After Logging in your account check for your preferred python version as follows:
module avail 2>&1 | grep python
Now proceed to request for an interactive compute node where a configuration file and security measures will be established. A single core on an interactive node has proven sufficient for this exercise. Request an arbitrary interactive compute node as follows:
qsub -I -P PROJ0101 -q serial -l select=1:ncpus=1:mpiprocs=1:nodetype=haswell_reg
Note:
In your interactive compute node, load the preferred python module as follows:
module add chpc/python/3.6.0_gcc-6.3.0
You are not the only person on the system, so it is important to set up authentication on your notebook so that not everyone gets access to your notebook (and worse – your data).
So first one needs a configuration file, this can be done by passing the generate-config parameter to jupyter as follows:
[USERNAME@cnode0010 ~]$ jupyter-notebook --generate-config
Note
Next you need to generate your password (remember it – you'll need it when you connect later):
python
from notebook.auth import passwd passwd() Enter password: Verify password: 'sha1:f27008fdb0eb:4c2f305d5e230edca16c7059882ba3ba63bee03b'
Use the following command to access the “jupyter_notebook_config.py” file: $ cd /home/USERNAME/.jupyter/jupyter_notebook_config.py
Now edit the jupyter_notebook_config.py file, specifically edit the c.NotebookApp.passwd line.
c.NotebookApp.password = 'sha1:f27008fdb0eb:4c2f305d5e230edca16c7059882ba3ba63bee03b'
Remember to uncomment it, don't just copy and paste my hash in.
There might be a cleaner way of doing this… Please let us know if you have one!
VERY IMPORTANT: Do not add the lines below to your .ssh/config file on the cluster, you WILL break any attempt at parallel processing!
Open a terminal on your local machine and create a .ssh/config file.
touch .ssh/config
If your desktop system runs Windows, a simple way to deal with this is to run a unix-like environment inside Windows. You can either useCygwin Cygwin directly, or start a “Local Terminal” in MobaXterm. From this terminal you can edit the local ~/.ssh/config file as if you were working on a Linux computer.
Continue to edit the ~/.ssh/config file on your local machine by adding in these lines:
Host cnode*
Hostname %h
User YOURUSERNAME
ProxyCommand ssh YOURUSERNAME@lengau.chpc.ac.za nc %h 22
LocalForward 8838 localhost:8838
Note
Ultimately, what this will do is allow you to ssh directly to a compute node (note you can only do this to nodes where you currently have a job running).
ssh cnode*
You should be prompted for your password, twice. This is because the ssh logs in to Lengau first and then from Lengau it logs into the the compute node.
You are now ready to roll…
In your browser go to: http://localhost:8838
The jobscript will look something like:
#!/bin/bash #PBS -P SHORTNAME #PBS -q serial #PBS -l select=1:ncpus=8:mpiprocs=1 #PBS -l walltime=08:00:00 #PBS -N Jupyter #PBS -m abe #PBS -M YOUR@EMAIL.ADDRESS module add chpc/python/3.6.0_gcc-6.3.0 JUPYTERPORT=8838 # you could change this too, if you wanted to. hostname > ~/jupyter.host jupyter-notebook --port=${JUPYTERPORT} --no-browser
If you submit that job and wait for it to start running then you can check which host the session is running on with:
cat ~/jupyter.host
Then, again on your local machine, you need to connect to the compute node, i.e. ssh cnode0101. If you are working in Windows, do this from your Cygwin or MobaXterm terminal command line. You will be prompted for your Lengau login password.