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We are currently working on an experimental JupyterHub which will allow you to log on to the login nodes and run notebooks directly from the browser. If you want to test this out, you can try here: http://albedo0.dmawi.de:8000 Note that VPN is required! Currently access is provided only by request, please open a ticket on hpc@awi.de to get on the list during the testing phase. You will be presented with a login page, and after login, with a selection of job profiles. You can either run your notebook on a login node (not recommended), a compute node, or a GPU node. In case of a compute node or GPU node, yu need to specify which computing account SLURM should use. A list of available computing accounts is provided for you. Additionally, in the case of a GPU node, you need to specify which type of GPU you want to use (A40 or A100) and how many GPUs you wish to use. On the JupyterLab JupyterHub page (the interface you are provided after SLURM launches your job), you can select the Python3 kernel (bare-bones Python only) or the Analysis Toolbox kernel (most common scientific analysis and plotting packages). If you want to install your own kernel, you can do the following:
Ensure you replace the path and name with appropriate values for your path! In your conda environment, you need to have the SLURM-enabled Jupyterhub jobs are restricted to 12 hours. |
JupyterLab from a login node
Please, read until the end of this section, the last step is really important for things to work. Load the analysis-toolbox:
please follow the instructions in SLURM-enabled Jupyterhub jobs are restricted to 12 hours. |
JupyterLab from a login node
Please, read until the end of this section, the last step is really important for things to work. Load the analysis-toolbox:
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[mandresm@albedo1:~]$ module load analysis-toolbox
[mandresm@albedo1:~]$ jupyter notebook --no-browser --ip=0.0.0.0
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[I 15:26:36.310 NotebookApp] Jupyter Notebook 6.5.3 is running at:
[I 15:26:36.310 NotebookApp] http://albedo1:8891/?token=asdasdads
[I 15:26:36.310 NotebookApp] or http://127.0.0.1:8891/?token=asdasdasd
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[mandresm@albedo1:~]$ module load analysis-toolbox [mandresm@albedo1:~]$ jupyter notebook --no-browser --ip=0.0.0.0 ... [I 15:26:36.310 NotebookApp] JupyterUse Notebook 6.5.3 is running at: [I 15:26:36.310 NotebookApp] http://albedo1:8891/?token=asdasdads [I 15:26:36.310 NotebookApp] or http://127.0.0.1:8891/?token=asdasdasd [IControl-C to stop this server and shut down all kernels (twice to skip confirmation). [C 15:26:36.310313 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation). [C 15:26:36.313 NotebookApp] To To access the notebook, open this file in a browser: file:///albedo/home/mandresm/.local/share/jupyter/runtime/nbserver-3890270-open.html Or copy and paste one of these URLs: http://albedo1:8891/?token=asdasdaas or http://127.0.0.1:8891/?token=asdasda |
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If you have ssh automatically configured to connect to Albedo then the process will be idling at this point. If you are requested your password then enter your password and again there will be no output. You don't need to do anything here anymore, just leave this local terminal open.
Now copy the address that looks like http://gpu-001:8888/?token=123 paste it in your browser, and substitute gpu-001 with 0.0.0.0. Jupyter Lab should open now!that looks like http://gpu-001:8888/?token=123 paste it in your browser, and substitute gpu-001 with 0.0.0.0. Jupyter Lab should open now!
How to use your own conda environment in JupyterHub/Lab? → add a Jupyter Kernel?
Python Notebook
For using your own conda environment in JupyterHub/Lab and access it via a Kernel there make sure your conda environment already has ipykernel:
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conda activate <your_conda_environment>
conda install ipykernel |
Then install your environment as an ipykernel:
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source activate {environment_name}
python -m ipykernel install --user --name=<environment_name> |
Refresh Jupyter in your browser, you should now have your environment available as a kernel.
R Notebook
R is slightly different from the
Singularity
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Singularity support is still under construction! |
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