Commit f63b7a91 authored by Christian Tischer's avatar Christian Tischer

Update README.md

parent 5a263e90
......@@ -61,21 +61,53 @@ TODO
### Launching an interactive jupyter notebook on a GPU cluster node
1. Make sure you are in the EMBL intranet
2. Login to the cluster with `ssh` from your terminal.
- Mac and Linux: a terminal and ssh is included.
- Windows: please install [git for windows](https://git-scm.com/download/win) which includes a ssh command client (choose *Run Git and included Unix tools form Windows Command Prompt* on installation).
3. Open a terminal
4. Log into the EMBL cluster:
#### Prerequisites
- Make sure you are in the EMBL intranet
- You need a terminal with the `ssh` command. On Mac and Linux this is included, on Windows please install [git for windows](https://git-scm.com/download/win) which includes a ssh command client (choose *Run Git and included Unix tools form Windows Command Prompt* on installation).
- Your data and jupyter notebooks must be on a group-share, e.g. (Linux: `/g/kreshuk`; Mac: `/Volumes/kreshuk`; Windows: `\\kreshuk\kreshuk` )
#### Log into cluster and start an interactive jupyter notebook with stardist environment
- Open a terminal window on your computer
- Log into the EMBL cluster by typing:
- `ssh EMBLUSERNAME@login.cluster.embl.de`
- when asked enter you EMBLK password.
4. Ask for an interactive job on a GPU node:
- `srun -t 60:00 -N1 -n4 --mem 32G -p gpu -C "gpu=2080Ti|gpu=1080Ti" --gres=gpu:1 -W 0 --pty -E $SHELL
IP=$(ip a s $(ip r l | grep default | awk '{ print $5 }') | grep -Po 'inet \K[\d.]+')
source /g/almf/software/miniconda3/run_conda.sh
conda activate stardist-gpu
cd /g/cba/exchange/stardist/examples/2D
jupyter notebook --ip $IP 2_training.ipynb
- Enter you EMBL password.
- Ask for an interactive job on a GPU node:
- `srun -t 60:00 -N1 -n4 --mem 32G -p gpu -C "gpu=2080Ti|gpu=1080Ti" --gres=gpu:1 -W 0 --pty -E $SHELL`
- The time and memory needs to be adjusted (HOW?)
- If the cluster is busy, it may take some time until you get the job...
- Store the IP address of the cluster node into a variable:
- `IP=$(hostname -i)`
- Activate conda:
- `source /g/almf/software/miniconda3/run_conda.sh`
- Activate the stardist environment
- conda activate stardist-gpu
- Go to a folder containing your notebooks
- cd /g/FOLDER/WITH/NOTEBOOKS
- Run jupyter notebook with the IP of the cluster node that you are currently on
- `jupyter notebook --ip $IP`
The last command will result in an output like this:
```
[I 08:51:35.097 NotebookApp] Serving notebooks from local directory: /home/tischer
[I 08:51:35.097 NotebookApp] The Jupyter Notebook is running at:
[I 08:51:35.097 NotebookApp] http://10.11.12.249:8888/?token=235e5613589eb1d80435099afe395dad536bde40e3fde755
[I 08:51:35.097 NotebookApp] or http://127.0.0.1:8888/?token=235e5613589eb1d80435099afe395dad536bde40e3fde755
[I 08:51:35.097 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[W 08:51:35.133 NotebookApp] No web browser found: could not locate runnable browser.
[C 08:51:35.133 NotebookApp]
To access the notebook, open this file in a browser:
file:///home/tischer/.local/share/jupyter/runtime/nbserver-51995-open.html
Or copy and paste one of these URLs:
http://10.11.12.249:8888/?token=235e5613589eb1d80435099afe395dad536bde40e3fde755
or http://127.0.0.1:8888/?token=235e5613589eb1d80435099afe395dad536bde40e3fde755
```
You need to copy and paste the second last line, here `http://10.11.12.249:8888/?token=235e5613589eb1d80435099afe395dad536bde40e3fde755` into a webbrowser on your computer.
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