Preparation

1. Login to MeluXina machine

You can find instructions on how to access the MeluXina machine in MeluXina documentation.

Details for:

• Windows users, and
• Linux/Mac users.

2. Use your username to connect to MeluXina

For exmaple the below example shows the user of u100490

ssh u100490@login.lxp.lu -p 8822

3. Ensure that you can access your home and project directories

3.1 Check your home directory

Once you have logged in, you will be in a default home directory. Check with the following command.

[u100490@login02 ~]$ pwd
/home/users/u100490

3.2 Check the bootcamp project directory

Change to the project directory for Nvidia Bootcamp activities.

[u100490@login02 ~]$ cd /project/home/p200117
[u100490@login02 p200117]$ pwd
/project/home/p200117

4. Create a personal working folder in the bootcamp project directory

Please create your own working folder under the project directory. For example, here it is the process for user with user name u100490.

[u100490@login02 p200117]$ mkdir "${USER}"

4.1 Copy the files required by the practicals in your working directory

Now copy climate.simg and climate.sh from project directory to your user directory. For example, here is the process for user u100490.

[u100490@login02 p200117]$ cp /project/home/p200117/climate.simg /project/home/p200117/u100490
[u100490@login02 p200117]$ cp /project/home/p200117/climate.sh /project/home/p200117/u100490

4.2 Copy the files required by the practicals in your home directory

Copy cfd.simg and cfd.sh from project directory to your user directory. For example, here is the process for user u100490.

[u100490@login02 p200117]$ cp /project/home/p200117/cfd.simg /project/home/p200117/u100490
[u100490@login02 p200117]$ cp /project/home/p200117/cfd.sh /project/home/p200117/u100490

4.3 Check that all required file are available

Go to your home directory and check if all the necessary files are there (.simg and .sh). For example, here is the process for user u100490.

[u100490@login02 p200117]$ cd u100490
[u100490@login02 u100490]$ pwd
[u100490@login02 u100490]$ /project/home/p200117/u100490
[u100490@login02 u100490]$ ls -lthr
total 15G
-rw-r-x---. 1 u100490 p200117  736 Feb  8 18:59 climate.sh
-rwxr-x---. 1 u100490 p200117 7.2G Feb  8 19:19 climate.simg
-rwxr-x---. 1 u100490 p200117 6.9G Feb  8 19:21 cfd.simg
-rw-r-x---. 1 u100490 p200117  723 Feb  8 19:21 cfd.sh

5. For the dry run (9^th February from 11:30-12:30)

Follow the in instruction below step-by-step.

• Launch the service:

  [u100490@login02 u100490]$ salloc -A p200117 --res gpudev -q dev -N 1 -t 01:00:0
  [u100490@mel2123 u100490]$ mkdir -p $PROJECT/$USER/workspace-climate
  [u100490@mel2123 u100490]$ module load Singularity-CE/3.10.2-GCCcore-11.3.0
  
  [u100490@mel2123 u100490]$ singularity run --bind $PROJECT/$USER $PROJECT/$USER/climate.simg cp -rT /workspace $PROJECT/$USER/workspace-climate
  INFO:    Converting SIF file to temporary sandbox...
  INFO:    Cleaning up image...
  [u100490@mel2123 u100490]$ singularity run --nv --bind $PROJECT/$USER $PROJECT/$USER/climate.simg jupyter lab --notebook-dir=$PROJECT/$USER/workspace-climate/python/jupyter_notebook --port=8888 --ip=0.0.0.0 --no-browser --NotebookApp.token=""
  INFO:    Converting SIF file to temporary sandbox...
  WARNING: underlay of /usr/bin/nvidia-smi required more than 50 (452) bind mounts
  [W 10:10:32.723 LabApp] All authentication is disabled.  Anyone who can connect to this server will be able to run code.
  [I 10:10:33.043 LabApp] jupyter_tensorboard extension loaded.
  [I 10:10:33.047 LabApp] JupyterLab extension loaded from /usr/local/lib/python3.8/dist-packages/jupyterlab
  [I 10:10:33.047 LabApp] JupyterLab application directory is /usr/local/share/jupyter/lab
  [I 10:10:33.048 LabApp] [Jupytext Server Extension] NotebookApp.contents_manager_class is (a subclass of) jupytext.TextFileContentsManager already - OK
  [I 10:10:33.048 LabApp] Serving notebooks from local directory: /mnt/tier2/project/p200117/u100490/workspace-climate/python/jupyter_notebook
  [I 10:10:33.048 LabApp] Jupyter Notebook 6.2.0 is running at:
  [I 10:10:33.048 LabApp] http://hostname:8888/
  [I 10:10:33.049 LabApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
  

• Open a new terminal on your local computer, and again login to MeluXina to access the service.

• Use the squeue command to determine the node running the service. Nodes are listed in the NODELIST field.

• Connect to the service. For instance, if the service is running on node mel2123 then use the command:

  ssh -L8080:mel2123:8888 u100490@login.lxp.lu -p 8822
  

• Keep those terminals open/alive (please do not close them).

• Copy and paste localhost:8080 to your browser either to Chrome or Firefox.

  http://localhost:8080
  

You should now have access to the service.

6. For the afternoon session (9^th and 10^th February)

If have missed the dry run session, then please go through the steps from 1-4.

• Now it is time to edit your batch script (climate.sh) before launching your Jupyter notebook. Please follow the following steps.

  [u100490@login02 u100490]$ emacs(emacs -nw)/vim climate.sh
  #!/bin/bash -l
  #SBATCH --partition=gpu
  #SBATCH --ntasks=1
  #SBATCH --nodes=1
  ############  day one ##########
  #######SBATCH --time=02:00:00         ## use this option for day one
  #######SBATCH --res ai_bootcamp_day1   ## use this option for day one
  ################################
  
  ############  day two ##########
  #SBATCH --time=03:30:00         ## use this option for day two
  #SBATCH --res ai_bootcamp_day2  ## use this option for day two
  ################################
  #SBATCH -A p200117
  #SBATCH --qos default
  
  mkdir -p $PROJECT/$USER/workspace-climate
  module load Singularity-CE/3.10.2-GCCcore-11.3.0
  
  singularity run --bind $PROJECT/$USER $PROJECT/$USER/climate.simg cp -rT /workspace $PROJECT/$USER/workspace-climate
  singularity run --nv --bind $PROJECT/$USER $PROJECT/$USER/climate.simg jupyter lab --notebook-dir=$PROJECT/$USER/workspace-climate/python/jupyter_notebook --port=8888 --ip=0.0.0.0 --no-browser --NotebookApp.token=""
  

• Once you have modified your climate.sh, please launch your batch script as below.

  [u100490@login03 u100490]$ sbatch climate.sh
  Submitted batch job 276009
  [u100490@login03 u100490]$ squeue
  JOBID PARTITION     NAME     USER    ACCOUNT    STATE       TIME   TIME_LIMIT  NODES NODELIST(REASON)
  276009       gpu climate.  u100490    p200117  RUNNING       0:16        20:00      1 mel2077
  

• You have now initiated your singularity container which will help you to open the Jupyter nootebook.

  [u100490@login03 u100490]$ ls -lthr
  total 7.2G
  -rwxr-x---. 1 u100490 p200117 7.2G Feb  3 14:53 climate.simg
  -rw-r-----. 1 u100490 p200117  613 Feb  3 17:06 climate.sh
  -rw-r-x---. 1 u100490 p200117  724 Feb  8 19:41 cfd.sh
  -rwxr-x---. 1 u100490 p200117 6.9G Feb  8 19:42 cfd.simg
  -rw-r--r--. 1 u100490 p200117 1.1K Feb  3 17:58 slurm-276009.out
  

• You can also check if everything is OK by executing the command below.

  [u100490@login03 u100490]$ head -30 slurm-276009.out
  INFO:    Converting SIF file to temporary sandbox...
  INFO:    Cleaning up image...
  INFO:    Converting SIF file to temporary sandbox...
  WARNING: underlay of /usr/bin/nvidia-smi required more than 50 (452) bind mounts
  [W 17:58:37.489 LabApp] All authentication is disabled.  Anyone who can connect to this server will be able to run code.
  [I 17:58:37.807 LabApp] jupyter_tensorboard extension loaded.
  [I 17:58:37.811 LabApp] JupyterLab extension loaded from /usr/local/lib/python3.8/dist-packages/jupyterlab
  [I 17:58:37.811 LabApp] JupyterLab application directory is /usr/local/share/jupyter/lab
  [I 17:58:37.813 LabApp] [Jupytext Server Extension] NotebookApp.contents_manager_class is (a subclass of) jupytext.TextFileContentsManager already - OK
  [I 17:58:37.813 LabApp] Serving notebooks from local directory: /mnt/tier2/project/p200117/u100490/workspace-climate/python/jupyter_notebook
  [I 17:58:37.813 LabApp] Jupyter Notebook 6.2.0 is running at:
  [I 17:58:37.813 LabApp] http://hostname:8888/
  [I 17:58:37.813 LabApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
  

  If everything went OK your output should be similar.

• Open a new terminal on your local computer, and again login to MeluXina to access the service.

• Use the squeue command to determine the node running the service. Nodes are listed in the NODELIST field.

• Connect to the service. For instance, if the service is running on node mel2077 then use the command:

  ssh -L8080:mel2077:8888 u100490@login.lxp.lu -p 8822
  

• Keep those terminals open/alive (please do not close them).

• Copy and paste localhost:8080 to your browser either to Chrome or Firefox.

  http://localhost:8080
  

20 May 2026 10:47:1120 May 2026 10:47:11