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Part of CALC@HEI, the HEI research computing infrastructure — governance in transition, currently operated by the ISC staff.

Storage and quotas

On CALC@HEI, you need to be aware of where to put your data, how much space you have, and how much time data is kept on which location.

Filesystems structure​

On each server, your user is created with the following home directory :

ls -l /home/user.name
lrwxrwxrwx  1 root              root                51 Feb  4 10:21 .apptainer -> /data/disk01/apptainer/user.name/.apptainer/
lrwxrwxrwx  1 root              root                38 Feb  4 10:21 datasets -> /data/space/datasets/user.name/
lrwxrwxrwx  1 root              root                31 Feb  4 10:21 results -> /data/shared/user.name/results/
lrwxrwxrwx  1 root              root                31 Feb  4 10:22 shared_datasets -> /data/shared/user.name/shared_datasets/
  • .apptainer is your cache directory for your containers, use apptainer cache clean every week to clean unused containers.
  • datasets is your main directory for all your work material, do NOT use directly /home/user.name/ to put data or software on it : it would uselessly fill the root partition.
  • results is located on a shared filesystem between all Slurm nodes to allow you to run jobs anywhere : as long as you write the output of your job in results, you will be able to access it whatever node the job had run on.
  • shared_datasets is located on a shared filesystem between all Slurm nodes to allow you to run jobs anywhere : when your job needs to get the same data from several nodes, use this directory. NOTE : you will have less performances for fast reads/writes since it is a network shared filesystem : if this is a concern, please consider using the faster local datasets directory above and specify your work node in your sbatch using --nodelist=xxx.

Data retention​

  1. Local datasets : Data life is short here, for now cleaning is not automated but will probably be in the future. Useful for a large volume of data to be processed on one server, and with the fastest I/O available.
  2. Shared datasets and results : Data life is short here, for now cleaning is not automated but will probably be in the future. Useful for a large volume of data to be processed on several servers, and with reasonable I/O. (with some network latency due to NFS)
  3. Filer mount : Data life is long, and backuped : this is where you can store data, results and other files for a longer time. By default you don't have a filer mount, it is the Sinf who can create you a shared directory on their main filer (filer01.hevs.ch) on their infrastructure, which is backuped and also isolated with limited access. Create this filer mount with their "Demande d'obtention de droits d'accès réseau" request

NOTE : Please note the filer storage is slow, it is not advised to run a job directly using those data.

TODO : set auto-cleaning for old data on each filesystem

Quotas​

  1. The root filesystem (/, including /home) for every researchers is 20GB for convenience. For students, this quota is lowered to 10GB to encourage proper infrastructure usage / coding with a lower threshold.
  2. On local and shared datasets, quota will be set on a case by case basis

Cleaning​

  1. Users must regularly clean the Apptainer cache using apptainer cache clean. Every week is a good starting point, we might automate cleaning if this is not respected : please don't think the container is a persistent storage for your data, it is not.
  2. Don't keep data directly on your /home/user.name/ directory : you are limited on it (20GB for researchers, 10GB for students) just for convenience : no large file should be there.
  3. When you create new apptainer containers, the .sif files can be quite big : don't store them in /home/user.name/, prefer using either datasets/ or if needed, archive them in your filer mount.