/tag/apptainer
Apptainer and UVA HPC
Introduction Apptainer is a continuation of the Singularity project (see here). On December 18, 2023 we migrated from Singularity to Apptainer.
Containers created by Singularity and Apptainer are mutually compatible as of this writing, although divergence is to be expected.
One advantage of Apptainer is that users can now build container images natively on the UVA HPC system.
Apptainer and UVA HPC (after 12/18/2023) Apptainer is available as a module. The RC staff has also curated a library of pre-prepared Apptainer container images for popular applications as part of the shared software stack. Descriptions for these shared containers can be found via the module avail and module spider commands.
Custom Jupyter Kernels
You can create custom kernels from a conda environment or an Apptainer container.
In both cases you’ll need to install the ipykernel package.
Jupyter kernel based on a conda environment To create a custom kernel of the conda environment myenv that uses Python 3.7:
module load miniforge conda create -n myenv python=3.7 ipykernel <other_packages> source activate myenv python -m ipykernel install –user –name myenv –display-name "My Env" Note:
You can customize the display name for your kernel. It is shown when you hover over a tile in JupyterLab. If you do not specify a display name, the default Python [conda env:<ENV_NAME>] will be shown.
