Hoffman2:Singularity: Difference between revisions
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* Note: Singularity's newer versions are changed to a new name "Apptainer". It's recommended to use Apptainer instead of Singularity. | * Note: Singularity's newer versions are changed to a new name "Apptainer". It's recommended to use Apptainer instead of Singularity. | ||
Just need to replace all the "singularity" with "apptainer" in the following command and it should work the same way. | |||
===How to use Singularity=== | ===How to use Singularity=== | ||
Revision as of 18:19, 8 April 2026
Singularity
Singularity is a type of container technology. It is provided in Hoffman2 currently.
* Note: Singularity's newer versions are changed to a new name "Apptainer". It's recommended to use Apptainer instead of Singularity. Just need to replace all the "singularity" with "apptainer" in the following command and it should work the same way.
How to use Singularity
The example code here is from IDRE team's | gitlab. Please check it up for more information.
Interactive mode
In a CentOs 7 Node, load Singularity module as
module load singularity singularity shell --userns $H2_CONTAINER_LOC/tensorflow-2.4.1-gpu-jupyter.sif
Then run your command inside of the container
python3 tf-example.py > tf-example-batch.out
Batch mode
Add the following line into your batch job script
module load singularity/3.7.1
Use "singularity exec" to run command in Singularity container
Example
singularity exec --userns $H2_CONTAINER_LOC/tensorflow-2.4.1-gpu-jupyter.sif python3 tf-example.py > tf-example-batch.out
Convert Docker image for Singularity
Docker image can be converted for Singularity
export SINGULARITY_CACHEDIR=$SCRATCH/singularity_cache singularity pull tensorflow-1.15.5-gpu-jupyter.sif docker://tensorflow/tensorflow:1.15.5-gpu-jupyter