Using Containers¶
Researchers can use Docker or Singularity containers within the cluster. This is a great way to run difficult-to-compile applications or to share workflows among colleagues.
See also: Singularity
Running an interactive container¶
User can run within a container interactively, this is great for testing code before running a job. Here is an example of running within a docker container lolcow:
srun --pty -c 4 --mem=64G bash
module purge
module load GCC/10.2.0 OpenMPI/4.0.5 Singularity/3.10.2
singularity pull docker://godlovedc/lolcow
singularity shell lolcow.sif
Once you have typed the singularity shell command you will be within the container and can type the commands available from within the container such as the lolcow utility fortune | cowsay | lolcat
Running a container in batch¶
Running a batch job with containers is similar to running a regular job, but will ultimately depend on how the container was created, so your mileage may vary. Here is an example batch submit script that will run the autometa software that was created in a docker image, lets name the submit file runContainer.sh:
#SBATCH -J autometa-job
#SBATCH -c 4
#SBATCH --mem=64G
#SBATCH --mailtype=BEGIN,END,FAIL
#SBATCH --mail-user=myemail@email.net
#SBATCH --time=12:00:00
module load Singularity/3.10.2
singularity pull docker://jasonkwan/autometa:latest
singularity exec autometa_latest.sif calculate_read_coverage.py somedata.dat
Now to run the file you can:
Note that singularity shell is primarily for interactive use and singularity exec (or possibly singularity run) are for executing the applications that were built within the container directly. It is important to know how the container was created to make effective use of the software.