Purpose

The purpose of this repository is to gather information useful to someone who is new to HPC systems running a container technology. In order to support a rapidly changing computational environment we have adopted the use of singularity containers.

In this repository you will find guides that introduce our chosen container solution Singularity and our chosen job scheduler Slurm Workload Manager. By using both of these tools we allow students and researchers to develop a container environment locally (on their laptop or PC) and enable them to move the container and job script around to different compute resources without needing to re-install software or libraries.

In order to support the above workflow we have divided this repository into two parts, one for singularity and one for slurm. In each you will find a README.md that contains a quick start to the technology as well as example scripts that will be usefull for you to base your work off of.

Using containers

To get the most of these materials you need to have a basic understanding of linux and knowledge of the computational problem you are trying to solve. To better outline how to use this guide I will first layout the expected workflow a user should use:

1. Install Singularity on your local system
   • linux install instructions
   • Windows users can install Singularity in WSL v2
   • Mac users will need a local linux install via Vagrant or a Virtual Machine
2. Build and test your first Singularity container (see 1_singularity/README.md)

Running on the HPC

1. If you want to use the HPC resources on campus you need to create a slurm job submission script .sbatch for the desired compute resource (see 2_slurm/README.md)
2. Upload your .sif container, your .sbatch file, and your code/data to the compute resrouce you are using
3. Submit your job using sbatch <my-file.sbatch>