Getting Started

1. Before using the hpc-client, you need to decide how it will run on your cluster.
   
   Choose an integration method and keep it in mind for later. This sets how frequently the hpc-client will look for, pull, and queue hpc jobs to your HPC from your Flywheel site.

2. It is strongly recommended that you make a private Git repo (GitHub, GitLab, etc.) to track your changes.
   
   This will make the hpc-client much easier to manage.

3. Perform the initial cluster setup. If you are unfamiliar with singularity, it is recommended that you read--at a minimum--SingularityCE's introduction and quick start guides.

4. Create an authorization token so Singularity and Flywheel can work with each other.

5. If your queue type is not in the table described in the HPC Types, or is sufficiently different, review the guide for adding a queue type.

6. Collaborate with Flywheel staff to install the Flywheel engine in your HPC repo. They will also configure the hold engine on your Flywheel site to ensure that other engines do not pick up gear jobs that are tagged with "hpc" (or your desired tag).

7. Complete the integration method you chose in step one.
   
   Confirm the hpc-client is running regularly by monitoring <configuration directory>/logs/cast.log and the Flywheel user interface.

8. Test and run your first HPC job tests in collaboration with Flywheel. It is recommended that you test with "Stress Test" (stress-test), or, if you're testing GPU capabilities, fw-nvidia-cuda-test. Both gears are available from Flywheel's Gear Exchange.
   
   Note: Please use the beta version of the Flywheel CLI fw-beta to install them.

9. Enjoy!