HPC Classroom Usage

Summary

Clipper is now available for classroom use, primarily for teaching rather than research. This allows students to gain hands-on experience using an HPC environment.

Allocated Resources

Students have access to a dedicated class partition with the following total resources:

• 80 CPUs
• 2 GPUs
• 1.5 TB of memory

Each student may submit jobs with a maximum of:

• 8 CPUs
• 1 GPU
• 64 GB of memory

If a student submits a single job that requests more than the specified limits, it will be automatically rejected by Slurm.

Jobs from the same user are managed such that their combined resource usage cannot exceed the per-job limits. If multiple jobs collectively exceed these limits, they will queue and execute sequentially as resources free up.

When all available class partition resources are being used, any additional job submissions will be queued until sufficient resources become available. For example, if both GPUs are currently in use, newly submitted jobs requesting a GPU will queue until the previous submissions finish.

Accessing the HPC Cluster

If you are connected to the student wifi you will need to be on the VPN. 

To access the cluster for classwork, use the provided login link. After signing in, you will see a tile on the main screen that looks like this:

Click on the tile to open a new screen, where you can log in to the cluster using SSH.

Submitting a Job

Refer to this knowledge base article Submitting a job for instructions on submitting a basic job. Be sure to change the partition setting to class instead of short.

Students will be unable to submit to other partitions available on Clipper. If a student attempts to submit to a partition other than class, they will receive the following error message from Slurm:

File Management

To upload or download files from the cluster, click on the file management tile on the main screen:

This will open a new window where you can use the top menu bar to upload, download, or delete files as needed.