Reference · RCC ClusterDocs
RCC day-to-day reference
The course teaches the RCC workflow in sequence. These reference pages collect commands and practical details that you may need later without repeating an entire class.
Use a class when learning a workflow for the first time. Use its reference companion when you already understand the safety boundary and need a command, decision table, or diagnostic sequence.
Find the right guide
| Task | Reference |
|---|---|
| Understand individual accounts, primary groups, external collaborators, and project membership | Users, groups, and projects |
| Import optional shell, prompt, Conda, or Shiny account defaults | Account starter setups |
| Create an SSH key, configure a client, connect with VS Code, or mount a small remote folder | Account access, SSH, and VS Code |
| Choose durable or temporary storage and transfer project data | Storage and transfer |
| Share data within a project, across RCC groups, or outside RCC | How to share data safely |
| Submit, inspect, connect to, and cancel jobs | Slurm commands |
| Understand shared, owner, borrowed, and interactive compute capacity | How shared compute works |
| Use Conda, Snakemake, or Apptainer | Software workflows |
| Diagnose permissions, file limits, GPU processes, searches, and failed jobs | Troubleshooting |
| Discover available CPUs, memory, GPUs, partitions, and supported software | Resources and discovery |
| Plan machine learning, AI, validation, inference, or distributed data processing | AI and data science |
Important boundary
Examples use public aliases and replaceable values. The site deliberately does not publish physical host inventories, internal addresses, firewall rules, or administrator commands. Use the current institutional RCC instructions and support channel for operational values.