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Campus cluster, Google Cloud, national allocations and high-throughput computing: what each is for, who can use it, and how to start.

Most research computing at UCR runs on the HPCC cluster. Cloud and national resources fill gaps: AI services, cloud-native tools, systems we do not have on campus, or more capacity than campus can offer. If you are not sure where to start, ask us. A short description of your work is enough.

Choose by what you are doing

If you need to Start with Also consider
Run batch simulations, pipelines or MPI jobs HPCC cluster NSF ACCESS for larger runs
Train or run models on GPUs HPCC cluster NAIRR Pilot, NSF ACCESS, Nautilus
Use generative AI models in your research Ursa Major (Tier 1 AI access) Cloud and AI
Use exotic hardware the HPCC does not have (such as TPUs or Arm) Ursa Major (Tier 1 exotic hardware, by consultation) NSF ACCESS
Run thousands of small independent jobs HPCC cluster OSG / OSPool
Run containers or JupyterHub at scale NRP Nautilus Ursa Major
Have your own cloud account on a grant Cloud accounts Ursa Major
Work with regulated data Secure research enclave Security and data
Get help running a lab-owned cluster RCSAS None

Campus

National and shared

National programs award time by application rather than by recharge. They have their own policies on eligibility and data.

A note on capacity

All of these are shared or allocated resources. Capacity, queue times, quotas and eligibility are set by each provider and change with demand. Choosing a service is not a reservation of capacity on it.

Owner: Research Computing Reviewed: 4 Oct 2026