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Research computing and data tools

The shared compute, storage, and software for coursework and research that a laptop cannot handle.

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When your laptop is not enough

Your issued laptop runs everyday coursework. Simulation, large datasets, machine-learning training, rendering, and genomics-scale analysis need shared resources: a high-performance computing cluster, large project storage, and GPU nodes. Access is free for coursework and research; you request an account and, for the cluster, take a short onboarding.

The cluster

The research computing cluster runs batch jobs — you submit a job to a queue and it runs when resources free up, rather than tying up an interactive session. It suits long simulations, parameter sweeps, and training runs. Staff help you get a workflow onto it; the first job is the hard part, and there is a consulting appointment for exactly that.

Storage that is actually backed up

Research and course project storage is on managed, backed-up systems — not your laptop drive, not a personal cloud account. Shared drives let a team and a faculty mentor work from the same files. Know your quota and what the retention and backup policy is; "it was on my laptop" is not a recovery plan.

Software

Beyond what ships on your laptop, the university licenses specialized packages — statistical, CAD and simulation, GIS, qualitative analysis, survey tools — available in labs, via remote desktop, or as a checkout license. The software licensing page lists what is available to students and how to get it.

Data management plans

Grant-funded projects usually require a data management plan: what data you will collect, how it is stored and secured, who can access it, how it is de-identified, and what happens to it after the project. The library and research computing help write one, and getting it right early prevents a compliance problem later.

Getting help

Research computing consultations cover getting onto the cluster, choosing tools, and workflow design. The library covers data management, finding datasets, and reproducibility. Your faculty mentor covers the domain methods. Start with a consultation before you spend a week fighting a setup alone.

Fictional information

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