Directory of Computing Resources for Statistical Research

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Computing Resources are essential for modern statistical research and data science. The department, university, and national organizations provide several High-Performance Computing (HPC) clusters to scale up your workflows, run massive simulations, or train deep learning models.

This page provides an overview of the computing clusters available to members of the department, detailing who manages them, hardware capabilities, and where to find setup instructions.

Tip: Choosing the Right Cluster
Start local before scaling up. Use the department-managed clusters for prototyping, data preparation, and medium-scale CPU jobs. For massive parallelism or extensive GPU needs that exceed department limits, you should apply for time on external clusters like PSC Bridges-2.

Available Computing Clusters

HPC Cluster Name	Management	Has GPUs?	Setup & Documentation Articles
Leviathans	Statistics Department	No (CPU focused)	Logging into Hydras Running Docker locally and on Hydras Submitting Slurm Jobs on Hydras
Ghidorahs	Statistics Department	Yes (3 nodes)	Logging into Hydras Running Docker locally and on Hydras Submitting Slurm Jobs on Hydras
Wright Cluster	Statistics Department	Yes (24 nodes)	Wright GPU Cluster Policy Requesting GPU Resources via Slurm CUDA Environments and Virtual Envs
PSC Clusters	External (Pittsburgh Supercomputing Center)	Yes (Many nodes)	Applying for PSC Allocations Using Modules on Bridges-2 Transferring Data to PSC with Globus

Note on Accounts: Department-managed clusters usually require you to request access via the department IT staff or faculty sponsor. External resources like PSC require writing a brief research proposal and creating an ACCESS account.