Alpine: High Performance Computing (HPC)

Description:

Alpine High‑Performance Computing (HPC) provides CU Anschutz researchers with access to Alpine, a large, centrally funded supercomputing cluster hosted by CU Boulder Research Computing. Alpine supports large scale data processing and computational analysis with more than 18,000 CPU cores, GPU resources, and high‑memory nodes. This environment is available at no cost to CU Anschutz faculty, researchers, staff and students and is designed to accelerate research productivity and multidisciplinary discovery. 

Important: Alpine is not approved for HIPAA regulated or highly confidential data.


Who can use it:

  • Researchers
     

Cost:

No cost for use of Alpine resources, except for optional paid PetaLibrary storage through CU Boulder Research Computing.

 

How to proceed: 

  • Click the Request HPC Access button on the right to begin the onboarding process for Alpine, including completion of the required End User Agreement and activation steps. You will be redirected to fill out an access form.  When your access is approved, you will receive confirmation and instructions from CU Boulder Research Computing. 
     
  • Click the HPC Support button on the right if you need assistance with accessing Alpine, troubleshooting account or environment issues, understanding available compute resources, or identifying the right training and documentation.  This button will open an email to rc-help@colorado.edu, and their team will assist you.
     

Additional resources:

  • CU Boulder Research Computing Alpine Documentation
  • Research Data Security and Classification Guidelines (for data eligibility on Alpine)
 
Request HPC Access Request HPC Support

Service Offerings (2)

Request HPC Access
Click here to begin the onboarding process for Alpine, including completion of the required End User Agreement and activation steps.
Request HPC Support
Click here to open an email to the HPC support team if you need assistance with accessing Alpine, troubleshooting account or environment issues, understanding available compute resources, or identifying the right training and documentation.