Get Started

Princeton Research Computing provides powerful high performance computing systems for the Princeton community to conduct and enable their research. It provides several different systems, with different clusters of computers designated for specific types of work.

Before you begin to use our High Performance Computing clusters, you must first complete the following three steps:

  1. Get An Account

    1. Obtain a Princeton University netID
      If you are a non-Princeton user, a Princeton faculty or staff member must fill out this RCU form to create an account for you.
    2. Enable your Unix shell access (if using Nobel)
      Instructions can be found in Unix: How do I enable/change the default Unix shell on my account?
    3. Identify which cluster(s) to use
      Explore our Research Computing Systems Overview page to help you choose.
    4. Request access to your desired cluster(s)
      Under the Systems page for selected cluster (e.g. Adroit, or Tiger), see the “How to Access" section. Additionally, you can try the Get an Account page for an overview and guidelines on proposals.
  2. Learn a Few Linux Commands

    The clusters are Linux machines, and it can be difficult to navigate the system unless you are familiar with at least a few basic commands.

    While we strongly recommend taking our Intro to Linux Command Line workshop before using the clusters (see Workshop & Live Training page for upcoming sessions), you are welcome to use the self-guided resources on our Learning Resources: the Linux Command Line page.

    At a minimum you should know how to use the following commands in Linux:
    pwd, ls, mkdir, cd, mv, and scp or rysnc
  3. Review the Guide to Getting Started with the Princeton Clusters

    Read through our guide for using the clusters and submit the example jobs in each section. This guide is the foundation of our Getting Started with the Princeton Clusters workshop (see Workshop & Live Training page for upcoming sessions). It covers many of the issues we see new users struggle with, along with important guidelines for using the Princeton clusters appropriately.


Additional Resources

If you encounter unfamiliar terminology, refer to Research Computing's Glossary page.

To learn more about research computing concepts and tools, see our Tutorials and Workshop & Live Training pages. 

If you need help with using the clusters, programming, or visualization, view our Support tab. The How To Get Help page is a great starting point.