Perseus is a large cluster predominantly used by researchers in astrophysical sciences and physics.

Some Technical Specifications:
Perseus is a 320 node Dell Beowulf cluster. All compute nodes in this cluster are connected via an Infiniband network designed for high speed and low latency to enable excellent performance for tightly coupled MPI codes. Each node has 28-core Broadwell processors and 128 GB of RAM. For more hardware details, see the Hardware Configuration information below.


How to Access the Perseus Cluster

To use the Perseus cluster you have to enable your Princeton Linux account, request an account on Perseus, and then log in through SSH.

  1. Enabling Princeton Linux Account

    Perseus is a Linux cluster. If your Perseus account is your first Princeton OIT Linux account, then you need to enable your Linux account. If you need help, the process is described in the Knowledge Base article Unix: How do I enable/change the default Unix shell on my account? For more on Unix, you can see Introduction to Unix at Princeton. Once you have access, you should not need to register again unless your account goes unused for more than six months.
  2. Requesting Access to Perseus

    Access to the large clusters like Perseus is granted on the basis of brief faculty-sponsored proposals (see For large clusters: Submit a proposal or contribute).

    If, however, you are part of a research group with a faculty member who has contributed to or has an approved project on Perseus, that faculty member can sponsor additional users by sending a request to Any non-Princeton user must be sponsored by a Princeton faculty or staff member for a Research Computer User (RCU) account.
  3. Logging into Perseus

    Once you have been granted access to Perseus, you should be able to SSH into it using the command below.

    For more on how to SSH, see the Knowledge Base article Secure Shell (SSH): Frequently Asked Questions (FAQ).
$ ssh <YourNetID>


How to Use the Perseus Cluster

Since Perseus is a Linux system, knowing some basic Linux commands is highly recommended. For an introduction to navigating a Linux system, view the material associated with our Intro to Linux Command Line workshop. 

Using Perseus also requires some knowledge on how to properly use the file system, module system, and how to use the scheduler that handles each user's jobs. For an introduction to navigating Princeton's High Performance Computing systems, view the material associated with our Getting Started with the Research Computing Clusters workshop. Additional information specific to Perseus' file system, priority for job scheduling, etc. can be found below.

To attend a live session of either workshop, see our Trainings page for the next available workshop.
For more resources, see our Support - How to Get Help page.


Important Guidelines

Please remember that these are shared resources for all users.

The head node, perseus, should be used for interactive work only, such as compiling programs, and submitting jobs as described below. No jobs should be run on the head node, other than brief tests that last no more than a few minutes. Where practical, we ask that you entirely fill the nodes so that CPU core fragmentation is minimized. For this cluster, perseus, that means multiples of 28 cores.


Wording of Acknowledgement of Support and/or Use of Research Computing Resources

"The author(s) are pleased to acknowledge that the work reported on in this paper was substantially performed using the Princeton Research Computing resources at Princeton University which is consortium of groups led by the Princeton Institute for Computational Science and Engineering (PICSciE) and Office of Information Technology's Research Computing."

"The simulations presented in this article were performed on computational resources managed and supported by Princeton Research Computing, a consortium of groups including the Princeton Institute for Computational Science and Engineering (PICSciE) and the Office of Information Technology's High Performance Computing Center and Visualization Laboratory at Princeton University."