Compute Support for Course

We have requested access to the shared Engineering Instructional queue on the Campus Cluster, for use for programming assignments and projects in this class. We are providing the following information as we received from Campus Cluster. We will not be able to provide any help with software setup, nor do we know how much compute is practically available (how busy is the cluster, how busy it will get if everyone in this class starts using it, etc.). Common compute clusters such as these get pretty crowded, so please plan accordingly. Please direct any questions about campus cluster usage to email addresses below.

The queue name you have been given access to is: eng-instruction. It consists of:

  1. 8 28-core nodes with 64 GB of RAM.

  2. 2 dual-socket Intel Xeon E5-2680v4 Broadwell GPU nodes with 256GB RAM & 1 NVIDIA P100 GPU (56 total GPU cores) with EDR InfiniBand interconnects

Please refer to information on how to get started. contains more comprehensive usage information including storage policies and locations

If your jobs require the use of GPU’s you can request the available GPU resources by using the feature flags as outlined here:

The College of Engineering has some shared storage available; however it is limited, so we ask that you be considerate in its use. Please contact the Technical Representatives at in order to be granted access to engineering storage for your course.

If you require large amounts of storage (>1 TB) we ask that you consult with the Technical Representatives to discuss other solutions.

Because you have been added as a user of the Campus Cluster, you should be automatically enrolled in the ICCP users mailing list, where you'll receive important updates about outages or preventative maintenance (PM) down times related to the campus cluster.

Any technical issues you may experience with the cluster should be addressed to the cluster administrators at:

For any other questions, you may reach out to the Technical Representatives at: