HPC Computing, Research Computing & Other Research Computing Options

Research computing most generally refers to the practice of combining computers in a way that delivers much higher performance than one could get out of a single desktop computer or workstation in order to solve large problems. The University of Denver hosts an High Performance Computing (HPC) cluster available to faculty members, researchers, and students engaged in research activities.  Our goal is to assist researchers by providing access to computational resources necessary to construct, analyze and interpret complex data.

Current options for researchers at DU:

  • on-campus and NSF funded high performance computing (HPC) clusters
  • on-campus and commercial computational cloud resources
  • computational workstations
  • computational servers

Please refer to Resources section at the bottom of this page for more information on how to use HPC.

HPC Computing Resources

DU High-Performance Computing (HPC)

Operating System Red Hat Enterprise Linux 7.7
Nodes 44 compute nodes
Hosted IT Data Center
Maximum theoretical performance 30.5408 TFLOPS
Maximum storage
  • 50 TB lab storage
    • Currently no research lab quotas
  • 11TB individual user storage
    • 100 GB user quotas
GPU 1 GPU node, 2 Nvidia Tesla P100 GPU cards
Job queue system Grid Engine
Availability Current HPC users

Research Data Analysis Cluster (RDAC)

Operating System Red Hat Enterprise Linux 7.6, managed by Bright Cluster Manager 8.2
Nodes 14 compute nodes
Hosted Hosted in DEN1 remote data center
Maximum theoretical performance 60 TFLOPS
Maximum storage
  • 178 TB lab storage
    • Assign research lab quotas as needed
  • 50 TB individual user storage
    • 250GB user quotas
GPU 2 GPU nodes, 1 Nvidia Tesla V100 per node
Job queue system SLURM 18
Availability New and current HPC users

 

Research Computing and Service Management

As computational computing can be challenging to utilize and understand, IT@DU can provide tutorials to assist researchers to accomplish their computational goals. Tutorials available include:

  • introduction to using the Linux command line
  • how to use a HPC job queue system for running analyses
  • how to use an environment module system to run computational analyses
  • how to gain access to cloud computational computing resources
  • how to gain access to NSF-funded high performance clusters.
  • IT@DU manages computational computing resources as well as additional Research Technology services. Currently, the high performance computing cluster, various researcher-owned computational workstations (per agreements with researchers), and computational cloud services are managed. Management includes service/system maintenance, access granting and control, installing/building/compiling new computational software, troubleshooting any issues, and assisting with using services.
  • In addition to computational computing services, IT@DU also manages additional Research Technology services, as the need arises or on behalf of a researcher. Current systems managed are: REDCap, Sona Systems (used exclusively by the Department of Psychology), and a proof-of-concept instance of elabFTW (electronic scientific notebook).