HCC Documentation

The Holland Computing Center supports a diverse collection of research computing hardware.  Anyone in the University of Nebraska system is welcome to apply for an account on HCC machines.

Access to these resources is by default shared with the rest of the user community via various job schedulers. These policies may be found on the pages for the various resources. Alternatively, a user may buy into an existing resource, acquiring ‘priority access’. Finally, several machines are available via Condor for opportunistic use. This will allow users almost immediate access, but the job is subject to preemption.

Getting Started

To begin using HCC resources:

  1. Set up your HCC account
  2. Connect to HCC Clusters
  3. Transfer data to HCC Clusters
  4. Check software availability
  5. Submit jobs on HCC Clusters

Which Cluster to Use?

Crane: Crane is the newest and most powerful HCC resource . If you are new to using HCC resources, Crane is the recommended cluster to use initially.  Limitations: Crane has only 2 CPU/16 cores and 64GB RAM per node. CraneOPA has 2 CPU/36 cores with a maximum of 512GB RAM per node.

Rhino: Rhino is intended for large memory (RAM) computing needs. Rhino has 4 AMD Interlagos CPUs (64 cores) per node, with either 192GB or 256GB RAM per node in the default partition. For extremely large RAM needs, there is also a ‘highmem’ partition with 2 x 512GB and 2 x 1TB nodes.

Important Notes

  • The Crane and Rhino clusters are separate. But, they are similar enough that submission scripts on whichever one will work on another, and vice versa (excluding GPU resources and some combinations of RAM/core requests).  
  • The worker nodes cannot write to the /home directories. You must use your /work directory for processing in your job. You may access your work directory by using the command:
    $ cd $WORK


  • Crane - HCC’s newest machine, Crane has 7232 Intel Xeon cores in 452 nodes with 64GB RAM per node.
  • Rhino - HCC’s AMD-based cluster, intended for large RAM computing needs.
  • Red - This cluster is the resource for UNL’s USCMS Tier-2 site.
  • Anvil - HCC’s cloud computing cluster based on Openstack
  • Glidein - A gateway to running jobs on the OSG, a collection of computing resources across the US.

Resource Capabilities

Cluster Overview Processors RAM* Connection Storage
Crane 572 node LINUX cluster 452 Intel Xeon E5-2670 2.60GHz 2 CPU/16 cores per node

120 Intel Xeon E5-2697 v4 2.3GHz, 2 CPU/36 cores per node

452 nodes @ 62.5GB

79 nodes @ 250GB

37 nodes @ 500GB

4 nodes @ 1500GB
QDR Infiniband

EDR Omni-Path Architecture
~1.8 TB local scratch per node

~4 TB local scratch per node

~1452 TB shared Lustre storage
Rhino 110 node LINUX cluster 110 AMD Interlagos CPUs (6272 / 6376), 4 CPU/64 cores per node 106 nodes @ 187.5GB/250GB

2 nodes @ 500GB

2 nodes @ 994GB
QDR Infiniband ~1.5TB local scratch per node

~360TB shared BeeGFS storage
Red 344 node LINUX cluster Various Xeon and Opteron processors 7,280 cores maximum, actual number of job slots depends on RAM usage 1.5-4GB RAM per job slot 1Gb, 10Gb, and 40Gb Ethernet ~10.8PB of raw storage space
Anvil 76 Compute nodes (Partially used for cloud, the rest used for general computing), 12 Storage nodes, 2 Network nodes Openstack cloud 76 Intel Xeon E5-2650 v3 2.30GHz 2 CPU/20 cores per node 76 nodes @ 256GB 10Gb Ethernet 528 TB Ceph shared storage (349TB available now)

* Due to overhead for the operating system and hardware, the maximum available memory is lower than the total installed memory. Requesting more may result in your job not running, being delayed, or running on a smaller number of nodes.