High Performance Computing


The College of Engineering will be deploying a new High Performance Computing Cluster (HPC2) in Fall 2020.  

If your research group is not part of the HPC2 Cluster and you would like to join, please send an email to coeitss-support@ucdavis.edu so that we can discuss access.

HPC 2 Participating Research Groups

Chemical Engineering
Ambarish Kulkarni
Roland Faller

Civil and Environmental Engineering
Geoff Schladow
Jonathan Herman

Electrical and Computer Engineering
John Owens

Mechanical and Aerospace Engineering
JP Delplanque
Seongkyu Lee

Materials Science and Engineering
Jeremy Mason

Center for Neuroscience
Charan Ranganath
Randall O’Reilly



The College of Engineering High Performance Computing Cluster (HPC1) contains 60 compute nodes and central storage, all connected on Infiniband networking. Each node contains 64GB of RAM shared by two CPU sockets, each with an 8-core CPU running at 2.4GHz. Central storage is managed by redundant storage servers, with 200 TB of usable storage evenly allocated to researchers. The storage is for temporary computation and is not backed up or duplicated in any way except that it is configured as RAID6 so can withstand up-to-two simultaneous hard drive failures.

Jobs are managed by the SLURM queue manager. Access to the cluster can be granted only to the participating professors and their research groups. If you qualify, enter your access application information here and your professor will be contacted to confirm your access.

Documentation on submitting jobs and other helpful links can be found here.


The cluster was built as a shared resource by participating College of Engineering professors with the understanding that the professors and their affiliated research groups will have complete and instantaneous access to the cluster nodes that they purchased. To illustrate, if a professor purchased five nodes of the cluster and wants to immediately run a job on those five nodes, any jobs currently running on those nodes will be immediately stopped and put back into the input queue and the professor’s job will run immediately. If the professor needs more resources than his original purchase (say 10 nodes), he can start a job requesting those resources and may be bumped if the owner of those other nodes requires them.

The compute node configuration is a 1U Dell PowerEdge R630 server with:

  • Two Intel E5-2630 v3 2.4GHz CPU’s with eight cores (16 threads) each
  • 64GB of RDIMM RAM
  • Intel QDR InfiniBand network adapter (30 gigabit, low latency)
  • 1 gigabit Ethernet network adaptor
  • 1 1TB 7200RPM hard drive
  • 10 Gigabit uplink to campus network backbone

Central storage is allocated based on the number of nodes purchased by a PI/Research group at 4TB per node. If 4 nodes are purchased 16TB storage will be allocated to the group. Storage can be expanded if additional nodes are purchased later.

Several compute nodes have the same internal configuration but are Dell PowerEdge R730 2U servers to accommodate the future use of two GPU cards.

HPC 1 Participating Research Groups

Biomedical Engineering
Sharon Aviran
Craig Benham
Yong Duan
Jinyi Qi
Cheemeng Tan

Chemical Engineering
Roland Faller

Civil and Environmental Engineering
Yueyue Fan
Jonathan Herman
Bassam Younis

Computer Science
Computer Science Department
Dipak Ghosal
Yong Jae Lee

Electrical and Computer Engineering
John Owens

Mechanical and Aerospace Engineering
Roger Davis
JP Delplanque
Seongkyu Lee

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