
The Research Computing team at Queen's University provide a number of centrally managed High Performance Computing (HPC) systems (detailed below). Researchers can avail of these systems in order to solve compute and data intensive problems.
-
Kelvin Cluster
Kelvin is a scalable High Performance Computing (HPC) and Research Data Storage environment (this cluster is the Dell Cluster replacement).
Installation date: Nov 2015
- Compute nodes run CENTOS operating system
- HP hardware
- 51 HP Apollo compute nodes with Intel Haswell generation processors
- High memory nodes ranging from 128GB to 1TB of RAM
- 500TB of lustre parallel file system for scratch
- Each node has 20 cores
- All compute nodes and storage are connected by an Infiniband fabric
- Visualisation node (Nvidia K4200) for openGL applications. This must be requested.
- Private cloud provision for applications such as Galaxy and CLC Bio.
- Windows Cluster
The Windows cluster provides support for Windows applications and users who want to work in Microsoft/GUI environment.
Installation year: 2013
Dell hardware
- Windows server 2012 operating system
- 16 x Dell c6220 servers
=> 256 cores
- Dual Intel Quad-core E5-2660 processors (64 GB memory )
- 10GB interconnect
- 30 terabytes of storage
- HPC Service
Software
A wide range of scientific software is available for all the systems. New software can be installed on request providing a valid software license is available.
Support for researchers
The Research Support team provide help in a number of ways:
- Training - a 90min introduction to Kelvin can be organized and delivered on request.
- Help with job scripts
- Software installation
- Consultancy
- Programming help
Accessing the service and Getting Help
Please use the QUB Sitehelpdesk
https://it.qub.ac.uk/sitehelpdesk/user/log.asp
Create a new case, choose "services", then "Highe Performance Computing" and pick a category.
The categories are:
a. user/group resquest or modification
b. jobscript help
c. application install request
d. suspected system issue
e. help with storage data
Last Updated: June 2017