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HPC Community

HPC usage at CQU is at record high levels! More domains are discovering the avantage of using the HPC. This means there is a vast and diverse community of CQU HPC users out there to be engaged with.

HPC Microsoft Teams Site

The easiest way to get involved with CQU's HPC community is to join the High Performance Computing Microsoft Teams Site. Anyone with a CQU account is freely able to join and leave this site. The intention of the site is to allow users to collaborate, help each other, bounce ideas around, allow for explosure and broaden the outlook of just what is possible in this ever changing space!

The purpose for each channel is loosely based on:

  • Programming – this channel is designed to discuss HPC programming type topics.
  • The Random HPC channel is more a casual channel to discuss random HPC related topics.
To join the “HPC Team”, start the teams application, click on the “Join or create a team” link in the bottom left hand corner, and then search for High performance Computing team -> then join this team!

Hacky Hour

Teams is not the only way to engage with CQU's HPC community. There is also the weekly Hacky Hour!

The Hacky Hour session is a free and informal session that allows researchers (including RHD students) to drop in for advice or to offer their IT expertise to help others.

The session does not simply have to be about the HPC but it is a fantastic way to meet other users in a live and informal environment.

The sessions are run every Wednesday from 3pm to 4pm QLD time and are held online via Zoom. The Zoom link can be found in the HPC Microsoft Teams Site or you can email eResearch@cqu.edu.au.

Some of the topics we can assist with include:

  • high performance computing (HPC)
  • cloud computing / virtual machines
  • research data management and data management plans – including the new Data Manager system!
  • research data storage
  • research data publishing
  • ORCiDs
  • data processing and pipelines
  • version control
  • automated workflows
  • Programming (Python, R)
  • Linux
  • Software and Data Carpentry.