The departmental Linux environment is available for those who need to use a Linux environment for particular software packages or code development, either for teaching or research. They are used extensively for computing-based UG and MSc courses and priority should be given to these users during term-time.

The environment is most readily accessible through a remote desktop on one of our multi-user Linux servers:


These are multi-user systems, meaning that they are often being used by many users concurrently. As such compute-intensive simulations should not be run directly on these machines. The following limits are in-place to prevent any one individual user unfairly causing excess load on these systems:

  • Maximum CPU allocation: 8 cores
  • Maximum memory usage: 16 GB

These limits apply across all sessions for each user on each system.

Your home directory on the Departmental Linux system is independent of other systems in the College. Files can be transferred to the College and personal computers using a number of software tools.


Accessing multi-user Linux machines depends on your computer’s operating system:

  • Windows. Use the Remote Desktop Connection tool provided by Windows. Enter one of the host names into the Host box and click connect.
  • Linux. Use the rdesktop tool available through most Linux distributions. You may need to install the corresponding package through your package manager.
  • OSX. Use the Remote Desktop Connection tool.

NOTE: you can also use the College's Remote Desktop Gateway, if the VPN is not working. More details of setting this up can be found on the Remote Access webpage. Note that you should set the "Security" setting to "RDP" if you are using Remmina on Linux.

Visualisation Wall

The Visualisation Wall is installed in CAGB 305 and can be used by Aeronautics academic staff, researchers and PhD students to explore and analyse large computational and experimental datasets. You can log into the system using your College credentials. Available software on the system includes Paraview for visualisation of data. See Software Packages for details on how to transfer files onto the departmental Linux system for use with the visualisation wall.

Additional Systems

The following additional systems are managed to support research projects:

  • (Dual-socket Intel(R) Xeon(R) Silver 4210 CPU @ 2.20GHz, 40 h/w cores, 192 GB RAM, 3 x NVIDIA T4 GPUs). This is for PhD students, researchers and staff working on machine learning problems.