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Computing Facilities

We have four well-equipped, student computing laboratories in the department. The computer labs are also accessible remotely. Access to online learning platforms includes Github classroom, Codio and Repl.it.

A wide variety of applications and development software runs on a range of platforms including Solaris (Unix), Windows and Linux.

  • Languages: Python, Java, C++, C#, C, Groovy, Haskell
  • IDEs: Eclipse, Scala, IntelliJ IDEA, JetBrains (RubyMine, CLion, PyCharm), Erlang, Glider, BlueJ, Android SDK, Anaconda
  • Software development: Git, Github desktop
  • Modelling environments: Matlab & All Matlab Toolboxes, StarLogo, Protege
  • Databases: Oracle, MySQL, SQLserver, DB2, Postgres, MongoDB, Hadoop
  • Data Science: R, RStudio, Neo4j
  • HTC/HPC: jupyterhub, tensorflow, torch, kubernetes
  • Website development: PHP, Perl, Tomcat, Javascript (Node.js),
  • XML development: XMLSpy, xt, xmlgrep, NotePad++ with XMLTools addin.
  • X/Unix: X2Go, Cygwin, Putty
  • Office: Microsoft Office365, Open Office, Visio, LaTeX (MikTeX)
  • Virtual learning environment and teaching tools: Moodle, Panopto, Collaborate, MS Teams
  • Browsers: Firefox, IE, Chrome
  • Email: Thunderbird, webmail
  • Accessibility software: ClaroRead
  • Utility: Filezilla, MagicDisc, TextPad, GIMP, Trend Apex anti-virus, Audacity, NotePad++

The 1/10/25-gigabit LAN is connected to the JANET University Network via the UCISA London Group. Departmental computer services and networks are managed and supported by the department's Systems Group.

Computing resources

GPU Cluster
Compute nodes Number Processor Cores per GPU RAM per GPU
2 8x GTX1080Ti 3584 12GB
3 4x Tesla P100 3584 16GB

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Condor Pool
Compute nodes Number Processor RAM per node
1400 i7 1-2GB

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Xen Servers
Number CPUs Cores RAM (GB) Disk (TB)
1 2x AMD 6276 64 128 1.6
2 2x AMD 6376 32 128 1.6
2 2x AMD 6368 32 256 1.6
4 2x Xeon E5-2640v3 32 128 2 (SSD)
1 2x Xeon E5-2667v4 16 256 8 (PCIe SSD)