Facilities in the Department of Computer Science

Resources to suit your needs

The Department of Computer Science hosts dedicated facilities and software for all levels of study.

You’ll benefit from access to facilities that enhance your core studies and enable you to pursue your own projects related to your studies. We also provide study and group work rooms with PCs to support student learning in a less formal environment and provide a meeting area for group work.

Our facilities include:

dedicated computer laboratories, available Monday to Friday 08:00 to 18:00
access to the Reading Academic Computing Cluster (RACC), a Linux cluster consisting of 500 CPU cores and several GPU nodes
provisions for working remotely.

The course surprised me by being so practical – every year had memorable sessions that really drove home the theoretical learning.

Ross Beale, BSc Computer Science graduate

Computer labs and workstations

Our purpose-built computer labs host workstations that run both Windows and Linux operating systems with a variety of storage solutions.

Further resources are available to students, particularly for project work, including:

Oculus Rift virtual reality headsets
mobile phone and Raspberry pi devices
external web hosting via cPanel
a specialist wireless network to support mobile robots.

We also aim to support you with any particular hardware or software you may require for projects, including free access to commercial software. There is a dedicated technician is on hand to support all our facilities.

Student reviewing code on a computer screen

Our software

As a student, you’ll get free access to a wide range of software packages.

This includes tools for:

software and app development
systems modelling
data science
mathematical manipulation.

Dedicated master's and PhD spaces

Our Department hosts a master’s project/study room, featuring dual monitor PCs, a seating area, and a screen for practising presentations.

All our PhD students are offered their own desk and a standard-specification laptop and have access to our 2-node CPU/GPU (32-core/V100) compute cluster.