Using GPU enabled systems in the CS department

There are several systems available for GPU processing:


PCs in lab 105

Lab Machines

The desktops in lab 105 and have i9 processors, 128GB RAM and Nvidia GeForce RTX 3090 graphics cards, which makes them ideal for code development, learning and testing. To utilise these GPUs select the GPU tab on the CS labs page.


Blaze is the name of a Linux server with 4 Nvidia GTX Titan X cards, each with 3072 cores and 12GB of RAM.

To access blaze, run the command:


Blaze is a managed Linux machine, and so you will be able to access your home directory once you are connected.

Blaze is a good option if you wish to run a longer compute job. Please note that blaze is a timeshare machine, so there is no guarantee that its GPUs will be available. Running the command nvidia-smi will print a summary of the cards, as well as the processes that each card is working on. If all cards are occupied, unfortunately you will either have to run your jobs on a different system, or wait for the cards to become free.

In order to facilitate more efficient usage of Blaze’s GPUs, it is important to only run your processes on one card. To do this, navigate to the directory /usr/local/cuda/ . Then run the following command:


To check which GPU your system is using, and to ensure that the environment variable has
been set correctly, type:

env | grep CUDA

You should the following output:


with n being a number between 0 and 3.

Installing GPU frameworks on Linux

In order to install Tensorflow in your filespace, first you need to add Python to your path by running one of the setup scripts in:


as follows:

source /opt/Python/Python-3.10.1_Setup.csh

Please pick whichever version is appropriate for your work.

Then, use pip (Python package manager) to install Tensorflow/Pytorch package:

pip install torch --user

If you don’t add the –user flag, pip may attempt to install Tensorflow in the global filesystem, which you won’t have write permissions for.

For any issues with blaze, please contact us, or come and see us in person.