In recent years, multi-core graphics processing units (GPUs) have been increasingly used by researchers for other purposes than rendering graphics. This thesis presents the implementation of GPU computing for real-time control of plasma instabilities known as resistive wall modes at the EXTRAP T2R fusion plasma device. A NVIDIA GPU is installed in the device plasma control system. Using the CUDA parallel computing platform, PID and LQG control algorithms are developed for the GPU. It is shown that computation times decrease with up to 80 % for the LQG algorithm and 33 % for the PID algorithm if computations in the control system are shifted from the central processing unit (CPU) to the GPU. The gains of GPU utilization are limited by latencies introduced by the CPU-GPU interaction. To better exploit the potential of the GPU, a zero-copy method is proposed, in which the GPU is allowed to perform read and write operations on CPU memory.