Abstract
On-line multi-player games have experienced an impressive growth over the last decade.
Despite this success, game providers struggle to keep up with the many different types
of cheating occurring in these games. Due to the computational demand of a large scale
multi-player on-line game, server resources are becoming scarce. This makes the task of
implementing cheat detection mechanisms difficult, because of the lack of computational
resources. Advances within the field of General Purpose computing on Graphic Processing
Units (GPGPU), have given developers easier access to the computational power of the
GPU.
In this thesis, we investigate what possible benefits there are of implementing a GPGPU
cheat detection mechanism. We have developed a framework for a game simulator that
includes a simple customizable physical engine and a cheat detection mechanism. We have
created both a CPU and a GPGPU version of the cheat detection mechanism we have
constructed. The GPGPU implementation runs on NVIDIA GPUs using the Compute
Unified Device Architecture (CUDA) framework. We have also constructed a simple user
interface to provide a graphical representation of the game simulator.
The results we have obtained from our research indicate that offloading cheat detection
mechanisms to the GPU, increases the speed of the mechanism. We also discover that in
addition to being faster, the GPU mechanism allows the Central Processing Unit (CPU)
to perform other game relevant tasks while the mechanism is executing. Overall, our
research shows that game providers can benefit from offloading certain parts of their
server side processing to the GPU.