Cheat detection processing: A GPU versus CPU comparison

Abstract

In modern online multi-player games, game providers are struggling to keep up with the many different types of cheating. Cheat detection is a task that requires a lot of computational resources. Advances made within the field of heterogeneous computing architectures, such as graphics processing units (GPUs), have given developers easier access to considerably more computational resources, enabling a new approach to solving this issue. In this paper, we have developed a small game simulator that includes a customizable physics engine and a cheat detection mechanism that checks the physical model used by the game. To make sure that the mechanisms are fair to all players, they are executed on the server side of the game system. We investigate the advantages of implementing physics cheat detection mechanisms on a GPU using the Nvidia CUDA framework, and we compare the GPU implementation of the cheat detection mechanism with a CPU implementation. The results obtained from the simulations show that offloading the cheat detection mechanisms to the GPU reduces the time spent on cheat detection, enabling the servers to support a larger number of clients.