Collaborative Diffusion on the GPU for Path-Finding in Games
Edinburgh Napier University
17 March 2015
@incollection{mcmillan2015collaborative,
title={Collaborative Diffusion on the GPU for Path-Finding in Games},
author={McMillan, Craig and Hart, Emma and Chalmers, Kevin},
booktitle={Applications of Evolutionary Computation},
pages={418–429},
year={2015},
publisher={Springer}
}
Exploiting the powerful processing power available on the GPU in many machines, we investigate the performance of parallelised versions of pathfinding algorithms in typical game environments. We describe a parallel implementation of a collaborative diffusion algorithm that is shown to find short paths in real-time across a range of graph sizes and provide a comparison to the well known Dijkstra and A* algorithms. Although some trade-off of cost vs path-length is observed under specific environmental conditions, results show that it is a viable contender for pathfinding in typical real-time game scenarios, freeing up CPU computation for other aspects of game AI.
April 15, 2015 by craigmcmillan01