13863

Collaborative Diffusion on the GPU for Path-Finding in Games

Craig McMillan, Emma Hart, Kevin Chalmers
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}

}

Download Download (PDF)   View View   Source Source   

873

views

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.
VN:F [1.9.22_1171]
Rating: 5.0/5 (1 vote cast)
Collaborative Diffusion on the GPU for Path-Finding in Games, 5.0 out of 5 based on 1 rating

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: