Optimization Of Large-Scale, Real-Time Simulations By Spatial Hashing
AI; Collision detection; Frustum culling; Picking; Spatial hashing
As simulations grow in scale, optimization techniques become virtually required to provide real-time response. In this paper we will discuss how spatial hashing can be utilized to optimize many aspects of large-scale simulations. Spatial hashing is a technique in which objects in a 2D or 3D domain space are projected into a 1D hash table allowing for very fast queries on objects in the domain space. Previous research has shown spatial hashing to be an effective optimization technique for collision detection. We propose several extensions of the technique in order to simultaneously optimize nearly all aspects of simulations including: 1) mobile object collision, 2) object-terrain collision, 3) object and terrain rendering, 4) object interaction, decision, or AI routines, and 5) picking. The results of a simulation are presented where visibility determination, collision and response, and an AI routine is calculated in real-time for over 30,000 mobiles objects on a typical desktop PC.
Summer Computer Simulation Conference 2005, SCSC 2005, Part of the 2005 Summer Simulation Multiconference, SummerSim 2005
Number of Pages
Article; Proceedings Paper
Source API URL
Hastings, Erin J.; Mesit, Jaruwan; and Guha, Ratan K., "Optimization Of Large-Scale, Real-Time Simulations By Spatial Hashing" (2005). Scopus Export 2000s. 3140.