Efficient and portable combined Tausworthe random number generators
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Hardware-based simulation and collision detection for large particle systems
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
CUDA by Example: An Introduction to General-Purpose GPU Programming
CUDA by Example: An Introduction to General-Purpose GPU Programming
OpenCL Programming Guide
| Hi-index | 0.00 |
The mechanisms which lead to high tree species diversity in forests are not yet fully understood. One of the leading theories is that the natural enemies' interaction can give rise to a survival advantage for rare tree species over more common species. One way of exploring such observations is through the use of individual based modeling. An individual-based model (IBM) is a bottom up simulation where the bulk dynamics emerge from the interaction of individual constituents. Due to their emergent nature, IBMs are population sensitive where achieving a high degree of accuracy is synonymous with matching system population sizes. Consequently such models may run into the millions of individuals and become computationally intensive. Here the computing power of graphics processing units (GPUs) is used to overcome this computation limitation. The algorithms developed here for GPUs allow this model to be scaled into the millions of individuals and run on standard desktop computers. This effectively puts supercomputing power at the fingertips of researchers, students, and forest management services alike. The parallel implementation developed here was compared against a serial implementation running on the central processing unit. The results show a significant perfomance gain for the parallel implementation while maintaining statistical accuracy. This shows that realistically sized models can be efficiently executed on inexpensive mass-market desktop computer hardware.