Scaling-up spatially-explicit ecological models using graphics processors

Johan van de Koppel, Rohit Gupta, Cornelis Vuik
Spatial Ecology Department, The Netherlands Institute of Ecology (NIOO-KNAW), Post Office Box 140, 4400 AC Yerseke, The Netherlands
Ecological Modelling, Volume 222, Issue 17, Pages 3011-3019, 10 September 2011


   title={Scaling-up spatially-explicit ecological models using graphics processors},

   author={van de Koppel, J. and Gupta, R. and Vuik, C.},

   journal={Ecological Modelling},




Download Download (PDF)   View View   Source Source   



How the properties of ecosystems relate to spatial scale is a prominent topic in current ecosystem research. Despite this, spatially explicit models typically include only a limited range of spatial scales, mostly because of computing limitations. Here, we describe the use of graphics processors to efficiently solve spatially explicit ecological models at large spatial scale using the CUDA language extension. We explain this technique by implementing three classical models of spatial self-organization in ecology: a spiral-wave forming predator-prey model, a model of pattern formation in arid vegetation, and a model of disturbance in mussel beds on rocky shores. Using these models, we show that the solutions of models on large spatial grids can be obtained on graphics processors with up to two orders of magnitude reduction in simulation time relative to normal pc processors. This allows for efficient simulation of very large spatial grids, which is crucial for, for instance, the study of the effect of spatial heterogeneity on the formation of self-organized spatial patterns, thereby facilitating the comparison between theoretical results and empirical data. Finally, we show that large-scale spatial simulations are preferable over repetitions at smaller spatial scales in identifying the presence of scaling relations in spatially self-organized ecosystems. Hence, the study of scaling laws in ecology may benefit significantly from implementation of ecological models on graphics processors.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2024 hgpu.org

All rights belong to the respective authors

Contact us: