A GPU-based multi-resolution algorithm for simulation of seed dispersal

Jing FAN; Hai-feng JI; Xin-xin GUAN; Ying TANG

doi:10.1631/jzus.C1200147

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A GPU-based multi-resolution algorithm for simulation of seed dispersal

Computer & Automation | Updated：2022-05-19

- A GPU-based multi-resolution algorithm for simulation of seed dispersal
- A GPU-based multi-resolution algorithm for simulation of seed dispersal
- Frontiers of Information Technology & Electronic Engineering Vol. 13, Issue 11, Pages: 816-827(2012)
- Affiliations：
  
  School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
- Author bio：
  
  [ "Jing FAN, E-mail: fanjing@zjut.edu.cn" ]
  Ying TANG, E-mail: tangying@gmail.com
- Funds：
- DOI：10.1631/jzus.C1200147
  CLC： TP391.9
- Received：23 May 2012，
  
  Revised：2012-10-12，
  
  Published：2012-11
- Accepted：
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Jing FAN, Hai-feng JI, Xin-xin GUAN, et al. A GPU-based multi-resolution algorithm for simulation of seed dispersal[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(11): 816-827.
DOI：

Jing FAN, Hai-feng JI, Xin-xin GUAN, et al. A GPU-based multi-resolution algorithm for simulation of seed dispersal[J]. Frontiers of Information Technology & Electronic Engineering, 2012, 13(11): 816-827. DOI： 10.1631/jzus.C1200147.

摘要

Abstract

In forest dynamics models

the intensive computation and load involved in the simulation of seed dispersal can become unbearably huge for large-scale forest analysis. To solve this problem

we propose a multi-resolution algorithm to compute seed dispersal on GPU. By exploiting the computation parallelism of seed dispersal

the computation of the whole forest plot is divided into multiple small plot cells

which are computed independently by parallel threads on GPU. To further improve the calculation efficiency with limited threads scale for GPU computation

we propose a hierarchical method to cluster the plot cells into a multi-resolution form according to the biological curves of tree seed dispersal. Experimental results show that our algorithm not only greatly reduces computational time but also obtains comparably correct results as compared to the naive GPU algorithm

which makes it especially suitable for large-scale forest modeling.

关键词

Keywords

references

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