Computational Science Technical Note CSTN-156

CSTN Home

Spatial Data Structures, Sorting and GPU Parallelism for Situated-agent Simulation and Visualisation}

A. V. Husselmann and K. A. Hawick

Archived April 2012

Abstract

Spatial data partitioning techniques are important for obtaining fast and efficient simulations of N-Body particle and spatial agent based models where they considerably reduce redundant entity interaction computation times. Highly parallel techniques based on concurrent threading can be deployed to further speed up such simulations. We study the use of GPU accelerators and highly data parallel techniques which require more complex organisation of spatial datastructures and also sorting techniques to make best use of GPU capabilities. We report on a multiple-GPU (mGPU) solution to grid-boxing for accelerating interaction-based models. Our system is able to both simulate and also graphically render in excess of $10^5 - 10^6$ agents on desktop hardware in interactive-time.

Keywords: grid-boxing; sorting; GPU; thread concurrency; data parallelism.

Full Document Text: PDF version.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@INPROCEEDINGS{CSTN-156,
  author = {A. V. Husselmann and K. A. Hawick},
  title = {Spatial Data Structures, Sorting and GPU Parallelism for Situated-agent
	Simulation and Visualisation},
  booktitle = {Proc. Int. Conf. on Modelling, Simulation and Visualization Methods
	(MSV'12)},
  year = {2012},
  pages = {14-20},
  address = {Las Vegas, USA},
  month = {16-19 July},
  publisher = {CSREA},
  institution = {Computer Science, Massey University},
  timestamp = {2012.05.03}
}


[ CSTN Index | CSTN BiBTeX ]