Computational Science Technical Note CSTN-244

CSTN Home

High Performance Simulations and Visualisations of Hyper-Dimensional Diffusion-Limited Aggregation Models

S. G. Morgan and K. A. Hawick

Archived: 2013

Abstract

Diffusion-Limited Aggregation (DLA) is a much studied growth process that finds applications in modelling a wide variety of real world systems from soot to pollen to colloidal sediments. DLA processes can be simulated on both discrete and contibuous coordinate spaces and modern computer processing technology allows relatively large fractal clusters to be grown with sizes of 10 million individual particles or more. However there are a number of controlling parameters that influence DLA growth and it is desireable to be able to interact with a growing aggregate to investigate the effect of these parameters. Such computational steering experiments suppor t complex rendering and visualisations using artificiual colouring and shading to denote aggregate properties. We report on various approaches to simulating interactive DLA growth on desktop and tablet computers ing two, three and higher dimensions alongwith fast statistical analysis. We also discuss the potential for applying parallel computing techniques such as Graphical processing Units(GPUs) as accelerators to speed up simulation, rendering and analyses.

Keywords: diffusion-limited aggregation; hyperdimensional simulation; lattice model; visualization

Full Document Text: Not yet available.

Citation Information: BiBTeX database for CSTN Notes.

BiBTeX reference:

@TECHREPORT{CSTN-244,
        author = {S. G. Morgan and K. A. Hawick},
        title = {High Performance Simulations and Visualisations of Hyper-Dimensional
                Diffusion-Limited Aggregation Models},
        institution = {Computer Science, Massey University, Auckland, New Zealand},
        year = {2013},
        keywords = {diffusion-limited aggregation; hyperdimensional simulation; lattice
                model; visualization},
        owner = {kahawick},
        timestamp = {2013.09.06}
}


[ CSTN Index | CSTN BiBTeX ]