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Visualization Symposium, IEEE Pacific (2011)
Hong Kong, China
Mar. 1, 2011 to Mar. 4, 2011
ISBN: 978-1-61284-935-5
pp: 51-58
ABSTRACT
Molecular dynamics is a widely used simulation technique to investigate material properties and structural changes under external forces. The availability of more powerful clusters and algorithms continues to increase the spatial and temporal extents of the simulation domain. This poses a particular challenge for the visualization of the underlying processes which might consist of millions of particles and thousands of time steps. Some application domains have developed special visual metaphors to only represent the relevant information of such data sets but these approaches typically require detailed domain knowledge that might not always be available or applicable. We propose a general technique that replaces the huge amount of simulated particles by a smaller set of representatives that are used for the visualization instead. The representatives capture the characteristics of the underlying particle density and exhibit coherency over time. We introduce loose capacity-constrained Voronoi diagrams for the generation of these representatives by means of a GPU-friendly, parallel algorithm. This way we achieve visualizations that reflect the particle distribution and geometric structure of the original data very faithfully. We evaluate our approach using real-world data sets from the application domains of material science, thermodynamics and dynamical systems theory.
INDEX TERMS
molecular dynamics method, computational geometry, data analysis, data visualisation, dynamical systems theory, loose capacity-constrained representatives, qualitative visual analysis, molecular dynamics, simulation technique, material properties, structural changes, external forces, visual metaphors, loose capacity-constrained Voronoi diagrams, GPU-friendly algorithm, parallel algorithm, real-world data sets, material science, thermodynamics, Graphics processing unit, Data visualization, Measurement, Density functional theory, Visualization, Clustering algorithms, Parallel algorithms, time-dependent data, particle-based visualization, molecular dynamics, clustering
CITATION
"Loose capacity-constrained representatives for the qualitative visual analysis in molecular dynamics", Visualization Symposium, IEEE Pacific, vol. 00, no. , pp. 51-58, 2011, doi:10.1109/PACIFICVIS.2011.5742372
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