Name
Title | ||
|---|---|---|
Loose capacity-constrained representatives for the qualitative visual analysis in molecular dynamics |
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/PACIFICVIS.2011.5742372 | Pacific Visualization Symposium |
Keywords | Field | DocType |
particle distribution,material science,original data,application domain,general technique,capacity-constrained representative,qualitative visual analysis,molecular dynamic,material property,detailed domain knowledge,real-world data set,simulated particle,voronoi diagram,clustering algorithms,parallel algorithms,structural changes,molecular dynamics,visual analysis,clustering,dynamic systems theory,density function theory,data visualization,dynamical systems theory,materials science,data visualisation,density functional theory,structural change,measurement,data analysis,computational geometry,visualization,parallel algorithm,domain knowledge,material properties,thermodynamics | Data mining,Data visualization,Domain knowledge,Parallel algorithm,Visualization,Computer science,Computational geometry,Theoretical computer science,Dynamical systems theory,Voronoi diagram,Cluster analysis | Conference |
ISSN | ISBN | Citations |
2165-8765 | 978-1-61284-933-1 | 7 |
PageRank | References | Authors |
0.49 | 15 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Steffen Frey | 1 | 116 | 18.93 |
| Thomas Schlomer | 2 | 7 | 0.49 |
| Sebastian Grottel | 3 | 140 | 10.41 |
| Carsten Dachsbacher | 4 | 1396 | 93.20 |
| Oliver Deussen | 5 | 2852 | 205.16 |
| Thomas Ertl | 6 | 4417 | 401.52 |