@inproceedings{b064d2cdb1cf40a1a0aa63ea4a10f0dd,
title = "Interactive visual exploration of a trillion particles",
abstract = "We present a method for the interactive exploration of tera-scale particle data sets. Such data sets arise from molecular dynamics, particle-based fluid simulation, and astrophysics. Our visualization technique provides a focus+context view of the data that runs interactively on commodity hardware. The method is based on a hybrid multi-scale rendering architecture, which renders the context as a hierarchical density volume. Fine details in the focus are visualized using direct particle rendering. In addition, clusters like dark matter halos can be visualized as semi-Transparent spheres enclosing the particles. Since the detail data is too large to be stored in main memory, our approach uses an out-of-core technique that streams data on demand. Our technique is designed to take advantage of a dual-GPU configuration, in which the workload is split between the GPUS based on the type of data. Structural features in the data are visually enhanced using advanced rendering and shading techniques. To allow users to easily identify interesting locations even in overviews, both the focus and context view use color tables to show data attributes on the respective scale. We demonstrate that our technique achieves interactive performance on a one trillionpar-Ticle data set from the DarkSky simulation.",
keywords = "I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling-Object hierarchies, J.2 [Computer Applications]: Physical Sciences and Engineering-Astronomy",
author = "Karsten Schatz and Christoph Muller and Michael Krone and Jens Schneider and Guido Reina and Thomas Ertl",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 6th IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2016 ; Conference date: 23-10-2016",
year = "2017",
month = mar,
day = "8",
doi = "10.1109/LDAV.2016.7874310",
language = "English",
series = "IEEE Symposium on Large Data Analysis and Visualization 2016, LDAV 2016 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "56--64",
editor = "Kenneth Moreland and Markus Hadwiger and Ross Maciejewski",
booktitle = "IEEE Symposium on Large Data Analysis and Visualization 2016, LDAV 2016 - Proceedings",
address = "United States",
}