Visualization of big SPH simulations via compressed octree grids

Handle URI:
http://hdl.handle.net/10754/600173
Title:
Visualization of big SPH simulations via compressed octree grids
Authors:
Reichl, Florian; Treib, Marc; Westermann, Rudiger
Abstract:
Interactive and high-quality visualization of spatially continuous 3D fields represented by scattered distributions of billions of particles is challenging. One common approach is to resample the quantities carried by the particles to a regular grid and to render the grid via volume ray-casting. In large-scale applications such as astrophysics, however, the required grid resolution can easily exceed 10K samples per spatial dimension, letting resampling approaches appear unfeasible. In this paper we demonstrate that even in these extreme cases such approaches perform surprisingly well, both in terms of memory requirement and rendering performance. We resample the particle data to a multiresolution multiblock grid, where the resolution of the blocks is dictated by the particle distribution. From this structure we build an octree grid, and we then compress each block in the hierarchy at no visual loss using wavelet-based compression. Since decompression can be performed on the GPU, it can be integrated effectively into GPU-based out-of-core volume ray-casting. We compare our approach to the perspective grid approach which resamples at run-time into a view-aligned grid. We demonstrate considerably faster rendering times at high quality, at only a moderate memory increase compared to the raw particle set. © 2013 IEEE.
Citation:
Reichl F, Treib M, Westermann R (2013) Visualization of big SPH simulations via compressed octree grids. 2013 IEEE International Conference on Big Data. Available: http://dx.doi.org/10.1109/BigData.2013.6691717.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2013 IEEE International Conference on Big Data
KAUST Grant Number:
UK- C0020
Issue Date:
Oct-2013
DOI:
10.1109/BigData.2013.6691717
Type:
Conference Paper
Sponsors:
We would like to thank Volker Springel from the MaxPlanck Society in Garching for his support with the data set.This publication is based on work supported by Award No.UK- C0020, made by King Abdullah University of Scienceand Technology (KAUST).
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Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorReichl, Florianen
dc.contributor.authorTreib, Marcen
dc.contributor.authorWestermann, Rudigeren
dc.date.accessioned2016-02-28T06:44:22Zen
dc.date.available2016-02-28T06:44:22Zen
dc.date.issued2013-10en
dc.identifier.citationReichl F, Treib M, Westermann R (2013) Visualization of big SPH simulations via compressed octree grids. 2013 IEEE International Conference on Big Data. Available: http://dx.doi.org/10.1109/BigData.2013.6691717.en
dc.identifier.doi10.1109/BigData.2013.6691717en
dc.identifier.urihttp://hdl.handle.net/10754/600173en
dc.description.abstractInteractive and high-quality visualization of spatially continuous 3D fields represented by scattered distributions of billions of particles is challenging. One common approach is to resample the quantities carried by the particles to a regular grid and to render the grid via volume ray-casting. In large-scale applications such as astrophysics, however, the required grid resolution can easily exceed 10K samples per spatial dimension, letting resampling approaches appear unfeasible. In this paper we demonstrate that even in these extreme cases such approaches perform surprisingly well, both in terms of memory requirement and rendering performance. We resample the particle data to a multiresolution multiblock grid, where the resolution of the blocks is dictated by the particle distribution. From this structure we build an octree grid, and we then compress each block in the hierarchy at no visual loss using wavelet-based compression. Since decompression can be performed on the GPU, it can be integrated effectively into GPU-based out-of-core volume ray-casting. We compare our approach to the perspective grid approach which resamples at run-time into a view-aligned grid. We demonstrate considerably faster rendering times at high quality, at only a moderate memory increase compared to the raw particle set. © 2013 IEEE.en
dc.description.sponsorshipWe would like to thank Volker Springel from the MaxPlanck Society in Garching for his support with the data set.This publication is based on work supported by Award No.UK- C0020, made by King Abdullah University of Scienceand Technology (KAUST).en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectdata compressionen
dc.subjectSPHen
dc.subjectvolume renderingen
dc.titleVisualization of big SPH simulations via compressed octree gridsen
dc.typeConference Paperen
dc.identifier.journal2013 IEEE International Conference on Big Dataen
dc.contributor.institutionTechnische Universitat Munchen, Munich, Germanyen
kaust.grant.numberUK- C0020en
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