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The Feature Tree: Visualizing Feature Tracking in Distributed AMR Datasets

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L. JiangAuthors Info & Claims

PVG '03: Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics

Page 14

https://doi.org/10.1109/PVGS.2003.1249048

Published: 20 October 2003 Publication History

Abstract

In this paper, we describe a feature extraction and tracking algorithm for AMR (Adaptive Mesh Refinement) datasets that operates within a distributed computing environment. Because features can span multiple refinement levels and multiple processors, tracking must be performed across time, across levels, and across processors. The resulting visualization is represented as a "Feature Tree". A feature will now contain multiple parts corresponding to different levels of refinements. The feature tree allows a viewer to determine that a feature splits or merges at the next refinement level, and allows a viewer to extract and isolate a multi-level isosurface and watch how that surface changes over both time and space. The algorithm is implemented within a computational steering environment which enables the visualization routines to operate on the data in-situ (while the simulation is ongoing).

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Cited By

Zou XWu KBoyuka DMartin DByna STang HBansal KLigocki TJohansen HSamatova NBalaji PXu C(2015)Parallel in situ detection of connected components in adaptive mesh refinement dataProceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing10.1109/CCGrid.2015.154(302-312)Online publication date: 4-May-2015
https://dl.acm.org/doi/10.1109/CCGrid.2015.154
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https://dl.acm.org/doi/10.1016/j.cag.2013.09.001
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cover image Guide Proceedings

PVG '03: Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics

October 2003

116 pages

ISBN:076952091X

Publisher

IEEE Computer Society

United States

Publication History

Published: 20 October 2003

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Cited By

Zou XWu KBoyuka DMartin DByna STang HBansal KLigocki TJohansen HSamatova NBalaji PXu C(2015)Parallel in situ detection of connected components in adaptive mesh refinement dataProceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing10.1109/CCGrid.2015.154(302-312)Online publication date: 4-May-2015
https://dl.acm.org/doi/10.1109/CCGrid.2015.154
Eichner CBittig ASchumann HTominski C(2014)Special Section on Visual AnalyticsComputers and Graphics10.1016/j.cag.2013.09.00138(18-26)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.1016/j.cag.2013.09.001
Peterka TRoss R(2012)Versatile communication algorithms for data analysisProceedings of the 19th European conference on Recent Advances in the Message Passing Interface10.1007/978-3-642-33518-1_33(275-284)Online publication date: 23-Sep-2012
https://dl.acm.org/doi/10.1007/978-3-642-33518-1_33
Fujishiro IOtsuka RTakahashi STakeshima Y(2005)T-mapProceedings of the 6th international symposium on high-performance computing and 1st international conference on Advanced low power systems10.5555/1783214.1783231(176-190)Online publication date: 7-Sep-2005
https://dl.acm.org/doi/10.5555/1783214.1783231
Tzeng FMa KKramer W(2005)Intelligent Feature Extraction and Tracking for Visualizing Large-Scale 4D Flow SimulationsProceedings of the 2005 ACM/IEEE conference on Supercomputing10.1109/SC.2005.37Online publication date: 12-Nov-2005
https://dl.acm.org/doi/10.1109/SC.2005.37
Ji GShen H(2004)Efficient isosurface tracking using precomputed correspondence tableProceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization10.5555/2384225.2384269(283-292)Online publication date: 19-May-2004
https://dl.acm.org/doi/10.5555/2384225.2384269
Garth CTricoche XScheuermann G(2004)Tracking of Vector Field Singularities in Unstructured 3D Time-Dependent DatasetsProceedings of the conference on Visualization '0410.1109/VISUAL.2004.107(329-336)Online publication date: 10-Oct-2004
https://dl.acm.org/doi/10.1109/VISUAL.2004.107

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