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|a 10.1109/TVCG.2023.3326526
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|a eng
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|a Lukasczyk, Jonas
|e verfasserin
|4 aut
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| 245 |
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|a ExTreeM
|b Scalable Augmented Merge Tree Computation via Extremum Graphs
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|c 2024
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|a Date Revised 27.12.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a Over the last decade merge trees have been proven to support a plethora of visualization and analysis tasks since they effectively abstract complex datasets. This paper describes the ExTreeM-Algorithm: A scalable algorithm for the computation of merge trees via extremum graphs. The core idea of ExTreeM is to first derive the extremum graph G of an input scalar field f defined on a cell complex K, and subsequently compute the unaugmented merge tree of f on G instead of K; which are equivalent. Any merge tree algorithm can be carried out significantly faster on G, since K in general contains substantially more cells than G. To further speed up computation, ExTreeM includes a tailored procedure to derive merge trees of extremum graphs. The computation of the fully augmented merge tree, i.e., a merge tree domain segmentation of K, can then be performed in an optional post-processing step. All steps of ExTreeM consist of procedures with high parallel efficiency, and we provide a formal proof of its correctness. Our experiments, performed on publicly available datasets, report a speedup of up to one order of magnitude over the state-of-the-art algorithms included in the TTK and VTK-m software libraries, while also requiring significantly less memory and exhibiting excellent scaling behavior
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|a Journal Article
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|a Will, Michael
|e verfasserin
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| 700 |
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|a Wetzels, Florian
|e verfasserin
|4 aut
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| 700 |
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|a Weber, Gunther H
|e verfasserin
|4 aut
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| 700 |
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|a Garth, Christoph
|e verfasserin
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|t IEEE transactions on visualization and computer graphics
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|g 30(2023), 1 vom: 23. Jan., Seite 1085-1094
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|u http://dx.doi.org/10.1109/TVCG.2023.3326526
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