ExTreeM: Scalable Augmented Merge Tree Computation via Extremum Graphs

Journal Article · 23 October 2023 · IEEE Transactions on Visualization and Computer Graphics

DOI: https://doi.org/10.1109/tvcg.2023.3326526 · OSTI ID:2370363

Lukasczyk, Jonas ^[1]; Will, Michael ^[1]; Wetzels, Florian ^[1]; Weber, Gunther H. ^[2]; Garth, Christoph ^[1]

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1. Univ. Kaiserslautern-Landau (RPTU) (Germany)
2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Over the last decade merge trees have been proven to support a plethora of visualization and analysis tasks since they effectively abstract complex datasets. Here, 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.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE National Nuclear Security Administration (NNSA); USDOE Exascale Computing Project
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 2370363
• Journal Information: IEEE Transactions on Visualization and Computer Graphics, Journal Name: IEEE Transactions on Visualization and Computer Graphics Journal Issue: 1 Vol. 30; ISSN 1077-2626
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English