Distributed Augmentation, Hypersweeps, and Branch Decomposition of Contour Trees for Scientific Exploration

Year: 2024

Type: article

Abstract: Contour trees describe the topology of level sets in scalar fields and are widely used in topological data analysis and visualization. A main challenge of utilizing contour trees for large-scale scientific data is their computation at scale using high-performance computing. To address this challenge, recent work has introduced distributed hierarchical contour trees for distributed computation and storage of contour trees. However, effective use of these distributed structures in analysis and visualization requires subsequent computation of geometric properties and branch decomposition to support contour extraction and exploration. In this work, we introduce distributed algorithms for augmentation, hypersweeps, and branch decomposition that enable parallel computation of geometric properties, and support the use of distributed contour trees as query structures for scientific exploration. We evaluate the parallel performance of these algorithms and apply them to identify and extract important contours for scientific visualization.

Source: IEEE Transactions on Visualization and Computer Graphics

DOI: 10.1109/tvcg.2024.3456322

Authors: Mingzhe Li, Hamish Carr, Oliver Rübel, Bei Wang, Gunther H. Weber

Institutions: University of Utah, University of Leeds, Lawrence Berkeley National Laboratory

Language: English

Topic: Topological and Geometric Data Analysis

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, U.S. Department of Energy, National Energy Research Scientific Computing Center, University of Leeds, Office of Science, National Nuclear Security Administration, Advanced Scientific Computing Research, Lawrence Berkeley National Laboratory

OpenAlex ID: W4402401646