Optimization and Augmentation for Data Parallel Contour Trees
| Autor: | Oliver Rubel, Gunther H. Weber, James Ahrens, Hamish Carr |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Artificial Intelligence and Image Processing
Computer science Scientific visualization Parallel algorithm Software Engineering 020207 software engineering Computation Theory and Mathematics 02 engineering and technology Construct (python library) Computer Graphics and Computer-Aided Design Trees Hyperstructure Signal Processing 0202 electrical engineering electronic engineering information engineering Computer Graphics Topological data analysis Computer Vision and Pattern Recognition Representation (mathematics) Algorithm Software Algorithms |
| Zdroj: | IEEE transactions on visualization and computer graphics, vol 28, iss 10 IEEE transactions on visualization and computer graphics, vol PP, iss 99 |
| ISSN: | 1941-0506 1077-2626 |
| Popis: | Contour trees are used for topological data analysis in scientific visualization. While originally computed with serial algorithms, recent work has introduced a vector-parallel algorithm. However, this algorithm is relatively slow for fully augmented contour trees which are needed for many practical data analysis tasks. We therefore introduce a representation called the hyperstructure that enables efficient searches through the contour tree and use it to construct a fully augmented contour tree in data parallel, with performance on average 6 times faster than the state-of-the-art parallel algorithm in the TTK topological toolkit. |
| Databáze: | OpenAIRE |
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