Distributed Path Compression for Piecewise Linear Morse-Smale Segmentations and Connected Components
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866909307309654016 |
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| author | Will, Michael Lukasczyk, Jonas Tierny, Julien Garth, Christoph |
| author_facet | Will, Michael Lukasczyk, Jonas Tierny, Julien Garth, Christoph |
| contents | This paper describes the adaptation of a well-scaling parallel algorithm for computing Morse-Smale segmentations based on path compression to a distributed computational setting. Additionally, we extend the algorithm to efficiently compute connected components in distributed structured and unstructured grids, based either on the connectivity of the underlying mesh or a feature mask. Our implementation is seamlessly integrated with the distributed extension of the Topology ToolKit (TTK), ensuring robust performance and scalability. To demonstrate the practicality and efficiency of our algorithms, we conducted a series of scaling experiments on large-scale datasets, with sizes of up to 4096^3 vertices on up to 64 nodes and 768 cores. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_03771 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributed Path Compression for Piecewise Linear Morse-Smale Segmentations and Connected Components Will, Michael Lukasczyk, Jonas Tierny, Julien Garth, Christoph Distributed, Parallel, and Cluster Computing This paper describes the adaptation of a well-scaling parallel algorithm for computing Morse-Smale segmentations based on path compression to a distributed computational setting. Additionally, we extend the algorithm to efficiently compute connected components in distributed structured and unstructured grids, based either on the connectivity of the underlying mesh or a feature mask. Our implementation is seamlessly integrated with the distributed extension of the Topology ToolKit (TTK), ensuring robust performance and scalability. To demonstrate the practicality and efficiency of our algorithms, we conducted a series of scaling experiments on large-scale datasets, with sizes of up to 4096^3 vertices on up to 64 nodes and 768 cores. |
| title | Distributed Path Compression for Piecewise Linear Morse-Smale Segmentations and Connected Components |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2409.03771 |