FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking
Abstract
We present the Feature Tracking Kit (FTK), a framework that simplifies, scales, and delivers various feature-tracking algorithms for scientific data. The key of FTK is our high-dimensional simplicial meshing scheme that generalizes both regular and unstructured spatial meshes to spacetime while tessellating spacetime mesh elements into simplices. The benefits of using simplicial spacetime meshes include (1) reducing ambiguity cases for feature extraction and tracking, (2) simplifying the handling of degeneracies using symbolic perturbations, and (3) enabling scalable and parallel processing. The use of simplicial spacetime meshing simplifies and improves the implementation of several feature-tracking algorithms for critical points, quantum vortices, and isosurfaces. As a software framework, FTK provides end users with VTK/ParaView filters, Python bindings, a command line interface, and programming interfaces for feature-tracking applications. We demonstrate use cases as well as scalability studies through both synthetic data and scientific applications including Tokamak, fluid dynamics, and superconductivity simulations. We also conduct end-to-end performance studies on the Summit supercomputer. FTK is open-sourced under the MIT license: https://github.com/hguo/ftk.
Recommended Citation
H. Guo et al., "FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking," IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 8, pp. 3463 - 3480, Institute of Electrical and Electronics Engineers (IEEE), Aug 2021.
The definitive version is available at https://doi.org/10.1109/TVCG.2021.3073399
Department(s)
Computer Science
Research Center/Lab(s)
Intelligent Systems Center
Keywords and Phrases
Critical Points; Distributed and Parallel Processing; Faces; Feature Extraction; Feature Tracking; Isosurfaces; Isosurfaces; Parallel Processing; Spacetime Meshing; Three-Dimensional Displays; Topology; Tracking; Vortices
International Standard Serial Number (ISSN)
1077-2626; 1941-0506
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2021 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Aug 2021
Comments
This work was supported in part by the Exascale Computing Project (ECP), through Project 17-SC-20-SC, a collaborative effort of the U.S. Department of Energy Office of Science and the National Nuclear Security Administration, as part of the Co-design center for Online Data Analysis and Reduction (CODAR) [66], in part by the Scientific Discovery through Advanced Computing (SciDAC) Program, Office of Advanced Scientific Computing Research, U.S. Department of Energy, in part by the Laboratory Directed Research and Development (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, U.S. Department of Energy, under Grant DE-AC02-06CH11357, and in part by the National Science Foundation Division of Information and Intelligent Systems under Grant 1955764.