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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 thatgeneralizes both regular and unstructured spatial meshes to spacetime whiletessellating spacetime mesh elements into simplices. The benefits of usingsimplicial spacetime meshes include (1) reducing ambiguity cases for featureextraction and tracking, (2) simplifying the handling of degeneracies usingsymbolic perturbations, and (3) enabling scalable and parallel processing. Theuse of simplicial spacetime meshing simplifies and improves the implementationof several feature-tracking algorithms for critical points, quantum vortices,and isosurfaces. As a software framework, FTK provides end users withVTK/ParaView filters, Python bindings, a command line interface, andprogramming interfaces for feature-tracking applications. We demonstrate usecases as well as scalability studies through both synthetic data and scientificapplications including Tokamak, fluid dynamics, and superconductivitysimulations. We also conduct end-to-end performance studies on the Summitsupercomputer. FTK is open-sourced under the MIT license:https://github.com/hguo/ftk

FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking