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Releases: hguo/ftk

Release 0.0.9

31 Oct 01:56
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  • Integration with DeformingSpacetimeMesh
  • Critical line tracking in 3D unstructured grid
  • Particle tracer for 2D/3D regular grid vector fields
  • Unit tests for SYCL-accelerated 2D critical point tracking
  • Application-specific updates
    • XGC: Handling of magnetic fields from equilibrium data
    • MPAS-Ocean: CPU- and GPU-based Lagrangian particle tracer with vertical velocity support

Release 0.0.8

21 Mar 16:30
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  • Support for 3D periodical spacetime meshes (the same 2D spatial meshes with designated way of spacetime triangulation)
  • Adding an option to enable/disable cell reordering in unstructured 3D grids
  • Fixing unit tests when building with metis; updating catch2 to 2.13.10 to fix linux build
  • Various performance improvement and bug fixes

Release 0.0.7.1

27 Nov 02:17
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  • Allowing partitioning of 2D unstructured mesh for critical point tracking in parallel.
  • Adding options to resample unstructured grids in input streams
  • Various performance improvements and bug fixes.

Release 0.0.6

26 Mar 01:50
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  • New ParaView filter CriticalPointTracker
    • The new filter is the replacement of the previous CriticalPoint2DTracker, CriticalPointTracker2DUnstructured, and CriticalPoint3DTracker
    • The new integrated filter will determine mesh type (e.g., vtkUnstructuredGrid and vtkImageData) and dimensionality (2 or 3) for tracking critical points
    • The new filter uses correct coordinates and extents for vtkStructuredGrid, vtkRectilinearGrid, and vtkImageData
  • New ParaView filter CriticalLineTracker that tracks intersections of isosurfaces in two scalar functions; GPU accelerated critical line tracker
  • SYCL support (experimental)
    • 2D critical point tracking in regular grids (experimental)
  • New features for XGC
    • XGC 3D blob core line tracking with CUDA acceleration
    • New executable ftk.xgc.poincare that computes Poincare plot for XGC simulations; CUDA accelerated Poincare plot computation
  • New features for MPAS-O
    • I/O for MPAS-O netCDF outputs
    • Eddy center tracking in MPAS-O outputs
  • Improved I/O for netCDF, HDF5, ADIOS2, and VTK
  • Documentation
    • New example of in situ critical point tracking in a heat transfer simulation
  • Various bug fixes and performance improvements

Release 0.0.5.1

15 Mar 04:05
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  • ParaView synthetic data sources: added new sources including MovingExtremum3DSource, MovingRamp3DSource, MovingDualRamp3DSource; added new options to inject noise to SpiralWoven2DSource; fixed implementation of DoubleGyre2DSource
  • ParaView filters: added Levelset3DTracker; added output options ("traced" and "sliced") for all existing filters (CriticalPoint2DTracker, CriticalPoint3DTracker, Levelset2DTracker, and Levelset3DTracker)
  • Documentation
    • A new page of different installation and compilation options
    • A new page to document a number of options to produce synthetic data for tutorial and testing purposes; all examples are provided with command lines and ParaView state files (.pvsm) for reproducibility
    • A new example of tracking critical points in a 2D flow-past-cylinder dataset
  • Various bug fixes and performance improvements

Release 0.0.5

10 Feb 20:47
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  • Easing compilation and installation with spack install ftk
  • Bug fixing and performance improvements
  • Supporting data reading from ADIOS2 .bp files
  • Unit testing with CUDA accelerated critical point tracking

Release 0.0.4

17 Nov 14:27
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  • Integrated track_critical_points, track_tdgl_vortex, track_contours into one single executable ftk
  • GPU acceleration for tracking TDGL vortices and contours
  • bug fixing and performance improvements

Release 0.0.2.2 - Introduction of PyFTK

01 Sep 15:30
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  • Python bindings of FTK
  • Numerous improvements and bug fix

Release 0.0.2

26 Mar 20:09
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This release features several new capabilities:

  • A ParaView plugin vtkCriticalPoint2DTracker that tracks minima, maxima, and saddles in 2D scalar fields
  • Distributed and parallel 2D/3D critical point tracking with MPI
  • CUDA-accelerated 2D/3D critical point tracking
  • Automated testing with Travis CI / Google Test