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Although the contour filter was recently divided into 2 filters, flying edges and marching cubes, the marching cubes version still had many conditions and was the file that took the longest to compile on Frontier. To help speed up parallel compiles and prevent a single run of a compiler from being overwhelmed, the compilation of all the marching cubes conditions has been split up using instantiations.
1.6 KiB
Split flying edges and marching cells into separate filters
The contour filter contains 2 separate implementations, Marching Cells and Flying Edges, the latter only available if the input has a CellSetStructured<3> and ArrayHandleUniformPointCoordinates for point coordinates. The compilation of this filter was lenghty and resource-heavy, because both algorithms were part of the same translation unit.
Now, this filter is separated into two new filters, ContourFlyingEdges and ContourMarchingCells, compiling more efficiently into two translation units. The Contour API is left unchanged. All 3 filters Contour, ContourFlyingEdges and ContourMarchingCells rely on a new abstract class AbstractContour to provide configuration and common utility functions.
Although Contour is still the preferred option for most cases because it selects the best implementation according to the input, ContourMarchingCells is usable on any kind of 3D Dataset. For now, ContourFlyingEdges operates only on structured uniform datasets.
Deprecate functions GetComputeFastNormalsForStructured, SetComputeFastNormalsForStructured, GetComputeFastNormalsForUnstructured and GetComputeFastNormalsForUnstructured, to use the more general GetComputeFastNormals and SetComputeFastNormals instead.
By default, for the Contour filter, GenerateNormals is now true, and ComputeFastNormals is false.
The marching cubes version of contour still has several possible compile paths, so it can still take a bit to compile. To help manage the compile time further, the contour filter compilation is broken up even further using the instantiation build capabilities.