feat: Add new scatter strategies for initial mesh redistribution

[bd713]

Problem

The current strategy to scatter the mesh initially loaded by rank 0 uses vtkRedistributeDataSetFilter (kd-tree partitioning). This approach can take several minutes for large meshes (10s of millions of elements) when redistributed among 1000+ ranks.

Recent example: A 136M cell mesh redistributed to 1024 ranks takes about 17 minutes with the current kd-tree approach.

Solution

This PR adds partitioning strategies that bypass the VTK library's bottleneck, available via the new scatterMethod XML attribute.

Available strategies

Method	Description	Comment
kdtree	VTK built-in kd-tree (default)	Spatial locality, but can be slow and current version can lose tetra or pyramid cells
contiguous	Contiguous cell-index blocks	Fast, but does not guarantee spatial locality
cartesian	Regular Cartesian grid using -x/-y/-z partition counts	Does not guarantee load balancing if mesh is irregular
rcb	Recursive Coordinate Bisection along longest bounding-box axis	Spatial locality + load balance

Remark

The resulting partitions can be further refined and improved via calls to ParMetis or PTScotch with partitionRefinement>0

Benchmark

==============================================================================================================
SUMMARY (1024 ranks, 135901500 cells)
==============================================================================================================
Method        | Time (s)  | Cells       | Status  | Min cells | Max cells | Imbalance   | BBox Overlap
--------------------------------------------------------------------------------------------------------------
KdTree        | 1020.194  | 135901494   | LOSS    | 126714    | 139764    | 1.053103    | 1.086       
Contiguous    |   15.822  | 135901500   | OK      | 132716    | 132717    | 1.000005    | 2.861       
Cartesian     |   22.005  | 135901500   | OK      | 116157    | 152266    | 1.147304    | 1.095       
RCB           |   34.289  | 135901500   | OK      | 132716    | 132717    | 1.000005    | 1.116       
--------------------------------------------------------------------------------------------------------------

Speedup relative to each method:
  KdTree        64.48x slower than fastest
  Contiguous    1.00x slower than fastest <-- fastest
  Cartesian     1.39x slower than fastest
  RCB           2.17x slower than fastest

Best load balance: Contiguous (imbalance ratio: 1.000005x)
Best compactness:  KdTree (bbox overlap: 1.086)
==============================================================================================================

Rebaseline needed

57/67 failures are XML metadata diff: Group has a child 'scatterMethod' in the file to compare but not the baseline file.
10/67 are real partitioning changes in contact cases as we switched from Morton's algorithm to RCB

[victorapm]

That looks great, Bertrand. Even though contiguous is the fastest, we might want to have RCB as default since bbox values look much better and the additional cost is not too bad. cc @castelletto1

[dkachuma]

Looks good to me.

[joshua-white]

Nice. Only suggestion might be to add a log note if a "large" mesh and kdtree are detected, suggesting user consider something else.