[vtk-developers] A question regarding the most efficient way to merge neighbouring points in an iterative method

Robert Maynard robert.maynard at kitware.com
Mon Mar 18 02:08:00 EDT 2013


For DAX we have had good success with sort, unique and than lower bounds to
reduce a vector of points into the unique points.

To can check out the benchmark code I wrote here:
https://github.com/robertmaynard/PointMergingBenchmark to try out
both an incremental octree point locator and the sort code.

On 10 million points with 66% of them being duplicates under release mode (
which is very important ), I get the lower bounds methods
being ~9 to 10 times faster.




On Sun, Mar 17, 2013 at 8:25 AM, Philippe Pébay
<philippe.pebay at kitware.com>wrote:

> Hello all,
>
> I have a question regarding the most efficient way to insert points in an
> iterative method creating those as the algorithm progresses.
>
> Naively I am using a locator to insert each new point and possibly merge
> it on the fly if it is epsilon-close to a pre-existing one. This is
> convenient  and memory-wise this is efficient because the code does not
> grow a list of replicated points.
>
> However, if we put memory aside and focus on speed, then it seems to be
> more effective to merge points in a single pass, once they have all been
> created. Especially as the complexity of the mesh increases.
>
> If anyone has looked into this issue I would appreciate any elements of
> discussion.
>
> Thank you
> Philippe
>
> --
> Philippe Pébay, PhD
> Director of Visualization and High Performance Computing /
> Directeur de la Visualisation et du Calcul Haute Performance
> Kitware SAS
> 26 rue Louis Guérin, 69100 Villeurbanne, France
> +33 (0) 6.83.61.55.70 / 4.37.45.04.15
> http://www.kitware.fr <http://www.kitware.fr/>
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-- 
Robert Maynard
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