Hi Sebastian,
what are you trying to do with the 10 million+ point cloud? closest
location to itself is going to be painful yes :) when the point
clouds are reaching that high sometimes its best to have a similar
pointcloud around but with far fewer points. like say 1%.
Surprisingly it is a heck of a lot faster doing closest points lookup
from cloud A(10mill+) to a lowres cloud B (100k+) than to itself.
So workflow is:-
take original cloud A at 10mil+ duplicate and reduce down to Cloud B
1% with Ice nodes 'test random probability' and 'delete point'
remember to freeze this cloud so the delete point is not live
do all closest location lookup and additional processing on Cloud B
when finished do closest location lookup cloud A to B to transfer
results back to A
Its not perfect solution for everything but in some cases with eg
lighting pointclouds or working out densities in ICE it beats waiting
around for those 10mill+ points to work themselves out!
you may be able to do something cleverer with only the one high res
pointcloud but for me this level of abstraction works out ok
cheers
Rob