Comments (2)
bottler
commented on June 29, 2024
Would this task naturally use multiple cuda kernels, because you don't know in advance how big the output is? Like how knn is easier than radius-sampling because having k upfront lets everything happen in a single kernel.
Maybe using the current function with a large number of points and just take some of the output is as fast as you'll get.
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Chaoqi-LIU
commented on June 29, 2024
Hi, I wrote my own ad-hoc version with cuda/cpu, and yes you are right, we cannot know in advance the # output points. So I provide one more additional arg as the cap on # output points, and use max_dist < r as the early stop signal, it's pretty fast and results was satisfying.
Thanks anyway!
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