Source

nrnr / perfnotes.txt

Peter Shinners eccbc3b 

Peter Shinners 2cfda6f 
Peter Shinners eccbc3b 





















Peter Shinners 2cfda6f 



Peter Shinners eccbc3b 



Peter Shinners 2cfda6f 



Peter Shinners 1a75ba3 



Peter Shinners 2cfda6f 






Peter Shinners 1a75ba3 





nrnr
Create neighborhood: 15.615 sec
80r = Search block 5120872: 0.296 sec
40r = Search block 639449: 0.114 sec
20r = Search block 79971: 0.047 sec
10r = Search block 20031: 0.021 sec
Cleanup: 0.012 sec
3282352maxresident

40r 4d: sig11
40r 3d: .119 sec
40r 2d: .057 sec
40r 1d: .023 sec

kdtree
inserting 10000000 random vectors... 29.000 sec
80r = range query returned 2680049 items in 1.02700 sec
40r = range query returned 334901 items in 0.16200 sec
20r = range query returned 41902 items in 0.02000 sec
10r = range query returned 5175 items in 0.00300 sec
cleaned up in 2.32100 sec
3169120maxresident

nanoflann
Create Kdtree: 12.735sec
80r = Search: 2680049, 0.512sec
40r = Search: 334901, 0.076sec  ! crazy, similar speed between 20 and 40 unit radius !
20r = Search: 41902, 0.07sec
10r = Search: 5175, 0.001sec
Cleanup: 0.0279999sec
1180688maxresident



On the creation of the neighborhood. Reduce the 'inverse' to a single array instead
of one per dimension. This shortens create time from 16.5s to 12.0s. Reduces memory
by 76mb
    Create neighborhood: 12.069 sec
    Search block 639983: 0.116 sec
    Cleanup: 0.011 sec
    2658256maxresident



Area of a unit sphere is ~.52. Validated by the number of items found
in the rectangular search compared to the spherical search of kdtree and nanoflann



Minimize the code inside the search loop. Gives about 20% performance.
Not digging in the right place, but gets the 40radius test to .1 second.
    Create neighborhood: 12.076 sec
    Search block 639983: 0.09 sec
    Cleanup: 0.010 sec
    2657216maxresident
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