Hi all,
How does the choice of k affect memory and cpu in the kNN plugin?
I am currently studying the trade-off between large/small/super-small dimensional index. I am thinking of going super-small to save on storage and indexing speed. That would, however, require me to always set k to be high (>=100), and leave the rest to the cross-encoder (a fast/efficient one). My only concern is with memory and cpu when I have heavy search load.
I highly appreciate your thoughts on the matter.
Regards