Got myself a few months ago into the optimization rabbit hole as I had a slow quant finance library to take care of, and for now my most successful optimizations are using local memory allocators (see my C++ post, I also played with mimalloc which helped but custom local memory allocators are even better) and rethinking class layouts in a more “data-oriented” way (mostly going from array-of-structs to struct-of-arrays layouts whenever it’s more advantageous to do so, see for example this talk).
What are some of your preferred optimizations that yielded sizeable gains in speed and/or memory usage? I realize that many optimizations aren’t necessarily specific to any given language so I’m asking in !programming@programming.dev.
Noticed that Hibernate session (DB ORM session) was leaking to Jackson (JSON marshalling), potentially causing infinite n+1 problem. Changing a few lines of code to lazy loading and fixing the session leak reduced our daily data transfer from DB from 5.6Gb to 170Mb.
Not sure if this was the biggest optimisation, but definitely the dumbest issue.