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.
I just recently updated a database call to return the last 7 days of data instead of all data from all time. It went from taking 30+seconds to around 2-4 seconds. Still a long way to go to make it “good” but at least it’s not timing out now.
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I just recently updated a database call to return the last 7 days of data instead of all data from all time. It went from taking 30+seconds to around 2-4 seconds. Still a long way to go to make it “good” but at least it’s not timing out now.