you're still releasing resources - so you might not become faster overall but you can compute more in the same time later if necessity arises (althougth that might be somewhat premature but can be good for library code - so it becomes more applicable in different environments)
and there are some rare but tricky scenarios like:
hardware is mobile phone:
app seem to be bottlenecked on arithmetics according to the profiler, so it feels obvious to start optimization there
in reality what happens - hardware has limit on power, so it can't give full power to CPU, GPU and memory all at the same time
since app uses too much memory - it has to redirect power there, also memory emits heat, so CPU becomes throttled
By optimizing memory, everything runs colder -> CPU gets more power, can run sustained higher frequencies - app becomes faster
you're still releasing resources - so you might not become faster overall but you can compute more in the same time later if necessity arises (althougth that might be somewhat premature but can be good for library code - so it becomes more applicable in different environments)
and there are some rare but tricky scenarios like:
hardware is mobile phone: app seem to be bottlenecked on arithmetics according to the profiler, so it feels obvious to start optimization there
in reality what happens - hardware has limit on power, so it can't give full power to CPU, GPU and memory all at the same time
since app uses too much memory - it has to redirect power there, also memory emits heat, so CPU becomes throttled
By optimizing memory, everything runs colder -> CPU gets more power, can run sustained higher frequencies - app becomes faster