zlacker

There's many algorithms with a space vs time tradeoff. But what works best, depends a lot on the time/energy cost of re-computing something, vs the storage/bandwidth cost of caching results.

Expensive calculation, cheap storage → caching results helps.

Limited bandwidth / 'expensive' storage, simple calculation (see: today's hyper-fast CPU+L1 cache combo's) → better to re-compute some things on the fly as needed.

I suspect there's a lot of existing software (components) out there designed along the "save CPU cycles, burn storage" path, where in modern reality a "save storage, CPU cycles are cheap" would be more effective. CPU speeds have grown way way faster than main memory bandwidth (or even size?) over the last decades.

For a datacenter, supercomputer, embedded system, PC or some end-user's phone, the metrics will be different. But same principle applies.