[OkayPhysicist]

Concurrenceny deals with what can be parallel, because they don't share data dependencies. For example, a map() function is trivially a statement of concurrency: each item needs to have a function applied to it, and assuming pure functions, that can all be done concurrently.

Parallel computing cares about what should be parallel, i.e., actually implementing parallelism. For most programmers, this job can (and probably should) be left to the scheduler, whose job is to translate concurrency into reasonably sane parallelism.

The scheduler comes with overhead, though, that can be avoided with hand-spun parallelism. I like to think about it like manual memory management: for most programs and programmers, using a garbage collector that a memory management expert wrote is easier/better than manually allocating and freeing memory, but there are performance gains to be had if you don't.