I mean, theoretically it's possible. A super basic example would be if the data is known at compile time, it could be auto-parallelized, e.g.

    int buf_size = 10000000;
    auto vec = make_large_array(buf_size);
    for (const auto& val : vec)
    {
        do_expensive_thing(val);
    }

this could clearly be parallelised. In a C++ world that doesn't exist, we can see that it's valid.

If I replace it with int buf_size = 10000000; cin >> buf_size; auto vec = make_large_array(buf_size); for (const auto& val : vec) { do_expensive_thing(val); }

the compiler could generate some code that looks like: if buf_size >= SOME_LARGE_THRESHOLD { DO_IN_PARALLEL } else { DO_SERIAL }

With some background logic for managing threads, etc. In a C++-style world where "control" is important it likely wouldn't fly, but if this was python...

    arr_size = 10000000
    buf = [None] * arr_size
    for x in buf:
        do_expensive_thing(x)

could be parallelised at compile time.