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The `map` operation is a typical concept from the functional programming paradigm.
However, side-effects are a typical example of something that does not fit functional programming well.
As a result, `map` is probably not what you want to use.

As an alternative, you can just use the [`apply`](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.pool.Pool.apply) method of the `Pool` class as follows:
```python
import multiprocessing

pool = multiprocessing.Pool
for f_i in f:
    pool.apply(f_i)
```

Given that your context seems to be IO-bound, it might also be useful to consider thread pools instead of process pools.
Threads are a bit more lightweight, but due to the [GIL](https://wiki.python.org/moin/GlobalInterpreterLock) they are only useful for tasks where the CPU has to wait for IO anyway.
```python
from concurrent.futures import ThreadPoolExecutor

with ProcessPoolExecutor() as pool:
    for f_i in f:
        pool.submit(f_i)
```
FYI: the `concurrent.futures` package also has a ProcessPoolExecutor with the same interface.