Process-based parallelism runs work in several operating-system processes, each with its own interpreter and lock, so that Python code runs on several cores at once. Its serialisation cost is the time spent converting data to bytes and back to move them between processes (pickling, copying through a pipe), which shared memory or files mapped by both processes avoid.
bench_pyscale.py.