Distribution of tasks across multiple CPUs using
This example requires execution on 2 CPUs. It can be run using:
$ mpirun -n 2 python path/to/parallel_tasks.rst
All I’m doing here is illustrating the use of
parallel.map with the simplest example I could come up with. I create a list which will have an integer appended to it – hardly useful, but hopefully demonstrates how a series of data can be mapped onto a function in parallel. In this case, the data is just a list of numbers.
>>> from cogent3.util import parallel >>> passed_indices =  >>> series = list(range(20)) >>> result = parallel.map(passed_indices.append, series) >>> assert passed_indices == list(range(0,20,2)) or passed_indices == list(range(1,20,2))
The result is either the list of even numbers up to (but not including) 20 or the list of odd numbers.