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Python Language Using the multiprocessing module to parallelise tasks


Example

import multiprocessing

def fib(n):
    """computing the Fibonacci in an inefficient way
    was chosen to slow down the CPU."""
    if n <= 2:
        return 1
    else:
        return fib(n-1)+fib(n-2) 
p = multiprocessing.Pool() 
print(p.map(fib,[38,37,36,35,34,33]))

# Out: [39088169, 24157817, 14930352, 9227465, 5702887, 3524578]

As the execution of each call to fib happens in parallel, the time of execution of the full example is 1.8× faster than if done in a sequential way on a dual processor.

Python 2.2+