A Concise Introduction to Programming in Python

Chapter 27

Parallel Programming

Real-world problems often take too long to solve on a single processor because

of their size or computational demands. Parallel processing is a family of

mechanisms for coordinating multiple tasks that work in parallel to solve a

single problem. In this chapter, we explore the use of parallel programming

with the example from Chapter 10.

Listing 27.1: Monte Carlo Integration (Parallel Version)

1 # montecarlo.py

2

3 from random import uniform

4 from math import exp

5 import multiprocessing

6

7 def count_hits(f, a, b, m, n):

8 hits = 0

9 for i in range(n):

10 x = uniform(a, b)

11 y = uniform(0, m)

12 if y <= f(x):

13 hits += 1

14