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map_example_codealong.py | ||
numerical_integration.py | ||
numerical_integration_solution.py | ||
README.md |
Exercise B: multiprocessing and map
Objective: introduce map
and Pool.map
.
In the numerical_integration.py
file, we give Python code that calculates
the integral of a function in two different ways: numerically and analytically.
The given functions are integrate
(numerical integration), f
(the function
to integrate), and F
(the analytical integral).
We want to check the precision of the numerical integration as a function of the number of steps in the domain. To do this, we calculate and print the relative differences between the analytic result and the numerical result for different values of the number of steps.
TASKS:
- Read
numerical_integration.py
and familiarize yourselves with the code. - Update the
main
function so that it calculates the numerical error without any parallelization. You can use a for loop ormap
. - Note the execution time for this serial implementation.
- Implement the parallel version using
multiprocessing.Pool
. - Compare the timing for the parallel version with the serial time. What speed-up did you get?
BONUS TASKS (very optional):
- Implement a parallel version with threads (using
multiprocessing.pool.ThreadPool
). - Time this version, and hypothetize about the result.