updating exercise 2b

Exercise2b/README.md

@@ -0,0 +1,27 @@
+# Exercise 2b: 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**:  
+ 0. Read `numerical_integration.py` and familiarize yourselves with the code.
+ 1. Update the `main` function so that it calculates the numerical error without
+    any parallelization. You can use a for loop or `map`.
+ 2. Note the execution time for this serial implementation.
+ 3. Implement the parallel version using `multiprocessing.Pool`.
+ 4. Compare the timing for the parallel version with the serial time.
+    What speed-up did you get?
+
+**BONUS TASKS (very optional)**:  
+ 5. Implement a parallel version with threads (using `multiprocessing.pool.ThreadPool`).
+ 6. Time this version, and hypothetize about the result.

Exercise2b/numerical_integration.py

@@ -1,19 +1,5 @@
-# Exercise 2b
+"""Exercise 2b: multiprocessing
-
+"""
-# Here we have a Python function which calculates the integral in two
-# different ways: numerically and analytically.
-#
-# We want to check the precision of the numerical integration as a function of
-# the number of steps (subintervals). 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.
-#
-# Steps:
-# 0. Familizare yourselves with code below.
-# 1. Implement the serial version using a for loop or map
-# 2. Implement the parallel version using multiprocessing.Pool
-# 3. Time both versions
-# 4. What (if any) do you get?
 
 def integrate(f, a, b, n):
     "Perform numerical integration of f in range [a, b], with n steps"
@@ -50,7 +36,3 @@ def main():
 
 if __name__ == '__main__':
     main()
-
-# Bonus steps, very optional:
-# 6. Implement a parallel version with threads (using multiprocessing.pool.ThreadPool).
-# 7. Time this version, and hypothetize about the result.