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Fix sum example in README
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README.md
21
README.md
@ -101,16 +101,18 @@ Then with your text editor, open the file `sequential_sum.bend`, copy the code b
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```py
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# Defines the function Sum with two parameters: start and target
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def Sum(start, target):
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# If the value of start is the same as target, returns start
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if start == target:
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# If the value of start is the same as target, returns start.
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return start
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# If start is not equal to target, recursively call Sum with start incremented by 1, and add the result to start
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else:
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# If start is not equal to target, recursively call Sum with
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# start incremented by 1, and add the result to start.
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return start + Sum(start + 1, target)
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def main():
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# This translates to (1 + (2 + (3 + (...... + (79999999 + 80000000)))))
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return Sum(1, 80000000)
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# This translates to (1 + (2 + (3 + (...... + (999999 + 1000000)))))
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# Note that this will overflow the maximum value of a number in Bend
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return Sum(1, 1_000_000)
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```
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##### Running the file
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@ -143,20 +145,21 @@ Then with your text editor, open the file `parallel_sum.bend`, copy the code bel
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```py
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# Defines the function Sum with two parameters: start and target
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def Sum(start, target):
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# If the value of start is the same as target, returns start
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if start == target:
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# If the value of start is the same as target, returns start.
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return start
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# If start is not equal to target, calculate the midpoint (half), then recursively call Sum on both halves
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else:
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# If start is not equal to target, calculate the midpoint (half),
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# then recursively call Sum on both halves.
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half = (start + target) / 2
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left = Sum(start, half) # (Start -> Half)
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right = Sum(half + 1, target)
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return left + right
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# Main function to demonstrate the parallelizable sum from 1 to 80000000
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# A parallelizable sum of numbers from 1 to 1000000
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def main():
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# This translates to ((1 + 2) + (3 + 4)+ ... (79999999 + 80000000)...)
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return Sum(1, 80000000)
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# This translates to (((1 + 2) + (3 + 4)) + ... (999999 + 1000000)...)
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return Sum(1, 1_000_000)
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```
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In this example, the (3 + 4) sum does not depend on the (1 + 2), meaning that it can run in parallel because both computations can happen at the same time.
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