Using Amdahl’s Law, calculate the speedup gain of an application that has a 60 percent parallel component for (a) two processing
1 answer:
Answer:
a) Speedup gain is 1.428 times.
b) Speedup gain is 1.81 times.
Explanation:
in order to calculate the speedup again of an application that has a 60 percent parallel component using Anklahls Law is speedup which state that:
Where S is the portion of the application that must be performed serially, and N is the number of processing cores.
(a) For N = 2 processing cores, and a 60%, then S = 40% or 0.4
Thus, the speedup is:
Speedup gain is 1.428 times.
(b) For N = 4 processing cores and a 60%, then S = 40% or 0.4
Thus, the speedup is:
Speedup gain is 1.81 times.
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Answer:
- from matplotlib import pyplot as plt
- with open("text.txt") as file:
- data = file.readlines()
- category = []
- amount = []
- for row in data:
- values = row.split(" ")
- category.append(values[0])
- amount.append(float(values[1]))
- figure = plt.figure()
- ax = figure.add_axes([0,0,1,1])
- ax.axis('equal')
- ax.pie(amount, labels = category, autopct='%1.2f%%')
- plt.show()
Explanation:
Firstly, we need to import matplotlib library (Line 1).
Next, open a file stream and use readlines method to read the data from the text file (Line 4). Presume the data read from the text files are as follows:
Rent 450
Gas 150
Food 500
Clothing 120
Car 600
Create two lists, category and amount (Line 5-6). Use a for loop to traverse through the read data and use split method to break each row of data into two individual items. The first item is added to category list whereas the second item is added to amount list (Line 7 - 10).
Next, create a plot figure and then add the axes (Line 12 - 13). We can use the pie method to generate a pie chart (Line 15) by setting the amount list as first argument and category list as value of labels attributes. The output pie chart can be found in the attachment.
