Branch Prediction in Python
This assignment is based on one-bit and two-bit branch predictors. To simulate instructions and whether branches will occur or not, the provided methods next_branch_outcome_random
and next_branch_outcome_loop will be used. These methods will simulate a completely random prediction outcome and a set of outcomes that would more closely resemble a series of loops. A return of True represents taking a branch, and a False represents not taking a branch.
The class Predictor represents the predictor. It is best practice to set the initial state to 0.
In [ ]: from random import paretovariate from random import random
def next_branch_outcome_loop(): alpha = 2
outcome = paretovariate(alpha) outcome = outcome > 2
return outcome
def next_branch_outcome_random():
outcome = random() outcome = outcome > 0.5 return outcome
class Predictor:
def init (self):
self.state = 0
def next_predict(self):
"""
Use this method to return the prediction based off of the current state.
"""
raise NotImplementedError("Implement this method")
def incorrect_predict(self):
"""
Use this method to set the next state if an incorrect predict occurred. (self.state = next_state)
"""
raise NotImplementedError("Implement this method")
def correct_predict(self):
"""
Use this method to set the next state if an incorrect predict occurred. (self.state = next_state)””
raise NotImplementedError("Implement this method")
Part 1 - One Bit Predictor
Complete the OneBitPredictor class by implementing the next_predict, incorrect_predict, and correct_predict methods. This instantiation will be used to compute the prediction accu-
racy. Use the next_predict method of the class to predict the next branch state. If the predict is incorrect, use the incorrect_predict method to set the next state. If the predict is correct, use the correct_predict method to set the next state.
In [ ]: class OneBitPredictor(Predictor):
def next_predict(self):
# YOUR CODE HERE
raise NotImplementedError()
def incorrect_predict(self):
# YOUR CODE HERE
raise NotImplementedError()
def correct_predict(self):
# YOUR CODE HERE
raise NotImplementedError()
Part 1.1 - Random Branch Prediction
Use the next_branch_outcome_random method to generate branch outcomes. Use the previously implemented methods to compute a prediction rate.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
Part 1.2 - Loop Branch Prediction
Use the next_branch_outcome_loop method to generate branch outcomes. Use the previously implemented methods to compute a prediction rate.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
Part 2 - Two Bit Predictor
Complete the TwoBitPredictor class by implementing the next_predict, incorrect_predict, and correct_predict methods. This instantiation will be used to compute the prediction accu-
racy. Use the next_predict method of the class to predict the next branch state. If the predict is incorrect, use the incorrect_predict method to set the next state. If the predict is correct, use the correct_predict method to set the next state.
In [ ]: class TwoBitPredictor(Predictor):
def next_predict(self):
# YOUR CODE HERE
raise NotImplementedError()
def incorrect_predict(self):
# YOUR CODE HERE
raise NotImplementedError()
def correct_predict(self):
# YOUR CODE HERE
raise NotImplementedError()
Part 2.1 - Random Branch Prediction
Use the next_branch_outcome_random method to generate branch outcomes. Use the previously implemented methods to compute a prediction rate.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
Part 2.2 - Loop Branch Prediction
Use the next_branch_outcome_loop method to generate branch outcomes. Use the previously implemented methods to compute a prediction rate.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
Part 3 - N-Bit Predictor
Inherit the Predictor class and implement it’s methods just like before. Now, implement an n-bit predictor that represents a higher confidence prediction.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
Part 3.1 - Random Branch Prediction
Use the next_branch_outcome_random method to generate branch outcomes. Use the previously implemented methods to compute a prediction rate.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
Part 3.2 - Loop Branch Prediction
Use the next_branch_outcome_loop method to generate branch outcomes. Use the previously implemented methods to compute a prediction rate.
In [ ]: # YOUR CODE HERE
raise NotImplementedError()
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