def run_benchmark(size):
pred = bpredict.Local2BitPredictor(size)
runner = bpredict.ExternalRunner(pred, benchmark, args=args)
runner.run()
predicted = runner.stats[0].find('condPredicted')[0].values[0]
incorrect = runner.stats[0].find('condIncorrect')[0].values[0]
return (incorrect / predicted)
def run_test(runner):
start = time.time()
runner.run()
predicted = runner.stats[0].find('condPredicted')[0].values[0]
incorrect = runner.stats[0].find('condIncorrect')[0].values[0]
print(' misprediction rate: %f' % (incorrect / predicted))
print(' runtime: %f' % (time.time() - start))
# Run with the external TwoLevelAdaptive predictor (7168 bit)
pred = bpredict.TwoLevelAdaptiveTrainingPredictor(512, 10)
runner = bpredict.ExternalRunner(pred, benchmark, args)
print('External TwoLevelAdaptiveTrainingPredictor:')
run_test(runner)
# Run with the external Local2Bit predictor (8192 bit)
pred = bpredict.Local2BitPredictor(4096)
runner = bpredict.ExternalRunner(pred, benchmark, args)
print('External Local2BitPredictor:')
run_test(runner)
# Run with the perceptron predictor (8064 bit)
pred = bpredict.PerceptronPredictor(256, 36, 48, 64)
runner = bpredict.ExternalRunner(pred, benchmark, args)
print('External PerceptronPredictor:')
run_test(runner)