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- #!/usr/bin/env python
- import numpy as np
- import matplotlib.mlab as mlab
- import matplotlib.pyplot as plt
- import matplotlib.patches as mpatches
- # Import data from file
- data_cpu = np.genfromtxt('results/cpu/times.dat', dtype=None, delimiter=' ', names=['name', 'time'])
- data_gpu = np.genfromtxt('results/gpu/times.dat', dtype=None, delimiter=' ', names=['name', 'time'])
- # Generate an array as placeholder for the x axis (we need to pass from a list to an array to take advantage of range)
- x = range(0, 17)
- # Strip away the "opencl/" prefix from all the name
- stripped_names = []
- for elem in data_cpu['name']:
- elem = elem.replace("opencl/", "")
- elem = elem.replace("/ocl", "")
- elem = elem.replace("/OpenCL", "")
- stripped_names.append(elem)
- # Create the bar plot
- plt.bar(x, data_cpu['time'], width=0.5, color='b', align='edge')
- plt.bar(x, data_gpu['time'], width=-0.5, color='r', align='center')
- plt.xticks(x, stripped_names)
- plt.title('Execution time of the various benchmarks expressed in seconds')
- plt.xlabel('Benchmark')
- plt.ylabel('seconds')
- # Add some patches as legend of the colors used for the various benchmarks
- red_patch = mpatches.Patch(color='blue', label='Execution time for cpu')
- blue_patch = mpatches.Patch(color='red', label='Execution time for gpu')
- plt.legend(handles=[blue_patch, red_patch])
- plt.show()
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