update exerciseC
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3 changed files with 65 additions and 75 deletions
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@ -1,67 +1,53 @@
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import sys
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import collections
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import os
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.patheffects as PathEffects
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dts = collections.defaultdict(dict)
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N_processes = 5
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N_threads = 5
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for fname in sys.argv[1:]:
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values = open(fname).read().split()
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n1 = int(values[0])
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n2 = int(values[1])
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# Load measured timings
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times = np.empty((N_processes, N_threads))
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for fname in os.listdir('timings'):
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values = open(f'timings/{fname}').read().split()
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n_processes = int(values[0])
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n_threads = int(values[1])
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dt = float(values[2])
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times[n_processes-1][n_threads-1] = dt
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print(times)
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dts[n1][n2] = dt
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""" Plot measured time"""
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fig_time, axs_time = plt.subplots()
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im = axs_time.imshow(times.T, origin='lower')
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axs_time.set_title('Computation time')
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fig_time.colorbar(im, ax=axs_time, label='Measured computation time (s)')
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print(dts)
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N1 = max(dts)
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N2 = max(max(v) for v in dts.values())
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""" Plot speedup """
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workers = np.arange(N_processes + 1)[:, None] * np.arange(N_threads + 1)
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speedup = times[0, 0] / times
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print(N1, N2)
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fig_speedup, axs_speedup = plt.subplots()
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im = axs_speedup.imshow(speedup.T, origin='lower')
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axs_speedup.set_title('Computation speed-up')
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fig_speedup.colorbar(im, ax=axs_speedup, label='Speed-up')
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x = np.empty((N1 + 1, N2 + 1))
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for n1, values in dts.items():
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for n2, v in values.items():
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x[n1, n2] = v
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# Set same style for both plots
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for axs, data in zip([axs_time, axs_speedup], [times, speedup]):
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axs.set_xlabel('# processes')
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axs.set_ylabel('# threads')
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axs.set_xticks(np.arange(N_processes))
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axs.set_xticklabels(np.arange(N_processes)+1)
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axs.set_yticks(np.arange(N_threads))
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axs.set_yticklabels(np.arange(N_threads)+1)
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x[:, 0] = np.nan
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x[0, :] = np.nan
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for i in range(N_processes):
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for j in range(N_threads):
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txt = axs.text(i, j, f'{data[i, j]:.2f}', fontsize=10, color='w',
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ha='center', va='center', fontweight='bold')
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txt.set_path_effects([PathEffects.withStroke(linewidth=0.5, foreground='k')])
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axs.spines[['right', 'top']].set_visible(False)
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print(x)
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# Save plots
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fig_time.savefig('time.png', dpi=300)
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fig_speedup.savefig('speedup.png', dpi=300)
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from matplotlib import pyplot
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fig, axes = pyplot.subplots()
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im = axes.imshow(x, origin='lower')
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axes.set_ylabel('# processes')
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axes.set_xlabel('# threads')
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axes.spines[['right', 'top']].set_visible(False)
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axes.set_title('time')
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fig.colorbar(im, ax=axes, label='s')
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fig_small, axes = pyplot.subplots()
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im = axes.imshow(x[:5, :5], origin='lower')
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axes.set_ylabel('# processes')
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axes.set_xlabel('# threads')
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axes.spines[['right', 'top']].set_visible(False)
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axes.set_title('time')
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fig_small.colorbar(im, ax=axes, label='s')
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workers = np.arange(N1 + 1)[:, None] * np.arange(N2 + 1)
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speedup = x[1,1] / x
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speedup[:, 0] = np.nan
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speedup[0, :] = np.nan
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figs, axes = pyplot.subplots()
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im = axes.imshow(speedup, origin='lower')
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axes.set_ylabel('# processes')
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axes.set_xlabel('# threads')
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axes.spines[['right', 'top']].set_visible(False)
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axes.set_title('speedup')
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figs.colorbar(im, ax=axes, label='s')
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fig.savefig('time.svg')
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fig_small.savefig('time_inset.svg')
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figs.savefig('speedup.svg')
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pyplot.show()
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