update exerciseC
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morales-gregorio
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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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@ -3,17 +3,11 @@ import sys
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from multiprocessing import Pool as ProcessPool
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import time
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def process_image(fname):
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n_threads = os.getenv('OMP_NUM_THREADS', '(unset)')
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print(f"Worker {fname=} OMP_NUM_THREADS={n_threads}")
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def process_image(input_tuple):
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# An image is an array with width, height and three (RGB) color channels
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# (Sometimes there is a transparency channel too: RGBA)
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im = Image.open(fname)
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try:
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A = np.median(im, axis=2)[::4, ::4]
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except:
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A = np.array(im)[::4, ::4]
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fname, A = input_tuple
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n_threads = os.getenv('OMP_NUM_THREADS', '(unset)')
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print(f"Worker {fname=} OMP_NUM_THREADS={n_threads}", flush=True)
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# Decompose image
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U, S, Vh = np.linalg.svd(A)
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@ -36,10 +30,10 @@ if __name__ == '__main__':
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fnames = sys.argv[3:]
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# Check that the output folders exist, or create them if needed
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if not os.path.isdir('processed_images'): os.mkdir('processed_images')
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if not os.path.isdir('timings'): os.mkdir('timings')
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if not os.path.isdir('processed_images'): os.mkdir('processed_images')
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print(f"Controller with {n_processes} processes and {n_threads} threads / worker")
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print(f"Controller with {n_processes} processes and {n_threads} threads / worker", flush=True)
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# The environment that is set in the parent is inherited by child workers,
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# we need to set the variable before numpy is imported!
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@ -50,19 +44,28 @@ if __name__ == '__main__':
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import numpy as np
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from PIL import Image
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# Time the execution
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# I/O Load the images
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image_arrays = []
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for fname in fnames:
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im = Image.open(fname)
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A = np.array(im)
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image_arrays.append((fname, A))
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# Time the execution of the pool map
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start_time = time.time()
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with ProcessPool(n_processes) as p:
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new_images = p.map(process_image, fnames)
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new_images = p.map(process_image, image_arrays)
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elapsed_time = time.time() - start_time
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# I/O save the processed images
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for im, fname in zip(new_images, fnames):
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im = Image.fromarray(im)
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im.save(fname.replace('images', 'processed_images'))
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print(f'{n_processes} processes and {n_threads} threads and {len(fnames)} jobs: {elapsed_time}')
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print(f'{n_processes} processes and {n_threads} threads and {len(fnames)} jobs: {elapsed_time}\n',
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flush=True)
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# IO: Save the timing to a unique txt file
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# I/O: Save the timing to a unique txt file
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filename = f'timings/{n_processes:02}_processes_{n_threads:02}_threads.txt'
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with open(filename, 'w') as file:
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file.write(f'{n_processes} {n_threads} {elapsed_time:.6f}')
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@ -1,7 +1,8 @@
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# This is bash, it executes the python script multiple times
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for i in {1..10}
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# This is bash
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# It runs the python script multiple times with different arguments
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for i in {1..5} # Number of processes
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do
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for j in {1..10}
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for j in {1..5} # Number of threads
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do
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python process_images.py $i $j images/*
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done
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