thesis version
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2
rtbenchmarks/.gitignore
vendored
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2
rtbenchmarks/.gitignore
vendored
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data_basic/
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data_imgpro/
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113
rtbenchmarks/plot_basic
Executable file
113
rtbenchmarks/plot_basic
Executable file
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import os, sys
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sys.path.append(os.path.abspath(os.path.dirname(os.path.abspath(__file__))+"/../scripts"))
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import fileinput
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import numpy as np
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import matplotlib as mpl
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show = len(sys.argv) > 1 and sys.argv[1] == 'show'
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if not show:
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mpl.use('pgf')
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import matplotlib.pyplot as plt
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import matplotlib.lines as lines
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from common import set_size, config_plt, get_colors, fix_log_rects
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config_plt()
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def loadData(fn):
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content = []
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with open(fn) as f:
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content = f.readlines()
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values = {}
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for line in content:
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n, method, sample, ncores, strtime = [x for x in line.split(':')]
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time = float(strtime)
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if method != "seq":
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time = time/float(ncores)
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if not n in values:
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values[n] = []
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values[n].append(time);
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return values
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def figSize(title, xlabel, xticks, output, datasrcs, error=False):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"temps (s)")
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plt.xticks(xticks)
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plt.xscale('log')
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plt.yscale('log')
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nd = len(datasrcs)
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width = 3.5
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pos = .5-.5*nd
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for f, label in datasrcs:
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values = loadData(f)
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barcolor, errcolor = get_colors(['seq', 'omp', 'gen_omp', 'gen_thread'], label)
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for k, a in values.items():
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x = int(k)
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m = np.mean(a)
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s = 2.5758 * np.std(a) / np.sqrt(len(a)) # confiance 99 %
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x = x * ((20+width)/(20-width))**pos
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p = np.log10(x)
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lwidth = width * 10**(p-1)
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bar = plt.bar(x, m, width=lwidth, color=barcolor, label=label)
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fix_log_rects(bar, 1e-4)
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if error:
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plt.errorbar(x, m, s, elinewidth=1.5, capsize=2, ecolor=errcolor)
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label=''
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pos = pos + 1
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plt.legend(bbox_to_anchor=(.38, 1))
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fig.set_size_inches(set_size(455.24408, .8))
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if not show:
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plt.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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# script
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plts = []
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plt = figSize(u"", u"taille des données", [1e2, 1e3, 1e4, 1e5, 1e6, 1e7],
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"plots/rt_seq.pdf", [
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['data_basic/rt_seq_seq', 'seq'],
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['data_basic/rt_seq_gen_omp', 'gen_omp'],
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['data_basic/rt_seq_gen_thread', 'gen_thread'],
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],
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error=True
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)
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plts.append(plt)
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for cores in [1, 2, 4, 6, 8, 10, 12, 14, 16, 18]:
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plt = figSize(u"", u"taille des données", [1e2, 1e3, 1e4, 1e5, 1e6, 1e7],
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"plots/rt_par_"+str(cores)+".pdf", [
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['data_basic/rt_size_'+str(cores)+'_seq', 'seq'],
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['data_basic/rt_size_'+str(cores)+'_omp', 'omp'],
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['data_basic/rt_size_'+str(cores)+'_gen_omp', 'gen_omp'],
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['data_basic/rt_size_'+str(cores)+'_gen_thread', 'gen_thread'],
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],
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error=True
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)
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plts.append(plt)
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if show:
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for plt in plts:
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plt.show()
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147
rtbenchmarks/plot_imgpro
Executable file
147
rtbenchmarks/plot_imgpro
Executable file
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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import os, sys
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sys.path.append(os.path.abspath(os.path.dirname(os.path.abspath(__file__))+"/../scripts"))
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import fileinput
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import numpy as np
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import matplotlib as mpl
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show = len(sys.argv) > 1 and sys.argv[1] == 'show'
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if not show:
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mpl.use('pgf')
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import matplotlib.pyplot as plt
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import matplotlib.lines as lines
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from common import set_size, config_plt, get_colors
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config_plt()
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def loadData(fn):
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content = []
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with open(fn) as f:
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content = f.readlines()
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values = {}
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for line in content:
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method, ncores, strtime = [x for x in line.split(':')]
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time = float(strtime)
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if method != "seq":
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time = time/float(ncores)
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if not ncores in values:
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values[ncores] = []
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values[ncores].append(time);
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return values
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def figCores(title, xlabel, xticks, output, datasrcs, error=False):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"temps (s)")
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plt.xticks(xticks)
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nd = len(datasrcs)
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width = .4
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pos = .5-.5*nd
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for f, label in datasrcs:
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values = loadData(f)
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barcolor, errcolor = get_colors(['seq', 'omp', 'gen_omp', 'gen_thread'], label)
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if "1" in values:
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values.pop("1")
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for k, a in values.items():
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x = int(k)
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m = np.mean(a)
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s = 2.5758 * np.std(a) / np.sqrt(len(a)) # confiance 99 %
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x = x + pos*width
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plt.bar(x, m, width=width, color=barcolor, label=label)
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if error:
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plt.errorbar(x, m, s, elinewidth=.8, capsize=1, ecolor=errcolor)
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label=''
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pos = pos + 1
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plt.legend(bbox_to_anchor=(1, 1))
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fig.set_size_inches(set_size(455.24408, .8))
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if not show:
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plt.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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def figSpeedUp(title, xlabel, xticks, output, basetime, datasrcs):
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fig = plt.figure()
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plt.title(title)
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plt.xlabel(xlabel)
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plt.ylabel(u"accélération")
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plt.xticks(xticks)
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nd = len(datasrcs)
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width = .4
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pos = .5-.5*nd
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for f, label in datasrcs:
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values = loadData(f)
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barcolor, errcolor = get_colors(['seq', 'omp', 'gen_omp', 'gen_thread'], label)
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if "1" in values:
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values.pop("1")
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for k, a in values.items():
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x = int(k)
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m = basetime/np.mean(a)
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x = x + pos*width
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plt.bar(x, m, width=width, color=barcolor, label=label)
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label=''
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pos = pos + 1
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plt.legend(bbox_to_anchor=(0.38, 1))
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fig.set_size_inches(set_size(455.24408, .8))
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if not show:
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plt.savefig(output, format='pdf', bbox_inches='tight')
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return plt
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# script
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values = loadData('data_imgpro/rt_cores_seq')
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basetime = np.mean(values["1"])
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plts = []
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plt = figCores(u"", u"nombre de cœurs", [2, 4, 6, 8, 10, 12, 14, 16, 18],
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"plots/rt_cores.pdf", [
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# ['data_imgpro/rt_cores_seq', 'seq'],
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['data_imgpro/rt_cores_gen_omp', 'omp'],
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['data_imgpro/rt_cores_gen_omp', 'gen_omp'],
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['data_imgpro/rt_cores_gen_thread', 'gen_thread'],
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],
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error=False
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)
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plts.append(plt)
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plt = figSpeedUp(u"", u"nombre de cœurs", [2, 4, 6, 8, 10, 12, 14, 16, 18],
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"plots/rt_speedup.pdf", basetime, [
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['data_imgpro/rt_cores_gen_omp', 'omp'],
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['data_imgpro/rt_cores_gen_omp', 'gen_omp'],
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['data_imgpro/rt_cores_gen_thread', 'gen_thread'],
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]
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)
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plts.append(plt)
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if show:
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for plt in plts:
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plt.show()
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79
rtbenchmarks/run_rt_basic
Executable file
79
rtbenchmarks/run_rt_basic
Executable file
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#!/bin/bash
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binary=./release/benchmarks/basic
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preload="LD_PRELOAD=~bachelet/local/kephren/lib64/libstdc++.so.6"
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repeat=20
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outdir="rtbenchmarks/data_basic"
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[ -x "${binary}" ] || exit 1
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run() {
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coreset=$1
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size=$2
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method=$3
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sample=$4
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ncores=$5
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prefix="${size}:${method}:${sample}:${ncores}"
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for i in $(seq ${repeat}); do
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t=$(eval "${preload} taskset -c ${coreset} ${binary} ${size} ${method} ${sample} ${ncores}"|cut -d' ' -f2)
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echo "${prefix}:${t}"
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done
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}
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benchSeq() {
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sizes=(100 1000 10000 100000 1000000 10000000)
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coreset=0
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sample=0 # seq
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ncores=1
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echo "---- benchSeq ----"
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for method in seq omp gen_omp gen_thread; do
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echo "==== ${method}"
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for size in ${sizes[@]}; do
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run "${coreset}" "${size}" "${method}" "${sample}" "${ncores}"
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done|tee "${outdir}/rt_seq_${method}"
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done
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}
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benchCores() {
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cores=(1 2 4 6 8 10 12 14 16 18)
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size=10000000
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sample=1 # par
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echo "---- benchCores ----"
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for method in omp gen_omp gen_thread; do
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echo "==== ${method}"
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for ncores in ${cores[@]}; do
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maxcore=$((ncores*4 - 1))
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coreset="$(seq -s, 0 4 ${maxcore})"
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run "${coreset}" "${size}" "${method}" "${sample}" "${ncores}"
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done|tee "${outdir}/rt_cores_${method}"
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done
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}
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benchSize() {
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sizes=(100 1000 10000 100000 1000000 10000000)
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ncores=$1
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maxcore=$((ncores*4 - 1))
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coreset="$(seq -s, 0 4 ${maxcores})"
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sample=1 # par
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echo "---- benchSize (ncores: ${ncores}) ----"
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for method in seq omp gen_omp gen_thread; do
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echo "==== ${method}"
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for size in ${sizes[@]}; do
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run "${coreset}" "${size}" "${method}" "${sample}" "${ncores}"
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done|tee "${outdir}/rt_size_${ncores}_${method}"
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done
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}
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eval "$*"
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38
rtbenchmarks/run_rt_imgpro
Executable file
38
rtbenchmarks/run_rt_imgpro
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#!/bin/bash
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binary=./release/benchmarks/imgpro
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preload="LD_PRELOAD=~bachelet/local/kephren/lib64/libstdc++.so.6"
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repeat=20
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outdir="rtbenchmarks/data_imgpro"
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[ -x "${binary}" ] || exit 1
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run() {
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coreset=$1
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method=$2
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ncores=$3
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prefix="${method}:${ncores}"
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for i in $(seq ${repeat}); do
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t=$(eval "${preload} taskset -c ${coreset} ${binary} ${size} ${method} ${sample} ${ncores}"|cut -d' ' -f2)
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echo "${prefix}:${t}"
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done
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}
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benchCores() {
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cores=(1 2 4 6 8 10 12 14 16 18)
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echo "---- benchCores ----"
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for method in seq omp gen_omp gen_thread; do
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echo "==== ${method}"
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for ncores in ${cores[@]}; do
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maxcore=$((ncores*4 - 1))
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coreset="$(seq -s, 0 4 ${maxcore})"
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run "${coreset}" "${method}" "${ncores}"
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done|tee "${outdir}/rt_cores_${method}"
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done
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}
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eval "$*"
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