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#!/usr/bin/python
# Copyright (C) 2015-2019 Free Software Foundation, Inc.
# This file is part of the GNU C Library.
#
# The GNU C Library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Lesser General Public
# License as published by the Free Software Foundation; either
# version 2.1 of the License, or (at your option) any later version.
#
# The GNU C Library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public
# License along with the GNU C Library; if not, see
# <http://www.gnu.org/licenses/>.
"""Compare two benchmark results
Given two benchmark result files and a threshold, this script compares the
benchmark results and flags differences in performance beyond a given
threshold.
"""
import sys
import os
import pylab
import import_bench as bench
import argparse
def do_compare(func, var, tl1, tl2, par, threshold):
"""Compare one of the aggregate measurements
Helper function to compare one of the aggregate measurements of a function
variant.
Args:
func: Function name
var: Function variant name
tl1: The first timings list
tl2: The second timings list
par: The aggregate to measure
threshold: The threshold for differences, beyond which the script should
print a warning.
"""
try:
v1 = tl1[str(par)]
v2 = tl2[str(par)]
d = abs(v2 - v1) * 100 / v1
except KeyError:
sys.stderr.write('%s(%s)[%s]: stat does not exist\n' % (func, var, par))
return
except ZeroDivisionError:
return
if d > threshold:
if v1 > v2:
ind = '+++'
else:
ind = '---'
print('%s %s(%s)[%s]: (%.2lf%%) from %g to %g' %
(ind, func, var, par, d, v1, v2))
def compare_runs(pts1, pts2, threshold, stats):
"""Compare two benchmark runs
Args:
pts1: Timing data from first machine
pts2: Timing data from second machine
"""
# XXX We assume that the two benchmarks have identical functions and
# variants. We cannot compare two benchmarks that may have different
# functions or variants. Maybe that is something for the future.
for func in pts1['functions'].keys():
for var in pts1['functions'][func].keys():
tl1 = pts1['functions'][func][var]
tl2 = pts2['functions'][func][var]
# Compare the consolidated numbers
# do_compare(func, var, tl1, tl2, 'max', threshold)
for stat in stats.split():
do_compare(func, var, tl1, tl2, stat, threshold)
# Skip over to the next variant or function if there is no detailed
# timing info for the function variant.
if 'timings' not in pts1['functions'][func][var].keys() or \
'timings' not in pts2['functions'][func][var].keys():
continue
# If two lists do not have the same length then it is likely that
# the performance characteristics of the function have changed.
# XXX: It is also likely that there was some measurement that
# strayed outside the usual range. Such ouiers should not
# happen on an idle machine with identical hardware and
# configuration, but ideal environments are hard to come by.
if len(tl1['timings']) != len(tl2['timings']):
print('* %s(%s): Timing characteristics changed' %
(func, var))
print('\tBefore: [%s]' %
', '.join([str(x) for x in tl1['timings']]))
print('\tAfter: [%s]' %
', '.join([str(x) for x in tl2['timings']]))
continue
# Collect numbers whose differences cross the threshold we have
# set.
issues = [(x, y) for x, y in zip(tl1['timings'], tl2['timings']) \
if abs(y - x) * 100 / x > threshold]
# Now print them.
for t1, t2 in issues:
d = abs(t2 - t1) * 100 / t1
if t2 > t1:
ind = '-'
else:
ind = '+'
print("%s %s(%s): (%.2lf%%) from %g to %g" %
(ind, func, var, d, t1, t2))
def plot_graphs(bench1, bench2):
"""Plot graphs for functions
Make scatter plots for the functions and their variants.
Args:
bench1: Set of points from the first machine
bench2: Set of points from the second machine.
"""
for func in bench1['functions'].keys():
for var in bench1['functions'][func].keys():
# No point trying to print a graph if there are no detailed
# timings.
if u'timings' not in bench1['functions'][func][var].keys():
sys.stderr.write('Skipping graph for %s(%s)\n' % (func, var))
continue
pylab.clf()
pylab.ylabel('Time (cycles)')
# First set of points
length = len(bench1['functions'][func][var]['timings'])
X = [float(x) for x in range(length)]
lines = pylab.scatter(X, bench1['functions'][func][var]['timings'],
1.5 + 100 / length)
pylab.setp(lines, 'color', 'r')
# Second set of points
length = len(bench2['functions'][func][var]['timings'])
X = [float(x) for x in range(length)]
lines = pylab.scatter(X, bench2['functions'][func][var]['timings'],
1.5 + 100 / length)
pylab.setp(lines, 'color', 'g')
if var:
filename = "%s-%s.png" % (func, var)
else:
filename = "%s.png" % func
sys.stderr.write('Writing out %s' % filename)
pylab.savefig(filename)
def main(bench1, bench2, schema, threshold, stats):
bench1 = bench.parse_bench(bench1, schema)
bench2 = bench.parse_bench(bench2, schema)
plot_graphs(bench1, bench2)
bench.compress_timings(bench1)
bench.compress_timings(bench2)
compare_runs(bench1, bench2, threshold, stats)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Take two benchmark and compare their timings.')
# Required parameters
parser.add_argument('bench1', help='First bench to compare')
parser.add_argument('bench2', help='Second bench to compare')
# Optional parameters
parser.add_argument('--schema',
default=os.path.join(os.path.dirname(os.path.realpath(__file__)),'benchout.schema.json'),
help='JSON file to validate source/dest files (default: %(default)s)')
parser.add_argument('--threshold', default=10.0, type=float, help='Only print those with equal or higher threshold (default: %(default)s)')
parser.add_argument('--stats', default='min mean', type=str, help='Only consider values from the statistics specified as a space separated list (default: %(default)s)')
args = parser.parse_args()
main(args.bench1, args.bench2, args.schema, args.threshold, args.stats)
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