aboutsummaryrefslogtreecommitdiffstats
path: root/benchtests/scripts/compare_bench.py
blob: 88e8911d812f463aeadd041f29ab8b7cbedd7e89 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
#!/usr/bin/python
# Copyright (C) 2015-2018 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.
    """
    d = abs(tl2[par] - tl1[par]) * 100 / tl1[str(par)]
    if d > threshold:
        if tl1[par] > tl2[par]:
            ind = '+++'
        else:
            ind = '---'
        print('%s %s(%s)[%s]: (%.2lf%%) from %g to %g' %
                (ind, func, var, par, d, tl1[par], tl2[par]))


def compare_runs(pts1, pts2, threshold):
    """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)
            do_compare(func, var, tl1, tl2, 'min', threshold)
            do_compare(func, var, tl1, tl2, 'mean', 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():
                    return

            # 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():
                print('Skipping graph for %s(%s)' % (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
            print('Writing out %s' % filename)
            pylab.savefig(filename)

def main(bench1, bench2, schema, threshold):
    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)


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, help='Only print those with equal or higher threshold (default: %(default)s)')

    args = parser.parse_args()

    main(args.bench1, args.bench2, args.schema, args.threshold)