forked from mirror/qemu
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
127 lines
3.7 KiB
Python
127 lines
3.7 KiB
Python
#!/usr/bin/env python3
|
|
#
|
|
# Simple benchmarking framework
|
|
#
|
|
# Copyright (c) 2019 Virtuozzo International GmbH.
|
|
#
|
|
# This program is free software; you can redistribute it and/or modify
|
|
# it under the terms of the GNU General Public License as published by
|
|
# the Free Software Foundation; either version 2 of the License, or
|
|
# (at your option) any later version.
|
|
#
|
|
# This program 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 General Public License for more details.
|
|
#
|
|
# You should have received a copy of the GNU General Public License
|
|
# along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
#
|
|
|
|
import math
|
|
import tabulate
|
|
|
|
# We want leading whitespace for difference row cells (see below)
|
|
tabulate.PRESERVE_WHITESPACE = True
|
|
|
|
|
|
def format_value(x, stdev):
|
|
stdev_pr = stdev / x * 100
|
|
if stdev_pr < 1.5:
|
|
# don't care too much
|
|
return f'{x:.2g}'
|
|
else:
|
|
return f'{x:.2g} ± {math.ceil(stdev_pr)}%'
|
|
|
|
|
|
def result_to_text(result):
|
|
"""Return text representation of bench_one() returned dict."""
|
|
if 'average' in result:
|
|
s = format_value(result['average'], result['stdev'])
|
|
if 'n-failed' in result:
|
|
s += '\n({} failed)'.format(result['n-failed'])
|
|
return s
|
|
else:
|
|
return 'FAILED'
|
|
|
|
|
|
def results_dimension(results):
|
|
dim = None
|
|
for case in results['cases']:
|
|
for env in results['envs']:
|
|
res = results['tab'][case['id']][env['id']]
|
|
if dim is None:
|
|
dim = res['dimension']
|
|
else:
|
|
assert dim == res['dimension']
|
|
|
|
assert dim in ('iops', 'seconds')
|
|
|
|
return dim
|
|
|
|
|
|
def results_to_text(results):
|
|
"""Return text representation of bench() returned dict."""
|
|
n_columns = len(results['envs'])
|
|
named_columns = n_columns > 2
|
|
dim = results_dimension(results)
|
|
tab = []
|
|
|
|
if named_columns:
|
|
# Environment columns are named A, B, ...
|
|
tab.append([''] + [chr(ord('A') + i) for i in range(n_columns)])
|
|
|
|
tab.append([''] + [c['id'] for c in results['envs']])
|
|
|
|
for case in results['cases']:
|
|
row = [case['id']]
|
|
case_results = results['tab'][case['id']]
|
|
for env in results['envs']:
|
|
res = case_results[env['id']]
|
|
row.append(result_to_text(res))
|
|
tab.append(row)
|
|
|
|
# Add row of difference between columns. For each column starting from
|
|
# B we calculate difference with all previous columns.
|
|
row = ['', ''] # case name and first column
|
|
for i in range(1, n_columns):
|
|
cell = ''
|
|
env = results['envs'][i]
|
|
res = case_results[env['id']]
|
|
|
|
if 'average' not in res:
|
|
# Failed result
|
|
row.append(cell)
|
|
continue
|
|
|
|
for j in range(0, i):
|
|
env_j = results['envs'][j]
|
|
res_j = case_results[env_j['id']]
|
|
cell += ' '
|
|
|
|
if 'average' not in res_j:
|
|
# Failed result
|
|
cell += '--'
|
|
continue
|
|
|
|
col_j = tab[0][j + 1] if named_columns else ''
|
|
diff_pr = round((res['average'] - res_j['average']) /
|
|
res_j['average'] * 100)
|
|
cell += f' {col_j}{diff_pr:+}%'
|
|
row.append(cell)
|
|
tab.append(row)
|
|
|
|
return f'All results are in {dim}\n\n' + tabulate.tabulate(tab)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
import sys
|
|
import json
|
|
|
|
if len(sys.argv) < 2:
|
|
print(f'USAGE: {sys.argv[0]} results.json')
|
|
exit(1)
|
|
|
|
with open(sys.argv[1]) as f:
|
|
print(results_to_text(json.load(f)))
|