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workload-automation/wa/instruments/perf.py
2018-09-06 08:39:09 +01:00

139 lines
5.4 KiB
Python

# Copyright 2013-2015 ARM Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# pylint: disable=unused-argument
import os
import re
from devlib.trace.perf import PerfCollector
from wa import Instrument, Parameter
from wa.utils.types import list_or_string, list_of_strs
PERF_COUNT_REGEX = re.compile(r'^(CPU\d+)?\s*(\d+)\s*(.*?)\s*(\[\s*\d+\.\d+%\s*\])?\s*$')
class PerfInstrument(Instrument):
name = 'perf'
description = """
Perf is a Linux profiling with performance counters.
Performance counters are CPU hardware registers that count hardware events
such as instructions executed, cache-misses suffered, or branches
mispredicted. They form a basis for profiling applications to trace dynamic
control flow and identify hotspots.
pref accepts options and events. If no option is given the default '-a' is
used. For events, the default events are migrations and cs. They both can
be specified in the config file.
Events must be provided as a list that contains them and they will look like
this ::
perf_events = ['migrations', 'cs']
Events can be obtained by typing the following in the command line on the
device ::
perf list
Whereas options, they can be provided as a single string as following ::
perf_options = '-a -i'
Options can be obtained by running the following in the command line ::
man perf-stat
"""
parameters = [
Parameter('events', kind=list_of_strs, default=['migrations', 'cs'],
global_alias='perf_events',
constraint=(lambda x: x, 'must not be empty.'),
description="""Specifies the events to be counted."""),
Parameter('optionstring', kind=list_or_string, default='-a',
global_alias='perf_options',
description="""Specifies options to be used for the perf command. This
may be a list of option strings, in which case, multiple instances of perf
will be kicked off -- one for each option string. This may be used to e.g.
collected different events from different big.LITTLE clusters.
"""),
Parameter('labels', kind=list_of_strs, default=None,
global_alias='perf_labels',
description="""Provides labels for pref output. If specified, the number of
labels must match the number of ``optionstring``\ s.
"""),
Parameter('force_install', kind=bool, default=False,
description="""
always install perf binary even if perf is already present on the device.
"""),
]
def __init__(self, target, **kwargs):
super(PerfInstrument, self).__init__(target, **kwargs)
self.collector = None
def initialize(self, context):
self.collector = PerfCollector(self.target,
self.events,
self.optionstring,
self.labels,
self.force_install)
def setup(self, context):
self.collector.reset()
def start(self, context):
self.collector.start()
def stop(self, context):
self.collector.stop()
def update_output(self, context):
self.logger.info('Extracting reports from target...')
outdir = os.path.join(context.output_directory, 'perf')
self.collector.get_trace(outdir)
for host_file in os.listdir(outdir):
label = host_file.split('.out')[0]
host_file_path = os.path.join(outdir, host_file)
context.add_artifact(label, host_file_path, 'raw')
with open(host_file_path) as fh:
in_results_section = False
for line in fh:
if 'Performance counter stats' in line:
in_results_section = True
next(fh) # skip the following blank line
if in_results_section:
if not line.strip(): # blank line
in_results_section = False
break
else:
line = line.split('#')[0] # comment
match = PERF_COUNT_REGEX.search(line)
if match:
classifiers = {}
cpu = match.group(1)
if cpu is not None:
classifiers['cpu'] = int(cpu.replace('CPU', ''))
count = int(match.group(2))
metric = '{}_{}'.format(label, match.group(3))
context.add_metric(metric, count, classifiers=classifiers)
def teardown(self, context):
self.collector.reset()