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