# Copyright 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.
#
import os
import csv
from collections import OrderedDict
from wlauto import ResultProcessor, Parameter
from wlauto.core import signal
from wlauto.exceptions import ConfigError, DeviceError
from wlauto.instrumentation import instrument_is_installed
from wlauto.utils.power import report_power_stats
from wlauto.utils.misc import unique
class CpuStatesProcessor(ResultProcessor):
name = 'cpustates'
description = '''
Process power ftrace to produce CPU state and parallelism stats.
Parses trace-cmd output to extract power events and uses those to generate
statistics about parallelism and frequency/idle core residency.
.. note:: trace-cmd instrument must be enabled and configured to collect
at least ``power:cpu_idle`` and ``power:cpu_frequency`` events.
Reporting should also be enabled (it is by default) as
``cpustate`` parses the text version of the trace.
Finally, the device should have ``cpuidle`` module installed.
This generates two reports for the run:
*parallel.csv*
Shows what percentage of time was spent with N cores active (for N
from 0 to the total number of cores), for a cluster or for a system as
a whole. It contain the following columns:
:workload: The workload label
:iteration: iteration that was run
:cluster: The cluster for which statics are reported. The value of
``"all"`` indicates that this row reports statistics for
the whole system.
:number_of_cores: number of cores active. ``0`` indicates the cluster
was idle.
:total_time: Total time spent in this state during workload execution
:%time: Percentage of total workload execution time spent in this state
:%running_time: Percentage of the time the cluster was active (i.e.
ignoring time the cluster was idling) spent in this
state.
*cpustate.csv*
Shows percentage of the time a core spent in a particular power state. The first
column names the state is followed by a column for each core. Power states include
available DVFS frequencies (for heterogeneous systems, this is the union of
frequencies supported by different core types) and idle states. Some shallow
states (e.g. ARM WFI) will consume different amount of power depending on the
current OPP. For such states, there will be an entry for each opp. ``"unknown"``
indicates the percentage of time for which a state could not be established from the
trace. This is usually due to core state being unknown at the beginning of the trace,
but may also be caused by dropped events in the middle of the trace.
'''
parameters = [
Parameter('first_cluster_state', kind=int, default=2,
description="""
The first idle state which is common to a cluster.
"""),
Parameter('first_system_state', kind=int, default=3,
description="""
The first idle state which is common to all cores.
"""),
Parameter('write_iteration_reports', kind=bool, default=False,
description="""
By default, this instrument will generate reports for the entire run
in the overall output directory. Enabling this option will, in addition,
create reports in each iteration's output directory. The formats of these
reports will be similar to the overall report, except they won't mention
the workload name or iteration number (as that is implied by their location).
"""),
Parameter('use_ratios', kind=bool, default=False,
description="""
By default proportional values will be reported as percentages, if this
flag is enabled, they will be reported as ratios instead.
"""),
Parameter('create_timeline', kind=bool, default=True,
description="""
Create a CSV with the timeline of core power states over the course of the run
as well as the usual stats reports.
"""),
Parameter('create_utilization_timeline', kind=bool, default=False,
description="""
Create a CSV with the timeline of cpu(s) utilisation over the course of the run
as well as the usual stats reports.
The values generated are floating point numbers, normalised based on the maximum
frequency of the cluster.
"""),
Parameter('start_marker_handling', kind=str, default="try",
allowed_values=['ignore', 'try', 'error'],
description="""
The trace-cmd instrument inserts a marker into the trace to indicate the beginning
of workload execution. In some cases, this marker may be missing in the final
output (e.g. due to trace buffer overrun). This parameter specifies how a missing
start marker will be handled:
:`ignore`: The start marker will be ignored. All events in the trace will be used.
:`error`: An error will be raised if the start marker is not found in the trace.
:`try`: If the start marker is not found, all events in the trace will be used.
""")
]
def validate(self):
if not instrument_is_installed('trace-cmd'):
message = '''
{} requires "trace-cmd" instrument to be installed and the collection of at
least "power:cpu_frequency" and "power:cpu_idle" events to be enabled during worklad
execution.
'''
raise ConfigError(message.format(self.name).strip())
def initialize(self, context):
# pylint: disable=attribute-defined-outside-init
device = context.device
for modname in ['cpuidle', 'cpufreq']:
if not device.has(modname):
message = 'Device does not appear to have {} capability; is the right module installed?'
raise ConfigError(message.format(modname))
if not device.core_names:
message = '{} requires"core_names" and "core_clusters" to be specified for the device.'
raise ConfigError(message.format(self.name))
self.core_names = device.core_names
self.core_clusters = device.core_clusters
idle_states = {s.id: s.desc for s in device.get_cpuidle_states()}
self.idle_state_names = [idle_states[i] for i in sorted(idle_states.keys())]
self.num_idle_states = len(self.idle_state_names)
self.iteration_reports = OrderedDict()
self.max_freq_list = []
# priority -19: just higher than the slow_start of instrumentation
signal.connect(self.set_initial_state, signal.BEFORE_WORKLOAD_EXECUTION, priority=-19)
def set_initial_state(self, context):
# TODO: this does not play well with hotplug but leaving as-is, as this will be changed with
# the devilib port anyway.
# Write initial frequencies into the trace.
# NOTE: this assumes per-cluster DVFS, that is valid for devices that
# currently exist. This will need to be updated for per-CPU DFS.
# pylint: disable=attribute-defined-outside-init
self.logger.debug('Writing initial frequencies into trace...')
device = context.device
cluster_freqs = {}
cluster_max_freqs = {}
self.max_freq_list = []
for c in unique(device.core_clusters):
try:
cluster_freqs[c] = device.get_cluster_cur_frequency(c)
cluster_max_freqs[c] = device.get_cluster_max_frequency(c)
except ValueError:
cluster_freqs[c] = None
cluster_max_freqs[c] = None
for i, c in enumerate(device.core_clusters):
self.max_freq_list.append(cluster_max_freqs[c])
entry = 'CPU {} FREQUENCY: {} kHZ'.format(i, cluster_freqs[c])
device.set_sysfile_value('/sys/kernel/debug/tracing/trace_marker',
entry, verify=False)
# Nudge each cpu to force idle state transitions in the trace
self.logger.debug('Nudging all cores awake...')
for i in xrange(len(device.core_names)):
command = device.busybox + ' taskset 0x{:x} {}'
try:
device.execute(command.format(1 << i, 'ls'))
except DeviceError:
self.logger.warning("Failed to nudge CPU %s, has it been hot plugged out?", i)
def process_iteration_result(self, result, context):
trace = context.get_artifact('txttrace')
if not trace:
self.logger.debug('Text trace does not appear to have been generated; skipping this iteration.')
return
self.logger.debug('Generating power state reports from trace...')
if self.create_timeline:
timeline_csv_file = os.path.join(context.output_directory, 'power_states.csv')
else:
timeline_csv_file = None
if self.create_utilization_timeline:
cpu_utilisation = os.path.join(context.output_directory, 'cpu_utilisation.csv')
else:
cpu_utilisation = None
reports = report_power_stats( # pylint: disable=unbalanced-tuple-unpacking
trace_file=trace.path,
idle_state_names=self.idle_state_names,
core_names=self.core_names,
core_clusters=self.core_clusters,
num_idle_states=self.num_idle_states,
first_cluster_state=self.first_cluster_state,
first_system_state=self.first_system_state,
use_ratios=self.use_ratios,
timeline_csv_file=timeline_csv_file,
cpu_utilisation=cpu_utilisation,
max_freq_list=self.max_freq_list,
start_marker_handling=self.start_marker_handling,
)
parallel_report = reports.pop(0)
powerstate_report = reports.pop(0)
if parallel_report is None:
self.logger.warning('No power state reports generated; are power '
'events enabled in the trace?')
return
else:
self.logger.debug('Reports generated.')
iteration_id = (context.spec.id, context.spec.label, context.current_iteration)
self.iteration_reports[iteration_id] = (parallel_report, powerstate_report)
if self.write_iteration_reports:
self.logger.debug('Writing iteration reports')
parallel_report.write(os.path.join(context.output_directory, 'parallel.csv'))
powerstate_report.write(os.path.join(context.output_directory, 'cpustates.csv'))
def process_run_result(self, result, context): # pylint: disable=too-many-locals
if not self.iteration_reports:
self.logger.warning('No power state reports generated.')
return
parallel_rows = []
powerstate_rows = []
for iteration_id, reports in self.iteration_reports.iteritems():
spec_id, workload, iteration = iteration_id
parallel_report, powerstate_report = reports
for record in parallel_report.values:
parallel_rows.append([spec_id, workload, iteration] + record)
for state in sorted(powerstate_report.state_stats):
stats = powerstate_report.state_stats[state]
powerstate_rows.append([spec_id, workload, iteration, state] +
['{:.3f}'.format(s if s is not None else 0)
for s in stats])
with open(os.path.join(context.output_directory, 'parallel.csv'), 'w') as wfh:
writer = csv.writer(wfh)
writer.writerow(['id', 'workload', 'iteration', 'cluster',
'number_of_cores', 'total_time',
'%time', '%running_time'])
writer.writerows(parallel_rows)
with open(os.path.join(context.output_directory, 'cpustate.csv'), 'w') as wfh:
writer = csv.writer(wfh)
headers = ['id', 'workload', 'iteration', 'state']
headers += ['{} CPU{}'.format(c, i)
for i, c in enumerate(powerstate_report.core_names)]
writer.writerow(headers)
writer.writerows(powerstate_rows)