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mirror of https://github.com/ARM-software/workload-automation.git synced 2024-10-06 02:41:11 +01:00

Merge pull request #501 from bjackman/acme-multiple-instruments2

energy_measurement: Allow multiple IIO devices for ACME
This commit is contained in:
setrofim 2017-10-06 15:01:31 +01:00 committed by GitHub
commit 12edabf753

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@ -16,6 +16,7 @@
# pylint: disable=W0613,E1101
from __future__ import division
from collections import defaultdict
import os
from devlib import DerivedEnergyMeasurements
@ -46,6 +47,14 @@ class EnergyInstrumentBackend(Plugin):
def validate_parameters(self, params):
pass
def get_instruments(self, target, **kwargs):
"""
Get a dict mapping device keys to an Instruments
Typically there is just a single device/instrument, in which case the
device key is arbitrary.
"""
return {None: self.instrument(target, **kwargs)}
class DAQBackend(EnergyInstrumentBackend):
@ -156,7 +165,8 @@ class AcmeCapeBackend(EnergyInstrumentBackend):
description="""
Host name (or IP address) of the ACME cape board.
"""),
Parameter('iio-device', default='iio:device0',
Parameter('iio-devices', default='iio:device0',
kind=list_or_string,
description="""
"""),
Parameter('buffer-size', kind=int, default=256,
@ -165,7 +175,30 @@ class AcmeCapeBackend(EnergyInstrumentBackend):
"""),
]
instrument = AcmeCapeInstrument
def get_instruments(self, target,
iio_capture, host, iio_devices, buffer_size):
#
# Devlib's ACME instrument uses iio-capture under the hood, which can
# only capture data from one IIO device at a time. Devlib's instrument
# API expects to produce a single CSV file for the Instrument, with a
# single axis of sample timestamps. These two things cannot be correctly
# reconciled without changing the devlib Instrument API - get_data would
# need to be able to return two distinct sets of data.
#
# Instead, where required WA will instantiate the ACME instrument
# multiple times (once for each IIO device), producing two separate CSV
# files. Aggregated energy info _can_ be meaningfully combined from
# multiple IIO devices, so we will later sum the derived stats across
# each of the channels reported by the instruments.
#
ret = {}
for iio_device in iio_devices:
ret[iio_device] = AcmeCapeInstrument(
target, iio_capture=iio_capture, host=host,
iio_device=iio_device, buffer_size=buffer_size)
return ret
class EnergyMeasurement(Instrument):
@ -211,15 +244,11 @@ class EnergyMeasurement(Instrument):
def __init__(self, target, loader=pluginloader, **kwargs):
super(EnergyMeasurement, self).__init__(target, **kwargs)
self.instrumentation = None
self.measurement_csv = None
self.measurement_csvs = {}
self.loader = loader
self.backend = self.loader.get_plugin(self.instrument)
self.params = obj_dict()
if self.backend.instrument.mode != CONTINUOUS:
msg = '{} instrument does not support continuous measurement collection'
raise ConfigError(msg.format(self.instrument))
supported_params = self.backend.get_parameters()
for name, param in supported_params.iteritems():
value = self.instrument_parameters.get(name)
@ -227,30 +256,79 @@ class EnergyMeasurement(Instrument):
self.backend.validate_parameters(self.params)
def initialize(self, context):
self.instrumentation = self.backend.instrument(self.target, **self.params)
self.instruments = self.backend.get_instruments(self.target, **self.params)
for instrument in self.instruments.itervalues():
if instrument.mode != CONTINUOUS:
msg = '{} instrument does not support continuous measurement collection'
raise ConfigError(msg.format(self.instrument))
for channel in self.channels or []:
if not self.instrumentation.get_channels(channel):
raise ConfigError('No channels found for "{}"'.format(channel))
# Check that the expeccted channels exist.
# If there are multiple Instruments, they were all constructed with
# the same channels param, so check them all.
for instrument in self.instruments.itervalues():
if not instrument.get_channels(channel):
raise ConfigError('No channels found for "{}"'.format(channel))
def setup(self, context):
self.instrumentation.reset(sites=self.sites,
kinds=self.kinds,
channels=self.channels)
for instrument in self.instruments.itervalues():
instrument.reset(sites=self.sites,
kinds=self.kinds,
channels=self.channels)
def start(self, context):
self.instrumentation.start()
for instrument in self.instruments.itervalues():
instrument.start()
def stop(self, context):
self.instrumentation.stop()
for instrument in self.instruments.itervalues():
instrument.stop()
def update_result(self, context):
outfile = os.path.join(context.output_directory, 'energy_instrument_output.csv')
self.measurement_csv = self.instrumentation.get_data(outfile)
context.add_artifact('energy_instrument_output', outfile, 'data')
for device, instrument in self.instruments.iteritems():
# Append the device key to the filename and artifact name, unless
# it's None (as it will be for backends with only 1
# devce/instrument)
if device is not None:
name = 'energy_instrument_output_{}'.format(device)
else:
name = 'energy_instrument_output'
outfile = os.path.join(context.output_directory, '{}.csv'.format(name))
self.measurement_csvs[device] = instrument.get_data(outfile)
context.add_artifact(name, outfile, 'data',
classifiers={'device': device})
self.extract_metrics(context)
def extract_metrics(self, context):
derived_measurements = DerivedEnergyMeasurements.process(self.measurement_csv)
for meas in derived_measurements:
context.add_metric(meas.name, meas.value, meas.units)
metrics_by_name = defaultdict(list)
for device in self.instruments:
csv = self.measurement_csvs[device]
derived_measurements = DerivedEnergyMeasurements.process(csv)
for meas in derived_measurements:
# Append the device key to the metric name, unless it's None (as
# it will be for backends with only 1 devce/instrument)
if device is not None:
metric_name = '{}_{}'.format(meas.name, device)
else:
metric_name = meas.name
context.add_metric(metric_name, meas.value, meas.units,
classifiers={'device': device})
metrics_by_name[meas.name].append(meas)
# Where we have multiple instruments, add up all the metrics with the
# same name. For instance with ACME we may have multiple IIO devices
# each reporting 'device_energy' and 'device_power', so sum them up to
# produce aggregated energy and power metrics.
# (Note that metrics_by_name uses the metric name originally reported by
# the devlib instrument, before we potentially appended a device key to
# it)
if len(self.instruments) > 1:
for name, metrics in metrics_by_name.iteritems():
units = metrics[0].units
value = sum(m.value for m in metrics)
context.add_metric(name, value, units)