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Code Issues Releases Wiki Activity

energy_model: adjusting to compensate for leakage when evaluating cluster power

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This commit is contained in:
Sergei Trofimov 2015-08-10 10:42:32 +01:00
parent ab45c4499f
commit 1d67dd3b99
1 changed files with 56 additions and 9 deletions
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65
wlauto/instrumentation/energy_model/__init__.py
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@ -171,7 +171,7 @@ def generate_report(freq_power_table, measured_cpus_table, cpus_table, idle_powe
fig, axes = plt.subplots(1, 2)
fig.set_size_inches(16, 8)
for i, cluster in enumerate(reversed(cpus_table.columns.levels[0])):
projected = cpus_table[cluster].dropna()
projected = cpus_table[cluster].dropna(subset=['1'])
plot_cpus_table(projected, axes[i], cluster)
cpus_plot_data = get_figure_data(fig)
@ -290,7 +290,8 @@ def fit_polynomial(s, n):
return poly(s.index)
def get_cpus_power_table(data, index):
def get_cpus_power_table(data, index, opps): # pylint: disable=too-many-locals
# pylint: disable=no-member
power_table = data[[index, 'cluster', 'cpus', 'power']].pivot_table(index=index,
columns=['cluster', 'cpus'],
values='power')
@ -299,11 +300,40 @@ def get_cpus_power_table(data, index):
power_table[cluster, 0] = (power_table[cluster, 1] -
(power_table[cluster, 2] -
power_table[cluster, 1]))
bs_power_table[cluster, 1][power_table[cluster, 1].notnull()] = fit_polynomial(power_table[cluster, 1].dropna(), 2)
bs_power_table[cluster, 2][power_table[cluster, 2].notnull()] = fit_polynomial(power_table[cluster, 2].dropna(), 2)
bs_power_table[cluster, 0] = (bs_power_table[cluster, 1] -
(bs_power_table[cluster, 2] -
bs_power_table[cluster, 1]))
bs_power_table.loc[power_table[cluster, 1].notnull(), (cluster, 1)] = fit_polynomial(power_table[cluster, 1].dropna(), 2)
bs_power_table.loc[power_table[cluster, 2].notnull(), (cluster, 2)] = fit_polynomial(power_table[cluster, 2].dropna(), 2)
if opps[cluster] is None:
bs_power_table.loc[bs_power_table[cluster, 1].notnull(), (cluster, 0)] = \
(2* power_table[cluster, 1] - power_table[cluster, 2]).values
else:
df = pd.concat([bs_power_table[cluster],
opps[cluster].set_index('frequency')],
axis=1).dropna(subset=[1]).reset_index()
# Create a projection by calculating coefficients from the lowest two OPPs (assume minimal leakage)
v0 = df.voltage[0]
v1 = df.voltage[1]
f0 = df.frequency[0]
f1 = df.frequency[1]
# Assumption:
# P = k1*v*f + k2*v^2*f
coeffs = np.array([
[v0 * f0, (v0**2) * f0],
[v1 * f1, (v1**2) * f1]
])
c1pow = np.array([df[1][0], df[1][1]])
c2pow = np.array([df[2][0], df[2][1]])
c1k1, c1k2 = np.linalg.solve(coeffs, c1pow)
c2k1, c2k2 = np.linalg.solve(coeffs, c2pow)
df['a1'] = pd.Series(df.frequency * df.voltage * c1k1 + df.frequency * df.voltage ** 2 * c1k2,
index=df.index)
df['a2'] = pd.Series(df.frequency * df.voltage * c2k1 + df.frequency * df.voltage ** 2 * c2k2,
index=df.index)
bs_power_table.loc[bs_power_table[cluster, 1].notnull(), (cluster, 0)] = (2 * df.a1 - df.a2).values
# re-order columns and rename colum '0' to 'cluster'
power_table = power_table[sorted(power_table.columns,
cmp=lambda x, y: cmp(y[0], x[0]) or cmp(x[1], y[1]))]
@ -327,6 +357,12 @@ def plot_cpus_table(projected, ax, cluster):
ax.grid(True)
def opp_table(d):
if d is None:
return None
return pd.DataFrame(d.items(), columns=['frequency', 'voltage'])
class EnergyModelInstrument(Instrument):
name = 'energy_model'
@ -391,6 +427,10 @@ class EnergyModelInstrument(Instrument):
Parameter('num_of_freqs_to_thermal_adjust', kind=int, default=0,
description="""The number of frequencies begining from the highest, to be adjusted for
the thermal effect."""),
Parameter('big_opps', kind=opp_table,
description="""OPP table mapping frequency to volatage (kHz --> mV) for the big cluster."""),
Parameter('little_opps', kind=opp_table,
description="""OPP table mapping frequency to volatage (kHz --> mV) for the little cluster."""),
]
def validate(self):
@ -531,7 +571,11 @@ class EnergyModelInstrument(Instrument):
freq_power_table.to_csv(wfh, index=False)
context.add_artifact('freq_power_table', freq_output, 'export')
measured_cpus_table, cpus_table = get_cpus_power_table(freq_power_table, 'frequency')
if self.big_opps is None or self.little_opps is None:
message = 'OPPs not specified for one or both clusters; cluster power will not be adjusted for leakage.'
self.logger.warning(message)
opps = {'big': self.big_opps, 'little': self.little_opps}
measured_cpus_table, cpus_table = get_cpus_power_table(freq_power_table, 'frequency', opps)
measured_cpus_output = os.path.join(output_directory, MEASURED_CPUS_TABLE_FILE)
with open(measured_cpus_output, 'w') as wfh:
measured_cpus_table.to_csv(wfh)
@ -606,7 +650,10 @@ class EnergyModelInstrument(Instrument):
pids_to_move = server_pids + children_pids
self.cpuset.root.add_tasks(pids_to_move)
for pid in pids_to_move:
self.device.execute('busybox taskset -p 0x{:x} {}'.format(list_to_mask(self.measuring_cpus), pid))
try:
self.device.execute('busybox taskset -p 0x{:x} {}'.format(list_to_mask(self.measuring_cpus), pid))
except DeviceError:
pass
def enable_all_cores(self):
counter = Counter(self.device.core_names)