Telemetry: adds CPU frequency stats.

tools/perf/metrics/cpu.py

 # Copyright 2013 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 from metrics import Metric
 
 class CpuMetric(Metric):
   """Calulates CPU load over a span of time."""
 
   def __init__(self, browser):
@@ skipping 12 matching lines @@
   def Stop(self, page, tab):
     assert self._start_cpu, 'Must call Start() first'
     self._results = _SubtractCpuStats(self._browser.cpu_stats, self._start_cpu)
 
   # Optional argument trace_name is not in base class Metric.
   # pylint: disable=W0221
   def AddResults(self, tab, results, trace_name='cpu_utilization'):
     assert self._results, 'Must call Stop() first'
     # Add a result for each process type.
     for process_type in self._results:
+      if process_type == 'Global':
+        continue
       trace_name_for_process = '%s_%s' % (trace_name, process_type.lower())
       cpu_percent = 100 * self._results[process_type]
       results.Add(trace_name_for_process, '%', cpu_percent,
                   chart_name='cpu_utilization', data_type='unimportant')
+    # Add a result for Global CPU stats.

[qyearsley, 2014/04/22 17:00:51]

Does "Global" mean all process types combined?

[bulach, 2014/04/22 17:12:30]

sort of. :)
it means system-wide utilization, not per process.
so yes, all process combined, but not necessarily "chrome process".

[qyearsley, 2014/04/22 17:25:52]

Alright -- not sure if it would be clearer if you say this in the comment above?

[bulach, 2014/04/22 17:52:48]

Done.

+    time_spent = 0.0

[qyearsley, 2014/04/22 17:00:51]

Is this in seconds or milliseconds?

[bulach, 2014/04/22 17:12:30]

I suppose the unit is 10mS:
https://www.kernel.org/doc/Documentation/cpu-freq/cpufreq-stats.txt

but it doesn't matter, it's just for a weighted average.

+    frequency_sum = 0.0
+    for k, v in self._results['Global']['GlobalCpuFrequencyStats'].iteritems():
+      frequency_sum += (k * v)

[qyearsley, 2014/04/22 17:00:51]

So what does frequency_sum represent? What are k and v?
I'm guessing that it's Hertz-seconds? So 1 MHz for 2 seconds would be 2,000,000
Hertz-seconds?

[bulach, 2014/04/22 17:12:30]

k and v are the key-values, happy to expand to frequency and time if you think
it's clearer.

you're right about Hertz-seconds, but that's probably a difficult to grasp unit
since Hertz is 1/second :) I suppose keeping it unit-less is clearer and
correct?

[qyearsley, 2014/04/22 17:25:52]

I think it would be a bit clearer if it were frequency and time rather than k
and v, although then you're gonna have to split that line :-P

Since Hertz in the context of processing is cycles/second, Hertz-seconds =
cycles, but since the time isn't in seconds, frequency_sum isn't actually number
of cycles...

Either way, frequency_sum is just used to compute average frequency, so I guess
it's better this way.

[bulach, 2014/04/22 17:52:48]

Replaced k, v with frequency, time_in_state.
I couldn't think of anything better for the the sums, but happy to change if you
have any other suggestion.

+      time_spent += v
+    results.Add('average_frequency_hz', 'Hz',
+                int(frequency_sum / time_spent),
+                chart_name='cpu_frequency',
+                data_type='unimportant')

[pasko, 2014/04/22 14:06:30]

what does data_type mean? is it documented anywhere? is it used anywhere?

[qyearsley, 2014/04/22 17:00:51]

The data_type parameter specifies two things -- whether the result that's being
added is a scalar value, a list of values, or a "histogram", and also whether it
should be marked as "important" (whether it's a primary thing that's being
measured or just extra info).

I think this way of specifying values is going to be deprecated.

 
 
 def _SubtractCpuStats(cpu_stats, start_cpu_stats):
   """Computes average cpu usage over a time period for different process types.
 
   Each of the two cpu_stats arguments is a dict with the following format:
       {'Browser': {'CpuProcessTime': ..., 'TotalTime': ...},
        'Renderer': {'CpuProcessTime': ..., 'TotalTime': ...}
        'Gpu': {'CpuProcessTime': ..., 'TotalTime': ...}}
 
   The 'CpuProcessTime' fields represent the number of seconds of CPU time
   spent in each process, and total time is the number of real seconds
   that have passed (this may be a Unix timestamp).
 
   Returns:
     A dict of process type names (Browser, Renderer, etc.) to ratios of cpu
     time used to total time elapsed.
   """
   cpu_usage = {}
   for process_type in cpu_stats:
     assert process_type in start_cpu_stats, 'Mismatching process types'
     # Skip any process_types that are empty.
-    if (not cpu_stats[process_type]) or (not start_cpu_stats[process_type]):
+    if ((not cpu_stats[process_type]) or
+        (not start_cpu_stats[process_type]) or
+        process_type == 'Global'):
       continue
     cpu_process_time = (cpu_stats[process_type]['CpuProcessTime'] -
                         start_cpu_stats[process_type]['CpuProcessTime'])
     total_time = (cpu_stats[process_type]['TotalTime'] -
                   start_cpu_stats[process_type]['TotalTime'])
     assert total_time > 0, 'Expected total_time > 0, was: %d' % total_time
     cpu_usage[process_type] = float(cpu_process_time) / total_time
+
+  if 'Global' not in cpu_stats:
+    return cpu_usage
+
+  frequency_stats = cpu_stats['Global']['GlobalCpuFrequencyStats']
+  start_frequency_stats = start_cpu_stats['Global']['GlobalCpuFrequencyStats']
+  total_frequency_stats = {}
+  for k in frequency_stats.iterkeys():
+    total_frequency_stats[k] = frequency_stats[k] - start_frequency_stats[k]
+
+  cpu_usage['Global'] = {}
+  cpu_usage['Global']['GlobalCpuFrequencyStats'] = total_frequency_stats
   return cpu_usage
-