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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# Analyse lock events and compute statistics
#
# Author: Alex Bennée <alex.bennee@linaro.org>
#
from __future__ import print_function
import simpletrace
import argparse
import numpy as np
class MutexAnalyser(simpletrace.Analyzer):
"A simpletrace Analyser for checking locks."
def __init__(self):
self.locks = 0
self.locked = 0
self.unlocks = 0
self.mutex_records = {}
def _get_mutex(self, mutex):
if not mutex in self.mutex_records:
self.mutex_records[mutex] = {"locks": 0,
"lock_time": 0,
"acquire_times": [],
"locked": 0,
"locked_time": 0,
"held_times": [],
"unlocked": 0}
return self.mutex_records[mutex]
def qemu_mutex_lock(self, timestamp, mutex, filename, line):
self.locks += 1
rec = self._get_mutex(mutex)
rec["locks"] += 1
rec["lock_time"] = timestamp[0]
rec["lock_loc"] = (filename, line)
def qemu_mutex_locked(self, timestamp, mutex, filename, line):
self.locked += 1
rec = self._get_mutex(mutex)
rec["locked"] += 1
rec["locked_time"] = timestamp[0]
acquire_time = rec["locked_time"] - rec["lock_time"]
rec["locked_loc"] = (filename, line)
rec["acquire_times"].append(acquire_time)
def qemu_mutex_unlock(self, timestamp, mutex, filename, line):
self.unlocks += 1
rec = self._get_mutex(mutex)
rec["unlocked"] += 1
held_time = timestamp[0] - rec["locked_time"]
rec["held_times"].append(held_time)
rec["unlock_loc"] = (filename, line)
def get_args():
"Grab options"
parser = argparse.ArgumentParser()
parser.add_argument("--output", "-o", type=str, help="Render plot to file")
parser.add_argument("events", type=str, help='trace file read from')
parser.add_argument("tracefile", type=str, help='trace file read from')
return parser.parse_args()
if __name__ == '__main__':
args = get_args()
# Gather data from the trace
analyser = MutexAnalyser()
simpletrace.process(args.events, args.tracefile, analyser)
print ("Total locks: %d, locked: %d, unlocked: %d" %
(analyser.locks, analyser.locked, analyser.unlocks))
# Now dump the individual lock stats
for key, val in sorted(analyser.mutex_records.iteritems(),
key=lambda k_v: k_v[1]["locks"]):
print ("Lock: %#x locks: %d, locked: %d, unlocked: %d" %
(key, val["locks"], val["locked"], val["unlocked"]))
acquire_times = np.array(val["acquire_times"])
if len(acquire_times) > 0:
print (" Acquire Time: min:%d median:%d avg:%.2f max:%d" %
(acquire_times.min(), np.median(acquire_times),
acquire_times.mean(), acquire_times.max()))
held_times = np.array(val["held_times"])
if len(held_times) > 0:
print (" Held Time: min:%d median:%d avg:%.2f max:%d" %
(held_times.min(), np.median(held_times),
held_times.mean(), held_times.max()))
# Check if any locks still held
if val["locks"] > val["locked"]:
print (" LOCK HELD (%s:%s)" % (val["locked_loc"]))
print (" BLOCKED (%s:%s)" % (val["lock_loc"]))
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