grpc/tools/profiling/microbenchmarks/bm_diff.py

#!/usr/bin/env python2.7
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import sys
import json
import bm_json
import tabulate
import argparse
from scipy import stats
import subprocess
import multiprocessing
import collections
import pipes
import os
sys.path.append(os.path.join(os.path.dirname(sys.argv[0]), '..', '..', 'run_tests', 'python_utils'))
import comment_on_pr
import jobset
import itertools
import speedup
import random
import shutil

_INTERESTING = (
  'cpu_time',
  'real_time',
  'locks_per_iteration',
  'allocs_per_iteration',
  'writes_per_iteration',
  'atm_cas_per_iteration',
  'atm_add_per_iteration',
)

def changed_ratio(n, o):
  if float(o) <= .0001: o = 0
  if float(n) <= .0001: n = 0
  if o == 0 and n == 0: return 0
  if o == 0: return 100
  return (float(n)-float(o))/float(o)

def median(ary):
  ary = sorted(ary)
  n = len(ary)
  if n%2 == 0:
    return (ary[n/2] + ary[n/2+1]) / 2.0
  else:
    return ary[n/2]

def min_change(pct):
  return lambda n, o: abs(changed_ratio(n,o)) > pct/100.0

_AVAILABLE_BENCHMARK_TESTS = ['bm_fullstack_unary_ping_pong',
                              'bm_fullstack_streaming_ping_pong',
                              'bm_fullstack_streaming_pump',
                              'bm_closure',
                              'bm_cq',
                              'bm_call_create',
                              'bm_error',
                              'bm_chttp2_hpack',
                              'bm_chttp2_transport',
                              'bm_pollset',
                              'bm_metadata',
                              'bm_fullstack_trickle']

argp = argparse.ArgumentParser(description='Perform diff on microbenchmarks')
argp.add_argument('-t', '--track',
                  choices=sorted(_INTERESTING),
                  nargs='+',
                  default=sorted(_INTERESTING),
                  help='Which metrics to track')
argp.add_argument('-b', '--benchmarks', nargs='+', choices=_AVAILABLE_BENCHMARK_TESTS, default=['bm_cq'])
argp.add_argument('-d', '--diff_base', type=str)
argp.add_argument('-r', '--repetitions', type=int, default=1)
argp.add_argument('-l', '--loops', type=int, default=12)
argp.add_argument('-j', '--jobs', type=int, default=multiprocessing.cpu_count())
args = argp.parse_args()

assert args.diff_base

def avg(lst):
  sum = 0.0
  n = 0.0
  for el in lst:
    sum += el
    n += 1
  return sum / n

def make_cmd(cfg):
  return ['make'] + args.benchmarks + [
      'CONFIG=%s' % cfg, '-j', '%d' % args.jobs]

def build(dest):
  shutil.rmtree('bm_diff_%s' % dest, ignore_errors=True)
  subprocess.check_call(['git', 'submodule', 'update'])
  try:
    subprocess.check_call(make_cmd('opt'))
    subprocess.check_call(make_cmd('counters'))
  except subprocess.CalledProcessError, e:
    subprocess.check_call(['make', 'clean'])
    subprocess.check_call(make_cmd('opt'))
    subprocess.check_call(make_cmd('counters'))
  os.rename('bins', 'bm_diff_%s' % dest)

def collect1(bm, cfg, ver, idx):
  cmd = ['bm_diff_%s/%s/%s' % (ver, cfg, bm),
         '--benchmark_out=%s.%s.%s.%d.json' % (bm, cfg, ver, idx),
         '--benchmark_out_format=json',
         '--benchmark_repetitions=%d' % (args.repetitions)
         ]
  return jobset.JobSpec(cmd, shortname='%s %s %s %d/%d' % (bm, cfg, ver, idx+1, args.loops),
                             verbose_success=True, timeout_seconds=None)

build('new')

where_am_i = subprocess.check_output(['git', 'rev-parse', '--abbrev-ref', 'HEAD']).strip()
subprocess.check_call(['git', 'checkout', args.diff_base])
try:
  build('old')
finally:
  subprocess.check_call(['git', 'checkout', where_am_i])
  subprocess.check_call(['git', 'submodule', 'update'])

jobs = []
for loop in range(0, args.loops):
  jobs.extend(x for x in itertools.chain(
    (collect1(bm, 'opt', 'new', loop) for bm in args.benchmarks),
    (collect1(bm, 'counters', 'new', loop) for bm in args.benchmarks),
    (collect1(bm, 'opt', 'old', loop) for bm in args.benchmarks),
    (collect1(bm, 'counters', 'old', loop) for bm in args.benchmarks),
  ))
random.shuffle(jobs, random.SystemRandom().random)

jobset.run(jobs, maxjobs=args.jobs)

class Benchmark:

  def __init__(self):
    self.samples = {
      True: collections.defaultdict(list),
      False: collections.defaultdict(list)
    }
    self.final = {}

  def add_sample(self, data, new):
    for f in args.track:
      if f in data:
        self.samples[new][f].append(float(data[f]))

  def process(self):
    for f in sorted(args.track):
      new = self.samples[True][f]
      old = self.samples[False][f]
      if not new or not old: continue
      mdn_diff = abs(median(new) - median(old))
      print '%s: new=%r old=%r mdn_diff=%r' % (f, new, old, mdn_diff)
      s = speedup.speedup(new, old)
      if abs(s) > 3 and mdn_diff > 0.5:
        self.final[f] = '%+d%%' % s
    return self.final.keys()

  def skip(self):
    return not self.final

  def row(self, flds):
    return [self.final[f] if f in self.final else '' for f in flds]


benchmarks = collections.defaultdict(Benchmark)

for bm in args.benchmarks:
  for loop in range(0, args.loops):
    with open('%s.counters.new.%d.json' % (bm, loop)) as f:
      js_new_ctr = json.loads(f.read())
    with open('%s.opt.new.%d.json' % (bm, loop)) as f:
      js_new_opt = json.loads(f.read())
    with open('%s.counters.old.%d.json' % (bm, loop)) as f:
      js_old_ctr = json.loads(f.read())
    with open('%s.opt.old.%d.json' % (bm, loop)) as f:
      js_old_opt = json.loads(f.read())

    for row in bm_json.expand_json(js_new_ctr, js_new_opt):
      print row
      name = row['cpp_name']
      if name.endswith('_mean') or name.endswith('_stddev'): continue
      benchmarks[name].add_sample(row, True)
    for row in bm_json.expand_json(js_old_ctr, js_old_opt):
      print row
      name = row['cpp_name']
      if name.endswith('_mean') or name.endswith('_stddev'): continue
      benchmarks[name].add_sample(row, False)

really_interesting = set()
for name, bm in benchmarks.items():
  print name
  really_interesting.update(bm.process())
fields = [f for f in args.track if f in really_interesting]

headers = ['Benchmark'] + fields
rows = []
for name in sorted(benchmarks.keys()):
  if benchmarks[name].skip(): continue
  rows.append([name] + benchmarks[name].row(fields))
if rows:
  text = 'Performance differences noted:\n' + tabulate.tabulate(rows, headers=headers, floatfmt='+.2f')
else:
  text = 'No significant performance differences'
comment_on_pr.comment_on_pr('```\n%s\n```' % text)
print text