llvm-mirror/tools/opt-viewer/opt-stats.py
Adam Nemet c8a609b98e [opt-viewer] Print allocated memory per remark in opt-stats.py
If heapy is installed print the "average" in-memory remark size.  This is
estimated by dividing the total heap size by the number of unique remarks.

llvm-svn: 308537
2017-07-19 22:04:58 +00:00

79 lines
2.5 KiB
Python
Executable File

#!/usr/bin/env python2.7
from __future__ import print_function
desc = '''Generate statistics about optimization records from the YAML files
generated with -fsave-optimization-record and -fdiagnostics-show-hotness.
The tools requires PyYAML and Pygments Python packages.'''
import optrecord
import argparse
import operator
from collections import defaultdict
from multiprocessing import cpu_count, Pool
try:
from guppy import hpy
hp = hpy()
except ImportError:
print("Memory consumption not shown because guppy is not installed")
hp = None
if __name__ == '__main__':
parser = argparse.ArgumentParser(description=desc)
parser.add_argument(
'yaml_dirs_or_files',
nargs='+',
help='List of optimization record files or directories searched '
'for optimization record files.')
parser.add_argument(
'--jobs',
'-j',
default=cpu_count(),
type=int,
help='Max job count (defaults to %(default)s, the current CPU count)')
parser.add_argument(
'--no-progress-indicator',
'-n',
action='store_true',
default=False,
help='Do not display any indicator of how many YAML files were read.')
args = parser.parse_args()
print_progress = not args.no_progress_indicator
files = optrecord.find_opt_files(args.yaml_dirs_or_files)
if not files:
parser.error("No *.opt.yaml files found")
sys.exit(1)
all_remarks, file_remarks, _ = optrecord.gather_results(
files, args.jobs, print_progress)
if print_progress:
print('\n')
bypass = defaultdict(int)
byname = defaultdict(int)
for r in optrecord.itervalues(all_remarks):
bypass[r.Pass] += 1
byname[r.Pass + "/" + r.Name] += 1
total = len(all_remarks)
print("{:24s} {:10d}".format("Total number of remarks", total))
if hp:
h = hp.heap()
print("{:24s} {:10d}".format("Memory per remark",
h.size / len(all_remarks)))
print('\n')
print("Top 10 remarks by pass:")
for (passname, count) in sorted(bypass.items(), key=operator.itemgetter(1),
reverse=True)[:10]:
print(" {:30s} {:2.0f}%". format(passname, count * 100. / total))
print("\nTop 10 remarks:")
for (name, count) in sorted(byname.items(), key=operator.itemgetter(1),
reverse=True)[:10]:
print(" {:30s} {:2.0f}%". format(name, count * 100. / total))