107 lines
2.9 KiB
Python
107 lines
2.9 KiB
Python
#!/usr/bin/env python3
|
|
|
|
""" Generates performance statistics for the eh_elf vs vanilla libunwind unwinding,
|
|
based on time series generated beforehand
|
|
|
|
Intended to be run from `statistics.sh`
|
|
"""
|
|
|
|
from collections import namedtuple
|
|
import numpy as np
|
|
import sys
|
|
import os
|
|
|
|
|
|
Datapoint = namedtuple("Datapoint", ["nb_frames", "total_time", "avg_time"])
|
|
|
|
|
|
def read_series(path):
|
|
with open(path, "r") as handle:
|
|
for line in handle:
|
|
nb_frames, total_time, avg_time = map(int, line.strip().split())
|
|
yield Datapoint(nb_frames, total_time, avg_time)
|
|
|
|
|
|
FLAVOURS = ["eh_elf", "vanilla"]
|
|
WITH_NOCACHE = False
|
|
|
|
if "WITH_NOCACHE" in os.environ:
|
|
WITH_NOCACHE = True
|
|
FLAVOURS.append("vanilla-nocache")
|
|
|
|
path_format = os.path.join(sys.argv[1], "{}_times")
|
|
datapoints = {}
|
|
avg_times = {}
|
|
total_times = {}
|
|
avgs_total = {}
|
|
avgs = {}
|
|
std_deviations = {}
|
|
unwound_frames = {}
|
|
|
|
for flv in FLAVOURS:
|
|
datapoints[flv] = list(read_series(path_format.format(flv)))
|
|
avg_times[flv] = list(map(lambda x: x.avg_time, datapoints[flv]))
|
|
total_times[flv] = list(map(lambda x: x.total_time, datapoints[flv]))
|
|
avgs[flv] = sum(avg_times[flv]) / len(avg_times[flv])
|
|
avgs_total[flv] = sum(total_times[flv]) / len(total_times[flv])
|
|
std_deviations[flv] = np.sqrt(np.var(avg_times[flv]))
|
|
|
|
cur_unwound_frames = list(map(lambda x: x.nb_frames, datapoints[flv]))
|
|
unwound_frames[flv] = cur_unwound_frames[0]
|
|
for run_id, unw_frames in enumerate(cur_unwound_frames[1:]):
|
|
if unw_frames != unwound_frames[flv]:
|
|
print(
|
|
"{}, run {}: unwound {} frames, reference unwound {}".format(
|
|
flv, run_id + 1, unw_frames, unwound_frames[flv]
|
|
),
|
|
file=sys.stderr,
|
|
)
|
|
|
|
avg_ratio = avgs["vanilla"] / avgs["eh_elf"]
|
|
ratio_uncertainty = (
|
|
1
|
|
/ avgs["eh_elf"]
|
|
* (
|
|
std_deviations["vanilla"]
|
|
+ avgs["vanilla"] / avgs["eh_elf"] * std_deviations["eh_elf"]
|
|
)
|
|
)
|
|
|
|
|
|
def format_flv(flv_dict, formatter, alterator=None):
|
|
out = ""
|
|
for flv in FLAVOURS:
|
|
val = flv_dict[flv]
|
|
altered = alterator(val) if alterator else val
|
|
out += "* {}: {}\n".format(flv, formatter.format(altered))
|
|
return out
|
|
|
|
|
|
def get_ratios(avgs):
|
|
def avg_of(flavour):
|
|
return avgs[flavour] / avgs["eh_elf"]
|
|
|
|
if WITH_NOCACHE:
|
|
return "\n\tcached: {}\n\tuncached: {}".format(
|
|
avg_of("vanilla"), avg_of("vanilla-nocache")
|
|
)
|
|
else:
|
|
return avg_of("vanilla")
|
|
|
|
|
|
print(
|
|
"Unwound frames:\n{}\n"
|
|
"Average whole unwinding time (one run):\n{}\n"
|
|
"Average time to unwind one frame:\n{}\n"
|
|
"Standard deviation:\n{}\n"
|
|
"Average ratio: {}\n"
|
|
"Ratio uncertainty: {}".format(
|
|
format_flv(unwound_frames, "{}"),
|
|
format_flv(avgs_total, "{} μs", alterator=lambda x: x // 1000),
|
|
format_flv(avgs, "{} ns"),
|
|
format_flv(std_deviations, "{}"),
|
|
get_ratios(avgs),
|
|
ratio_uncertainty,
|
|
)
|
|
)
|