Files
c4core/bm/bm_plot_c4core.py

267 lines
10 KiB
Python

import sys
import os
import re
thisdir = os.path.dirname(os.path.abspath(__file__))
moddir = os.path.abspath(f"{thisdir}/../cmake/bm-xp")
sys.path.insert(0, moddir)
import bm_plot as bm
from bm_util import first
from dataclasses import dataclass
import prettytable
def get_function_benchmark(function_name, run: bm.BenchmarkRun):
for rbm in run.entries:
if rbm.meta.function == function_name:
return rbm
raise Exception(f"function not found: {function_name}. Existing: {[rbm.meta.function for rbm in run.entries]}")
@dataclass
class CharconvMeta: # also for atox
title: str
subject: str
function: str
data_type: bm.FundamentalTypes
@classmethod
def make(cls, bm_title: str):
# eg:
# xtoa_c4_write_dec<uint8_t>
# xtoa_c4_utoa<uint8_t>
# xtoa_c4_xtoa<uint8_t>
# xtoa_c4_to_chars<uint8_t>
# xtoa_std_to_chars<uint8_t>
# xtoa_std_to_string<uint8_t>
# xtoa_sprintf<uint8_t>
# xtoa_sstream_reuse<uint8_t>
# xtoa_sstream<uint8_t>
rx = re.compile(r'(atox|xtoa|xtoahex|xtoaoct|xtoabin)_(.*?)<(u?int\d+_t|float|double)>')
if not rx.fullmatch(bm_title):
raise Exception(f"cannot understand bm title: {bm_title}")
subject = rx.sub(r'\1', bm_title)
function = rx.sub(r'\2', bm_title)
data_type = rx.sub(r'\3', bm_title)
return cls(
title=bm_title,
subject=subject,
function=function.replace("c4_", "c4::").replace("std_", "std::"),
data_type=bm.FundamentalTypes.make(data_type)
)
@property
def shortname(self):
return self.function
@property
def shortparams(self):
return str(self.data_type.short)
@property
def shorttitle(self):
return f"{self.shortname}<{self.shortparams}>"
@dataclass
class CharconvThreadsMeta:
function: str
num_threads: int
@classmethod
def make(cls, bm_title: str):
# eg:
# c4_itoa/real_time/threads:4
rx = re.compile(r'(.*?)/real_time/threads:(\d+)')
if not rx.fullmatch(bm_title):
raise Exception(f"cannot understand bm title: {bm_title}")
function = rx.sub(r'\1', bm_title)
num_threads = int(rx.sub(r'\2', bm_title))
return cls(
function=function.replace("c4_", "c4::").replace("std_", "std::"),
num_threads=num_threads
)
def checkbox_groups(self):
return {}
@property
def shortname(self):
return self.function
@property
def shorttitle(self):
return self.shortname
def plot_charconv_bars(bm_panel: bm.BenchmarkPanel, getref,
panel_title_human: str,
outputfile_prefix: str):
assert os.path.isabs(outputfile_prefix), outputfile_prefix
# make a comparison table
anchor = lambda run: f"{os.path.basename(outputfile_prefix)}-{first(run.meta).data_type}"
anchorlink = lambda run: f"<pre><a href='#{anchor(run)}'>{first(run.meta).data_type}</a></pre>"
with open(f"{outputfile_prefix}.txt", "w") as tablefile:
with open(f"{outputfile_prefix}.md", "w") as mdfile:
print(f"## {panel_title_human}\n\n<p>Data type benchmark results:</p>\n<ul>\n",
"\n".join([f" <li>{anchorlink(run)}</li>" for run in bm_panel.runs]),
"</ul>\n\n", file=mdfile)
for run in bm_panel.runs:
data_type = first(run.meta).data_type
tabletitle = f"{outputfile_prefix}-{data_type.short}"
table = prettytable.PrettyTable(title=f"{panel_title_human}: {data_type}")
table.add_column("function", [m.shorttitle for m in run.meta], align="l")
for prop in ("mega_bytes_per_second", "cpu_time_ms"):
ref = getref(run)
bar_values = list(run.extract_plot_series(prop))
bar_values_rel = list(run.extract_plot_series(prop, relative_to_entry=ref))
bar_values_pc = list(run.extract_plot_series(prop, percent_of_entry=ref))
pd = bm_panel.first_run.property_plot_data(prop)
hns = pd.human_name_short
table.add_column(hns, [f"{v_:7.2f}" for v_ in bar_values], align="r")
hns = hns.replace(" (ms)", "")
table.add_column(f"{hns}(x)", [f"{v_:5.2f}x" for v_ in bar_values_rel], align="r")
table.add_column(f"{hns}(%)", [f"{v_:7.2f}%" for v_ in bar_values_pc], align="r")
print(table, "\n\n")
print(table, "\n\n", file=tablefile)
pfx_bps = f"{os.path.basename(outputfile_prefix)}-mega_bytes_per_second-{data_type.short}"
pfx_cpu = f"{os.path.basename(outputfile_prefix)}-cpu_time_ms-{data_type.short}"
print(f"""
<br/>
<br/>
---
<a id="{anchor(run)}"/>
### {panel_title_human}: `{data_type}`
* Interactive html graphs for `{data_type}`:
* [MB/s](./{pfx_bps}.html)
* [CPU time](./{pfx_cpu}.html)
[![{data_type}: MB/s](./{pfx_bps}.png)](./{pfx_bps}.png)
[![{data_type}: CPU time](./{pfx_cpu}.png)](./{pfx_cpu}.png)
```
{table}
```
""", file=mdfile)
# make plots
for prop in ("mega_bytes_per_second", "cpu_time_ms"):
ps, ps_ = [], []
pd = bm_panel.first_run.property_plot_data(prop)
bar_label = f"{pd.human_name_short}{pd.qty_type.comment}"
outfilename = f"{outputfile_prefix}-{prop}"
for run in bm_panel.runs:
data_type = first(run.meta).data_type
bar_names = [m.shorttitle for m in run.meta]
bar_values = list(run.extract_plot_series(prop))
runtitle = f"{outfilename}-{data_type.short}"
# to save each bokeh plot separately and also
# a grid plot with all of them, we have to plot
# twice because bokeh does not allow saving twice
# the same plot from multiple pictures.
plotit = lambda: bm.plot_benchmark_run_as_bars(run, title=f"{panel_title_human}: {data_type}\n{bar_label}",
bar_names=bar_names, bar_values=bar_values, bar_label=bar_label)
# make one plot to save:
p, p_ = plotit()
bm._bokeh_save_html(f"{runtitle}.html", p)
bm._plt_save_png(f"{runtitle}.png")
bm._plt_clear()
# and another to gather:
p, p_ = plotit()
ps.append(p)
ps_.append(p_)
bm._plt_clear()
bm.bokeh_plot_many(ps, f"{outfilename}.html")
def plot_itoa_threads_(bm_panel: bm.BenchmarkPanel, getref,
panel_title_human: str,
outputfile_prefix: str):
assert os.path.isabs(outputfile_prefix), outputfile_prefix
orig = lambda yprop, **kw: lambda run: list(run.extract_plot_series(yprop, **kw))
divnt = lambda yprop, **kw: lambda run: [v / n for v, n in run.extract_plot_series_with_threads(yprop, **kw)]
mulnt = lambda yprop, **kw: lambda run: [v * n for v, n in run.extract_plot_series_with_threads(yprop, **kw)]
xprop = "threads"
xpd = bm_panel.first_run.property_plot_data(xprop)
xlabel = f"{xpd.human_name_short}"
for yprop, ylog, yget in (
#("mega_items_per_second", False, orig),
("mega_bytes_per_second", False, orig),
#("iterations", False, divnt),
#("real_time_ms", True, mulnt),
("cpu_time_ms", True, orig),):
ypd = bm_panel.first_run.property_plot_data(yprop)
ylabel = f"{ypd.human_name_short}{ypd.qty_type.comment}"
p = bm.plot_benchmark_panel_as_lines(
bm_panel, f"{panel_title_human}\n{ylabel}",
xget=orig("threads"),
yget=yget(yprop),
nameget=lambda run: first(run.meta).function,
ylog=ylog,
xlabel=xlabel,
ylabel=ylabel
)
name = f"{outputfile_prefix}-lines-{yprop}"
# save png using matplotlib
bm._plt_save_png(f"{name}.png")
bm._plt_clear()
# save html using bokeh
bm._bokeh_save_html(f"{name}.html", p)
#bkp.show(p)
return p
def plot_itoa_threads(dir_: str, json_files):
panel = bm.BenchmarkPanel(json_files, CharconvThreadsMeta)
ref = lambda bmrun: get_function_benchmark("std::to_chars", run=bmrun)
plot_itoa_threads_(panel, ref,
f"itoa benchmark: convert 2M 32b integers to string",
f"{dir_}/c4core-bm-charconv_threads")
def plot_charconv_xtoa(dir_: str, json_files, is_ftoa: bool):
fcase = "ftoa" if is_ftoa else "xtoa"
panel = bm.BenchmarkPanel(json_files, CharconvMeta)
ref = lambda bmrun: get_function_benchmark("sprintf", run=bmrun)
plot_charconv_bars(panel, ref,
f"xtoa benchmark: convert 1M numbers to strings",
f"{dir_}/c4core-bm-charconv-{fcase}")
def plot_charconv_atox(dir_: str, json_files, is_atof: bool):
fcase = "atof" if is_atof else "atox"
panel = bm.BenchmarkPanel(json_files, CharconvMeta)
ref = lambda bmrun: get_function_benchmark("scanf", run=bmrun)
plot_charconv_bars(panel, ref,
f"atox benchmark: convert 1M strings to numbers",
f"{dir_}/c4core-bm-charconv-{fcase}")
if __name__ == '__main__':
args = sys.argv[1:]
if len(args) < 2:
raise Exception(f"usage: {sys.executable} {sys.argv[0]} <atox|xtoa|itoa_threads|format|digits> benchmarkfile.json[,benchmarkfile2.json,...]")
cmd = args[0]
json_files = args[1:]
dir_ = os.path.dirname(json_files[0])
for jf in json_files:
print("jf:", jf, flush=True)
assert os.path.dirname(jf) == dir_, (os.path.dirname(jf), dir_)
assert os.path.exists(jf), jf
if cmd == "itoa_threads":
plot_itoa_threads(dir_, json_files)
elif cmd == "xtoa" or cmd == "ftoa":
plot_charconv_xtoa(dir_, json_files, (cmd == "ftoa"))
elif cmd == "atox" or cmd == "atof":
plot_charconv_atox(dir_, json_files, (cmd == "atof"))
elif cmd == "format":
raise Exception(f"not implemented: {cmd}")
elif cmd == "digits":
pass # nothing to do
else:
raise Exception(f"not implemented: {cmd}")