128 lines
3.7 KiB
Python
128 lines
3.7 KiB
Python
#!/usr/bin/env python3
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# Copyright Hans Dembinski 2018 - 2019.
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# Distributed under the Boost Software License, Version 1.0.
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# (See accompanying file LICENSE_1_0.txt or copy at
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# https://www.boost.org/LICENSE_1_0.txt)
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import os
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import numpy as np
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import glob
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import re
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import json
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import sys
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from collections import defaultdict, OrderedDict
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from matplotlib.patches import Rectangle
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from matplotlib.lines import Line2D
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from matplotlib.text import Text
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from matplotlib.font_manager import FontProperties
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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mpl.rcParams.update(mpl.rcParamsDefault)
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cpu_frequency = 0
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data = defaultdict(lambda: [])
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hostname = None
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for fn in sys.argv[1:]:
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d = json.load(open(fn))
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cpu_frequency = d["context"]["mhz_per_cpu"]
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# make sure we don't compare benchmarks from different computers
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if hostname is None:
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hostname = d["context"]["host_name"]
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else:
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assert hostname == d["context"]["host_name"]
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for bench in d["benchmarks"]:
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name = bench["name"]
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time = min(bench["cpu_time"], bench["real_time"])
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m = re.match("fill_(n_)?([0-9])d<([^>]+)>", name)
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if m.group(1):
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time /= 1 << 15
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tags = m.group(3).split(", ")
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dim = int(m.group(2))
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label = re.search(
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"fill_([a-z]+)", os.path.splitext(os.path.split(fn)[1])[0]
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).group(1)
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dist = tags[0]
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if len(tags) > 1 and tags[1] in ("dynamic_tag", "static_tag"):
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if len(tags) == 3 and "DStore" in tags[2]:
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continue
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label += "-" + {"dynamic_tag": "dyn", "static_tag": "sta"}[tags[1]]
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label += "-fill" if m.group(1) else "-call"
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data[dim].append((label, dist, time / dim))
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time_per_cycle_in_ns = 1.0 / (cpu_frequency * 1e6) / 1e-9
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plt.figure(figsize=(7, 6))
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i = 0
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for dim in sorted(data):
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v = data[dim]
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labels = OrderedDict()
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for label, dist, time in v:
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if label in labels:
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labels[label][dist] = time / time_per_cycle_in_ns
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else:
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labels[label] = {dist: time / time_per_cycle_in_ns}
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j = 0
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for label, d in labels.items():
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t1 = d["uniform"]
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t2 = d["normal"]
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i -= 1
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z = float(j) / len(labels)
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col = (1.0 - z) * np.array((1.0, 0.0, 0.0)) + z * np.array((1.0, 1.0, 0.0))
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if label == "root":
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col = "k"
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label = "ROOT 6"
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if "numpy" in label:
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col = "0.6"
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if "gsl" in label:
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col = "0.3"
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label = "GSL"
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tmin = min(t1, t2)
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tmax = max(t1, t2)
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r1 = Rectangle((0, i), tmax, 1, facecolor=col)
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r2 = Rectangle(
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(tmin, i), tmax - tmin, 1, facecolor="none", edgecolor="w", hatch="//////"
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)
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plt.gca().add_artist(r1)
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plt.gca().add_artist(r2)
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font = FontProperties(size=9)
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tx = Text(
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-0.5,
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i + 0.5,
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"%s" % label,
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fontproperties=font,
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va="center",
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ha="right",
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clip_on=False,
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)
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plt.gca().add_artist(tx)
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j += 1
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i -= 1
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font = FontProperties()
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font.set_weight("bold")
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tx = Text(
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-0.5,
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i + 0.6,
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"%iD" % dim,
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fontproperties=font,
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va="center",
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ha="right",
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clip_on=False,
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)
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plt.gca().add_artist(tx)
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plt.ylim(0, i)
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plt.xlim(0, 80)
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from matplotlib.ticker import MultipleLocator
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plt.gca().xaxis.set_major_locator(MultipleLocator(5))
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plt.tick_params("y", left=False, labelleft=False)
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plt.xlabel("average CPU cycles per random input value (smaller is better)")
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plt.tight_layout()
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plt.savefig("fill_performance.svg")
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plt.show()
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