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Introduce
SegmentQueueSynchronizer
abstraction for synchronization p…
…rimitives and `ReadWriteMutex`
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# To run this script run the command 'python3 scripts/generate_plots_semaphore_jvm.py' in the /benchmarks folder | ||
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import pandas as pd | ||
import sys | ||
import locale | ||
import matplotlib.pyplot as plt | ||
from matplotlib.ticker import FormatStrFormatter | ||
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input_file = "build/reports/jmh/results.csv" | ||
output_file = "out/semaphore_jvm.svg" | ||
# Please change the value of this variable according to the FlowFlattenMergeBenchmarkKt.ELEMENTS | ||
operations = 1000000 | ||
csv_columns = ["Score", "Param: parallelism", "Param: maxPermits", "Param: algo"] | ||
rename_columns = {"Score": "score", "Param: parallelism" : "threads", "Param: maxPermits" : "permits", "Param: algo": "algo"} | ||
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markers = ['v', 'P', 'x', '8', 'd', '1', '2', '8', 'p'] | ||
# markers = ['.', 'v', 'P', 'x', '8', 'd', '1', '2', '8', 'p'] | ||
colours = ["darkorange", "seagreen", "red", "blueviolet", "sienna"] | ||
# colours = ["royalblue", "darkorange", "seagreen", "red", "blueviolet", "sienna"] | ||
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def next_colour(): | ||
i = 0 | ||
while True: | ||
yield colours[i % len(colours)] | ||
i += 1 | ||
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def next_marker(): | ||
i = 0 | ||
while True: | ||
yield markers[i % len(markers)] | ||
i += 1 | ||
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def draw(data, plt): | ||
plt.xscale('log', basex=2) | ||
plt.gca().xaxis.set_major_formatter(FormatStrFormatter('%0.f')) | ||
plt.grid(linewidth='0.5', color='lightgray') | ||
plt.ylabel("us / op") | ||
plt.xlabel('threads') | ||
plt.xticks(data.threads.unique()) | ||
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colour_gen = next_colour() | ||
marker_gen = next_marker() | ||
for algo in data.algo.unique(): | ||
gen_colour = next(colour_gen) | ||
gen_marker = next(marker_gen) | ||
res = data[(data.algo == algo)] | ||
plt.plot(res.threads, res.score * 1000 / operations, label="{}".format(algo), color=gen_colour, marker=gen_marker) | ||
# plt.errorbar(x=res.concurrency, y=res.score*elements/1000, yerr=res.score_error*elements/1000, solid_capstyle='projecting', | ||
# label="flows={}".format(flows), capsize=4, color=gen_colour, linewidth=2.2) | ||
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langlocale = locale.getdefaultlocale()[0] | ||
locale.setlocale(locale.LC_ALL, langlocale) | ||
dp = locale.localeconv()['decimal_point'] | ||
if dp == ",": | ||
csv_columns.append("Score Error (99,9%)") | ||
rename_columns["Score Error (99,9%)"] = "score_error" | ||
elif dp == ".": | ||
csv_columns.append("Score Error (99.9%)") | ||
rename_columns["Score Error (99.9%)"] = "score_error" | ||
else: | ||
print("Unexpected locale delimeter: " + dp) | ||
sys.exit(1) | ||
data = pd.read_csv(input_file, sep=",", decimal=dp) | ||
data = data[csv_columns].rename(columns=rename_columns) | ||
data = data[(data.permits==8)] | ||
data = data[(data.algo!="Java ReentrantLock")] | ||
data = data[(data.algo!="Java Semaphore")] | ||
plt.rcParams.update({'font.size': 15}) | ||
plt.figure(figsize=(12, 12)) | ||
draw(data, plt) | ||
plt.legend(loc='lower center', borderpad=0, bbox_to_anchor=(0.5, 1.3), ncol=2, frameon=False, borderaxespad=2, prop={'size': 15}) | ||
plt.tight_layout(pad=12, w_pad=2, h_pad=1) | ||
plt.savefig(output_file, bbox_inches='tight') |
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