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Better script for performance tests

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fmontorsi
2019-08-08 11:18:05 +02:00
parent b66b2857ad
commit 9cdef8aa0c
2 changed files with 70 additions and 36 deletions
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51
perf/generate_graphs.py
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@@ -1,17 +1,21 @@
#!/usr/bin/python
#!/usr/bin/python3
#
# This script assumes that a CSV file produced by "generate_csv.sh" is provided as input
# This script assumes that the set of CSV files produced by "generate_csv.sh" is provided as input
# and that locally there is the "results" folder.
#
# configurable values:
INPUT_FILE_PUSHPULL_TCP_THROUGHPUT="pushpull_tcp_thr_results.csv"
INPUT_FILE_PUSHPULL_INPROC_THROUGHPUT="pushpull_inproc_thr_results.csv"
INPUT_FILE_PUBSUBPROXY_INPROC_THROUGHPUT="pubsubproxy_inproc_thr_results.csv"
INPUT_FILE_REQREP_TCP_LATENCY="reqrep_tcp_lat_results.csv"
INPUT_FILE_PUSHPULL_TCP_THROUGHPUT="results/pushpull_tcp_thr_results.csv"
INPUT_FILE_PUSHPULL_INPROC_THROUGHPUT="results/pushpull_inproc_thr_results.csv"
INPUT_FILE_PUBSUBPROXY_INPROC_THROUGHPUT="results/pubsubproxy_inproc_thr_results.csv"
INPUT_FILE_REQREP_TCP_LATENCY="results/reqrep_tcp_lat_results.csv"
# dependencies
#
# pip3 install matplotlib
#
import matplotlib.pyplot as plt
import numpy as np
@@ -19,31 +23,48 @@ import numpy as np
# functions
def plot_throughput(csv_filename, title):
def plot_throughput(csv_filename, title, force_10gb_limits=False):
message_size_bytes, message_count, pps, mbps = np.loadtxt(csv_filename, delimiter=',', unpack=True)
plt.semilogx(message_size_bytes, pps / 1e6, label='PPS [Mmsg/s]', marker='x')
plt.semilogx(message_size_bytes, mbps / 1e3, label='Throughput [Mb/s]', marker='o')
fig, ax1 = plt.subplots()
# PPS axis
color = 'tab:red'
ax1.set_xlabel('Message size [B]')
ax1.set_ylabel('PPS [Mmsg/s]', color=color)
ax1.semilogx(message_size_bytes, pps / 1e6, label='PPS [Mmsg/s]', marker='x', color=color)
ax1.tick_params(axis='y', labelcolor=color)
# GBPS axis
color = 'tab:blue'
ax2 = ax1.twinx() # instantiate a second axes that shares the same x-axis
ax2.set_ylabel('Throughput [Gb/s]', color=color)
ax2.semilogx(message_size_bytes, mbps / 1e3, label='Throughput [Gb/s]', marker='o')
if force_10gb_limits:
ax2.set_yticks(np.arange(0, 11, 1))
ax2.tick_params(axis='y', labelcolor=color)
ax2.grid(True)
plt.xlabel('Message size [B]')
plt.title(title)
plt.legend()
plt.show()
fig.tight_layout() # otherwise the right y-label is slightly clippe
plt.savefig(csv_filename.replace('.csv', '.png'))
plt.show()
def plot_latency(csv_filename, title):
message_size_bytes, message_count, lat = np.loadtxt(csv_filename, delimiter=',', unpack=True)
plt.semilogx(message_size_bytes, lat, label='Latency [us]', marker='o')
plt.xlabel('Message size [B]')
plt.ylabel('Latency [us]')
plt.grid(True)
plt.title(title)
plt.legend()
plt.show()
plt.savefig(csv_filename.replace('.csv', '.png'))
plt.show()
# main
plot_throughput(INPUT_FILE_PUSHPULL_TCP_THROUGHPUT, 'ZeroMQ PUSH/PULL socket throughput, TCP transport')
plot_throughput(INPUT_FILE_PUSHPULL_TCP_THROUGHPUT, 'ZeroMQ PUSH/PULL socket throughput, TCP transport', force_10gb_limits=True)
plot_throughput(INPUT_FILE_PUSHPULL_INPROC_THROUGHPUT, 'ZeroMQ PUSH/PULL socket throughput, INPROC transport')
plot_throughput(INPUT_FILE_PUBSUBPROXY_INPROC_THROUGHPUT, 'ZeroMQ PUB/SUB PROXY socket throughput, INPROC transport')
plot_latency(INPUT_FILE_REQREP_TCP_LATENCY, 'ZeroMQ REQ/REP socket latency, TCP transport')