numam-dpdk/app/test-crypto-perf/dpdk-graph-crypto-perf.py

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app/crypto-perf: add script to graph perf results The python script introduced in this patch runs the crypto performance test application for various test cases, and graphs the results. Test cases are defined in config JSON files, this is where parameters are specified for each test. Currently there are various test cases for devices crypto_qat, crypto_aesni_mb and crypto_gcm. Tests for the ptest types Throughput and Latency are supported for each. The results of each test case are graphed and saved in PDFs (one PDF for each test suite graph type, with all test cases). The graphs output include various grouped barcharts for throughput tests, and histogram and boxplot graphs are used for latency tests. Documentation is added to outline the configuration and usage for the script. Usage: A JSON config file must be specified when running the script, "./dpdk-graph-crypto-perf <config_file>" The script uses the installed app by default (from ninja install). Alternatively we can pass path to app by "-f <rel_path>/<build_dir>/app/dpdk-test-crypto-perf" All device test suites are run by default. Alternatively we can specify by adding arguments, "-t latency" - to run latency test suite only "-t throughput latency" - to run both throughput and latency test suites A directory can be specified for all output files, or the script directory is used by default. "-o <output_dir>" To see the output from the dpdk-test-crypto-perf app, use the verbose option "-v". Signed-off-by: Ciara Power <ciara.power@intel.com> Acked-by: Declan Doherty <declan.doherty@intel.com> Acked-by: Adam Dybkowski <adamx.dybkowski@intel.com>
2021-01-20 17:29:30 +00:00
#! /usr/bin/env python3
# SPDX-License-Identifier: BSD-3-Clause
# Copyright(c) 2021 Intel Corporation
"""
Script to automate running crypto performance tests for a range of test
cases as configured in the JSON file specified by the user.
The results are processed and output into various graphs in PDF files.
Currently, throughput and latency tests are supported.
"""
import glob
import json
import os
import shutil
import subprocess
from argparse import ArgumentParser
from argparse import ArgumentDefaultsHelpFormatter
import img2pdf
import pandas as pd
import plotly.express as px
SCRIPT_PATH = os.path.dirname(__file__) + "/"
GRAPH_DIR = "temp_graphs"
class Grapher:
"""Grapher object containing all graphing functions. """
def __init__(self, config, suite, graph_path):
self.graph_num = 0
self.graph_path = graph_path
self.suite = suite
self.config = config
self.test = ""
self.ptest = ""
self.data = pd.DataFrame()
def save_graph(self, fig, subdir):
"""
Update figure layout to increase readability, output to JPG file.
"""
path = os.path.join(self.graph_path, subdir, "")
if not os.path.exists(path):
os.makedirs(path)
fig.update_layout(font_size=30, title_x=0.5, title_font={"size": 25},
margin={'t': 300, 'l': 150, 'r': 150, 'b': 150})
fig.write_image(path + "%d.jpg" % self.graph_num)
def boxplot_graph(self, x_axis_label, burst, buffer):
"""Plot a boxplot graph for the given parameters."""
fig = px.box(self.data, x=x_axis_label,
title="Config: " + self.config + "<br>Test Suite: " +
self.suite + "<br>" + self.test +
"<br>(Outliers Included)<br>Burst Size: " + burst +
", Buffer Size: " + buffer,
height=1400, width=2400)
self.save_graph(fig, x_axis_label.replace(' ', '_'))
self.graph_num += 1
def grouped_graph(self, y_axis_label, x_axis_label, color_label):
"""Plot a grouped barchart using the given parameters."""
if (self.data[y_axis_label] == 0).all():
return
fig = px.bar(self.data, x=x_axis_label, color=color_label,
y=y_axis_label,
title="Config: " + self.config + "<br>Test Suite: " +
self.suite + "<br>" + self.test + "<br>"
+ y_axis_label + " for each " + x_axis_label +
"/" + color_label, barmode="group", height=1400,
width=2400)
fig.update_xaxes(type='category')
self.save_graph(fig, y_axis_label.replace(' ', '_'))
self.graph_num += 1
def histogram_graph(self, x_axis_label, burst, buffer):
"""Plot a histogram graph using the given parameters."""
quart1 = self.data[x_axis_label].quantile(0.25)
quart3 = self.data[x_axis_label].quantile(0.75)
inter_quart_range = quart3 - quart1
data_out = self.data[~((self.data[x_axis_label] <
(quart1 - 1.5 * inter_quart_range)) |
(self.data[x_axis_label] >
(quart3 + 1.5 * inter_quart_range)))]
fig = px.histogram(data_out, x=x_axis_label,
title="Config: " + self.config + "<br>Test Suite: "
+ self.suite + "<br>" + self.test
+ "<br>(Outliers removed using Interquartile Range)"
+ "<br>Burst Size: " + burst + ", Buffer Size: " +
buffer, height=1400, width=2400)
max_val = data_out[x_axis_label].max()
min_val = data_out[x_axis_label].min()
fig.update_traces(xbins=dict(
start=min_val,
end=max_val,
size=(max_val - min_val) / 200
))
self.save_graph(fig, x_axis_label.replace(' ', '_'))
self.graph_num += 1
def cleanup_throughput_datatypes(data):
"""Cleanup data types of throughput test results dataframe. """
data.columns = data.columns.str.replace('/', ' ')
data.columns = data.columns.str.strip()
data['Burst Size'] = data['Burst Size'].astype('category')
data['Buffer Size(B)'] = data['Buffer Size(B)'].astype('category')
data['Failed Enq'] = data['Failed Enq'].astype('int')
data['Throughput(Gbps)'] = data['Throughput(Gbps)'].astype('float')
data['Ops(Millions)'] = data['Ops(Millions)'].astype('float')
data['Cycles Buf'] = data['Cycles Buf'].astype('float')
return data
def cleanup_latency_datatypes(data):
"""Cleanup data types of latency test results dataframe. """
data.columns = data.columns.str.strip()
data = data[['Burst Size', 'Buffer Size', 'time (us)']].copy()
data['Burst Size'] = data['Burst Size'].astype('category')
data['Buffer Size'] = data['Buffer Size'].astype('category')
data['time (us)'] = data['time (us)'].astype('float')
return data
def process_test_results(grapher, data):
"""
Process results from the test case,
calling graph functions to output graph images.
"""
if grapher.ptest == "throughput":
grapher.data = cleanup_throughput_datatypes(data)
for y_label in ["Throughput(Gbps)", "Ops(Millions)",
"Cycles Buf", "Failed Enq"]:
grapher.grouped_graph(y_label, "Buffer Size(B)",
"Burst Size")
elif grapher.ptest == "latency":
clean_data = cleanup_latency_datatypes(data)
for (burst, buffer), group in clean_data.groupby(['Burst Size',
'Buffer Size']):
grapher.data = group
grapher.histogram_graph("time (us)", burst, buffer)
grapher.boxplot_graph("time (us)", burst, buffer)
else:
print("Invalid ptest")
return
def create_results_pdf(graph_path, pdf_path):
"""Output results graphs to PDFs."""
if not os.path.exists(pdf_path):
os.makedirs(pdf_path)
for _, dirs, _ in os.walk(graph_path):
for sub in dirs:
graphs = sorted(glob.glob(os.path.join(graph_path, sub, "*.jpg")),
key=(lambda x: int((x.rsplit('/', 1)[1])
.split('.')[0])))
if graphs:
with open(pdf_path + "%s_results.pdf" % sub, "wb") as pdf_file:
pdf_file.write(img2pdf.convert(graphs))
def run_test(test_cmd, test, grapher, params, verbose):
"""Run performance test app for the given test case parameters."""
process = subprocess.Popen(["stdbuf", "-oL", test_cmd] + params,
universal_newlines=True,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
rows = []
if verbose:
print("\n\tOutput for " + test + ":")
while process.poll() is None:
line = process.stdout.readline().strip()
if not line:
continue
if verbose:
print("\t\t>>" + line)
if line.replace(' ', '').startswith('#lcore'):
columns = line[1:].split(',')
elif line[0].isdigit():
line = line.replace(';', ',')
rows.append(line.split(','))
else:
continue
if process.poll() != 0 or not columns or not rows:
print("\n\t" + test + ": FAIL")
return
data = pd.DataFrame(rows, columns=columns)
grapher.test = test
process_test_results(grapher, data)
print("\n\t" + test + ": OK")
return
def parse_parameters(config_parameters):
"""Convert the JSON config to list of strings."""
params = []
for (key, val) in config_parameters:
if isinstance(val, bool):
params.append("--" + key if val is True else "")
elif len(key) == 1:
params.append("-" + key)
params.append(val)
else:
params.append("--" + key + "=" + val)
return params
app/crypto-perf: add script to graph perf results The python script introduced in this patch runs the crypto performance test application for various test cases, and graphs the results. Test cases are defined in config JSON files, this is where parameters are specified for each test. Currently there are various test cases for devices crypto_qat, crypto_aesni_mb and crypto_gcm. Tests for the ptest types Throughput and Latency are supported for each. The results of each test case are graphed and saved in PDFs (one PDF for each test suite graph type, with all test cases). The graphs output include various grouped barcharts for throughput tests, and histogram and boxplot graphs are used for latency tests. Documentation is added to outline the configuration and usage for the script. Usage: A JSON config file must be specified when running the script, "./dpdk-graph-crypto-perf <config_file>" The script uses the installed app by default (from ninja install). Alternatively we can pass path to app by "-f <rel_path>/<build_dir>/app/dpdk-test-crypto-perf" All device test suites are run by default. Alternatively we can specify by adding arguments, "-t latency" - to run latency test suite only "-t throughput latency" - to run both throughput and latency test suites A directory can be specified for all output files, or the script directory is used by default. "-o <output_dir>" To see the output from the dpdk-test-crypto-perf app, use the verbose option "-v". Signed-off-by: Ciara Power <ciara.power@intel.com> Acked-by: Declan Doherty <declan.doherty@intel.com> Acked-by: Adam Dybkowski <adamx.dybkowski@intel.com>
2021-01-20 17:29:30 +00:00
def run_test_suite(test_cmd, suite_config, verbose):
"""Parse test cases for the test suite and run each test."""
print("\nRunning Test Suite: " + suite_config['suite'])
graph_path = os.path.join(suite_config['output_path'], GRAPH_DIR,
suite_config['suite'], "")
grapher = Grapher(suite_config['config_name'], suite_config['suite'],
graph_path)
test_cases = suite_config['test_cases']
if 'default' not in test_cases:
print("Test Suite must contain default case, skipping")
return
default_params = parse_parameters(test_cases['default']['eal'].items())
app/crypto-perf: add script to graph perf results The python script introduced in this patch runs the crypto performance test application for various test cases, and graphs the results. Test cases are defined in config JSON files, this is where parameters are specified for each test. Currently there are various test cases for devices crypto_qat, crypto_aesni_mb and crypto_gcm. Tests for the ptest types Throughput and Latency are supported for each. The results of each test case are graphed and saved in PDFs (one PDF for each test suite graph type, with all test cases). The graphs output include various grouped barcharts for throughput tests, and histogram and boxplot graphs are used for latency tests. Documentation is added to outline the configuration and usage for the script. Usage: A JSON config file must be specified when running the script, "./dpdk-graph-crypto-perf <config_file>" The script uses the installed app by default (from ninja install). Alternatively we can pass path to app by "-f <rel_path>/<build_dir>/app/dpdk-test-crypto-perf" All device test suites are run by default. Alternatively we can specify by adding arguments, "-t latency" - to run latency test suite only "-t throughput latency" - to run both throughput and latency test suites A directory can be specified for all output files, or the script directory is used by default. "-o <output_dir>" To see the output from the dpdk-test-crypto-perf app, use the verbose option "-v". Signed-off-by: Ciara Power <ciara.power@intel.com> Acked-by: Declan Doherty <declan.doherty@intel.com> Acked-by: Adam Dybkowski <adamx.dybkowski@intel.com>
2021-01-20 17:29:30 +00:00
default_params.append("--")
default_params += parse_parameters(test_cases['default']['app'].items())
app/crypto-perf: add script to graph perf results The python script introduced in this patch runs the crypto performance test application for various test cases, and graphs the results. Test cases are defined in config JSON files, this is where parameters are specified for each test. Currently there are various test cases for devices crypto_qat, crypto_aesni_mb and crypto_gcm. Tests for the ptest types Throughput and Latency are supported for each. The results of each test case are graphed and saved in PDFs (one PDF for each test suite graph type, with all test cases). The graphs output include various grouped barcharts for throughput tests, and histogram and boxplot graphs are used for latency tests. Documentation is added to outline the configuration and usage for the script. Usage: A JSON config file must be specified when running the script, "./dpdk-graph-crypto-perf <config_file>" The script uses the installed app by default (from ninja install). Alternatively we can pass path to app by "-f <rel_path>/<build_dir>/app/dpdk-test-crypto-perf" All device test suites are run by default. Alternatively we can specify by adding arguments, "-t latency" - to run latency test suite only "-t throughput latency" - to run both throughput and latency test suites A directory can be specified for all output files, or the script directory is used by default. "-o <output_dir>" To see the output from the dpdk-test-crypto-perf app, use the verbose option "-v". Signed-off-by: Ciara Power <ciara.power@intel.com> Acked-by: Declan Doherty <declan.doherty@intel.com> Acked-by: Adam Dybkowski <adamx.dybkowski@intel.com>
2021-01-20 17:29:30 +00:00
if 'ptest' not in test_cases['default']['app']:
print("Test Suite must contain default ptest value, skipping")
return
grapher.ptest = test_cases['default']['app']['ptest']
for (test, params) in {k: v for (k, v) in test_cases.items() if
k != "default"}.items():
extra_params = parse_parameters(params.items())
app/crypto-perf: add script to graph perf results The python script introduced in this patch runs the crypto performance test application for various test cases, and graphs the results. Test cases are defined in config JSON files, this is where parameters are specified for each test. Currently there are various test cases for devices crypto_qat, crypto_aesni_mb and crypto_gcm. Tests for the ptest types Throughput and Latency are supported for each. The results of each test case are graphed and saved in PDFs (one PDF for each test suite graph type, with all test cases). The graphs output include various grouped barcharts for throughput tests, and histogram and boxplot graphs are used for latency tests. Documentation is added to outline the configuration and usage for the script. Usage: A JSON config file must be specified when running the script, "./dpdk-graph-crypto-perf <config_file>" The script uses the installed app by default (from ninja install). Alternatively we can pass path to app by "-f <rel_path>/<build_dir>/app/dpdk-test-crypto-perf" All device test suites are run by default. Alternatively we can specify by adding arguments, "-t latency" - to run latency test suite only "-t throughput latency" - to run both throughput and latency test suites A directory can be specified for all output files, or the script directory is used by default. "-o <output_dir>" To see the output from the dpdk-test-crypto-perf app, use the verbose option "-v". Signed-off-by: Ciara Power <ciara.power@intel.com> Acked-by: Declan Doherty <declan.doherty@intel.com> Acked-by: Adam Dybkowski <adamx.dybkowski@intel.com>
2021-01-20 17:29:30 +00:00
run_test(test_cmd, test, grapher, default_params + extra_params,
verbose)
create_results_pdf(graph_path, os.path.join(suite_config['output_path'],
suite_config['suite'], ""))
def parse_args():
"""Parse command-line arguments passed to script."""
parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter)
parser.add_argument('config_path', type=str,
help="Path to JSON configuration file")
parser.add_argument('-t', '--test-suites', nargs='+', default=["all"],
help="List of test suites to run")
parser.add_argument('-v', '--verbose', action='store_true',
help="""Display perf test app output.
Not recommended for latency tests.""")
parser.add_argument('-f', '--file-path',
default=shutil.which('dpdk-test-crypto-perf'),
help="Path for perf test app")
parser.add_argument('-o', '--output-path', default=SCRIPT_PATH,
help="Path to store output directories")
args = parser.parse_args()
return (args.file_path, args.test_suites, args.config_path,
args.output_path, args.verbose)
def main():
"""
Load JSON config and call relevant functions to run chosen test suites.
"""
test_cmd, test_suites, config_file, output_path, verbose = parse_args()
if test_cmd is None or not os.path.isfile(test_cmd):
print("Invalid filepath for perf test app!")
return
try:
with open(config_file) as conf:
test_suite_ops = json.load(conf)
config_name = os.path.splitext(config_file)[0]
if '/' in config_name:
config_name = config_name.rsplit('/', 1)[1]
output_path = os.path.join(output_path, config_name, "")
print("Using config: " + config_file)
except OSError as err:
print("Error with JSON file path: " + err.strerror)
return
except json.decoder.JSONDecodeError as err:
print("Error loading JSON config: " + err.msg)
return
if test_suites != ["all"]:
suite_list = []
for (suite, test_cases) in {k: v for (k, v) in test_suite_ops.items()
if k in test_suites}.items():
suite_list.append(suite)
suite_config = {'config_name': config_name, 'suite': suite,
'test_cases': test_cases,
'output_path': output_path}
run_test_suite(test_cmd, suite_config, verbose)
if not suite_list:
print("No valid test suites chosen!")
return
else:
for (suite, test_cases) in test_suite_ops.items():
suite_config = {'config_name': config_name, 'suite': suite,
'test_cases': test_cases,
'output_path': output_path}
run_test_suite(test_cmd, suite_config, verbose)
graph_path = os.path.join(output_path, GRAPH_DIR, "")
if os.path.exists(graph_path):
shutil.rmtree(graph_path)
if __name__ == "__main__":
main()