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#!/usr/bin/env python3
#
# Copyright 2018 Ettus Research, A National Instruments Company
#
# SPDX-License-Identifier: LGPL-3.0-or-later
#
# Description
# Parses the output files generated by crossbar_tb and outputs
# a load-latency graph and a expected-actual throughput graph
import os, sys
import argparse
import time
import glob
import csv
import re
import numpy as np
import matplotlib
#matplotlib.use('Agg')
import matplotlib.pyplot as plt
def get_options():
parser = argparse.ArgumentParser(description='Generate Load Latency Graphs')
parser.add_argument('datadir', type=str, default='.', help='Location of packet capture files generated by testbench')
return parser.parse_args()
TRAFFIC_PATTERNS = {'U':'UNIFORM', 'O':'UNIFORM_OTHERS', 'N':'NEIGHBOR', 'L':'LOOPBACK', 'S':'SEQUENTIAL', 'C':'BIT_COMPLEMENT', 'R':'RANDOM_PERM'}
class InfoFile():
def __init__(self, filename):
# Extract test info from filename
m = re.search(r".*/info_inj([0-9]+)_lpp([0-9]+)_traffic(.)_sess([0-9]+)\.csv", filename)
if m is None:
raise ValueError('Incorrect filename format: %s'%(filename))
self.inj_rate = int(m.group(1))
self.lpp = int(m.group(2))
self.traffic_patt = TRAFFIC_PATTERNS[m.group(3)]
self.session = int(m.group(4))
self.tx_pkts = 0
self.rx_pkts = 0
self.duration = 0
self.errs = 0
self.nodes = 0
with open(filename, 'r') as csvfile:
reader = csv.reader(csvfile, delimiter=',')
isheader = True
for row in reader:
if isheader:
isheader = False
if row != ['Impl', 'Node', 'TxPkts', 'RxPkts', 'Duration', 'ErrRoute', 'ErrData']:
raise ValueError('Incorrect header: %s'%(filename))
else:
self.impl = row[0]
self.tx_pkts = self.tx_pkts + int(row[2])
self.rx_pkts = self.tx_pkts + int(row[3])
self.duration = self.duration + int(row[4])
self.errs = self.errs + int(row[5]) + int(row[6])
self.nodes = self.nodes + 1
self.real_inj_rate = (100.0 * self.tx_pkts * self.lpp) / self.duration
class PktFile():
def __init__(self, filename):
# Extract test info from filename
m = re.search(r".*/pkts_node([0-9]+)_inj([0-9]+)_lpp([0-9]+)_traffic(.)_sess([0-9]+)\.csv", filename)
if m is None:
raise ValueError('Incorrect filename format: %s'%(filename))
self.node = int(m.group(1))
self.inj_rate = int(m.group(2))
self.lpp = int(m.group(3))
self.traffic_patt = TRAFFIC_PATTERNS[m.group(4)]
self.session = int(m.group(5))
self.latencies = []
with open(filename, 'r') as csvfile:
reader = csv.reader(csvfile, delimiter=',')
isheader = True
for row in reader:
if isheader:
isheader = False
if row != ['Src', 'Dst', 'Seqno', 'Error', 'Latency']:
raise ValueError('Incorrect header: %s'%(filename))
else:
self.latencies.append(int(row[4]))
########################################################################
# main
########################################################################
if __name__=='__main__':
options = get_options()
if (not os.path.isdir(options.datadir)):
print('ERROR: Data director %s does not exist'%(options.datadir))
sys.exit(1)
info_db = dict()
info_files = glob.glob(os.path.join(options.datadir, 'info*.csv'))
router_impl = ''
lines_per_pkt = 0
for ifile in info_files:
print('INFO: Reading %s...'%(ifile))
tmp = InfoFile(ifile)
router_impl = tmp.impl # Assume that all files have the same impl
lines_per_pkt = tmp.lpp # Assume that all files have the same LPP
info_db[(tmp.lpp, tmp.traffic_patt, tmp.inj_rate)] = tmp
pkt_db = dict()
pkts_files = glob.glob(os.path.join(options.datadir, 'pkts*.csv'))
for pfile in pkts_files:
print('INFO: Reading %s...'%(pfile))
tmp = PktFile(pfile)
config_key = (tmp.lpp, tmp.traffic_patt)
if config_key not in pkt_db:
pkt_db[config_key] = dict()
if tmp.inj_rate not in pkt_db[config_key]:
pkt_db[config_key][tmp.inj_rate] = []
pkt_db[config_key][tmp.inj_rate].extend(tmp.latencies)
# Write load-latency plots to file
actual_inj_rate_db = dict()
for config in sorted(pkt_db):
(lpp, traffic_patt) = config
ll_file = 'load-latency_%s_traffic-%s_lpp-%d.png'%(router_impl, traffic_patt, lpp)
print('INFO: Writing file ' + ll_file + '...')
percentile = [0, 25, 50, 75, 90, 95, 99, 99.9, 100]
plt.figure()
plt.title('Load Latency Graph for %s\n(Traffic: %s, LPP: %d)'%(router_impl, traffic_patt, lpp))
for p in percentile:
plot_data = dict()
for inj_rate in pkt_db[config]:
real_inj_rate = info_db[(lpp, traffic_patt, inj_rate)].real_inj_rate
plot_data[real_inj_rate] = np.percentile(pkt_db[config][inj_rate], p)
latencies = []
rates = []
for inj_rate in sorted(plot_data):
rates.append(inj_rate)
latencies.append(plot_data[inj_rate])
plt.plot(rates, latencies, label='$P_{%.1f}$'%(p))
plt.xlabel('Load (%)')
plt.xticks(range(0, 110, 10))
plt.ylabel('Latency (cycles)')
plt.grid(True)
plt.legend()
plt.savefig(os.path.join(options.datadir, ll_file), dpi=120)
# Generate actual inj_rate graph
real_inj_rates = []
for inj_rate in sorted(pkt_db[config]):
real_inj_rates.append(info_db[(lpp, traffic_patt, inj_rate)].real_inj_rate)
actual_inj_rate_db[config] = (sorted(pkt_db[config]), real_inj_rates)
# Write offered vs actual injection rate plots to file
injrate_file = 'injection-rate_%s_lpp-%d.png'%(router_impl, lines_per_pkt)
print('INFO: Writing file ' + injrate_file + '...')
plt.figure()
plt.title('Max Injection Rate Graph for %s'%(router_impl))
for config in actual_inj_rate_db:
(x, y) = actual_inj_rate_db[config]
plt.plot(x, y, label=str(config))
plt.xlabel('Offered Injection Rate (%)')
plt.xticks(range(0, 110, 10))
plt.ylabel('Accepted Injection Rate (%)')
plt.yticks(range(0, 110, 10))
plt.grid(True)
plt.legend()
plt.savefig(os.path.join(options.datadir, injrate_file), dpi=120)
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