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authorLuc Provoost <luc.provoost@intel.com>2021-04-12 18:18:30 +0200
committerLuc Provoost <luc.provoost@intel.com>2021-04-12 21:04:44 +0200
commite6b54f87766cead3df1f1f5b7099ac6562f6096a (patch)
tree3de6fe4fb5de1a275471b482a76ed3d24ea022a1 /VNFs/DPPD-PROX
parent9efb0fe5411cd3cd4eb7b8a6dbf2645ed18dbd1d (diff)
Code improvements
Rework of some of the code for better readability Change-Id: I559e88faba31d93e593d39cf436f3e114ba4528a Signed-off-by: Luc Provoost <luc.provoost@intel.com>
Diffstat (limited to 'VNFs/DPPD-PROX')
-rw-r--r--VNFs/DPPD-PROX/helper-scripts/rapid/format.yaml42
-rw-r--r--VNFs/DPPD-PROX/helper-scripts/rapid/prox_ctrl.py28
-rw-r--r--VNFs/DPPD-PROX/helper-scripts/rapid/rapid_flowsizetest.py157
-rw-r--r--VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py38
-rw-r--r--VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py283
5 files changed, 268 insertions, 280 deletions
diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/format.yaml b/VNFs/DPPD-PROX/helper-scripts/rapid/format.yaml
index d9c5540..01415ec 100644
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/format.yaml
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/format.yaml
@@ -11,16 +11,17 @@
Flows: Flows
Size: Size
RequestedSpeed: RequestedSpeed
- CoreGenerated: CoreGenerated
- SentByNIC: SentByNIC
- FwdBySUT: FwdBySUT
- RevByCore: RevByCore
- AvgLatency: AvgLatency
- PCTLatency: PCTLatency
- MaxLatency: MaxLatency
- PacketsSent: PacketsSent
- PacketsReceived: PacketsReceived
- PacketsLost: PacketsLost
+ CoreGenerated: pps_req_tx
+ SentByNIC: pps_tx
+ FwdBySUT: pps_sut_tx
+ RevByCore: pps_rx
+ AvgLatency: lat_avg
+ PCTLatency: lat_perc
+ MinLatency: lat_min
+ MaxLatency: lat_max
+ PacketsSent: abs_tx
+ PacketsReceived: abs_rx
+ PacketsLost: abs_dropped
rapid_flowsizetest:
Environment: environment_file
Test: test
@@ -28,21 +29,22 @@ rapid_flowsizetest:
Size: Size
Speed (Mpps):
RequestedSpeed: RequestedSpeed
- CoreGenerated: CoreGenerated
- SentByNIC: SentByNIC
- FwdBySUT: FwdBySUT
- RevByCore: RevByCore
+ CoreGenerated: pps_req_tx
+ SentByNIC: pps_tx
+ FwdBySUT: pps_sut_tx
+ RevByCore: pps_rx
Latency (usec):
- AvgLatency: AvgLatency
- PCTLatency: PCTLatency
- MaxLatency: MaxLatency
+ AvgLatency: lat_avg
+ PCTLatency: lat_perc
+ MinLatency: lat_min
+ MaxLatency: lat_max
Distribution:
bucket_size: bucket_size
buckets: buckets
Absolute Packet Count:
- PacketsSent: PacketsSent
- PacketsReceived: PacketsReceived
- PacketsLost: PacketsLost
+ PacketsSent: abs_tx
+ PacketsReceived: abs_rx
+ PacketsLost: abs_dropped
rapid_irqtest:
Environment: environment_file
Test: test
diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/prox_ctrl.py b/VNFs/DPPD-PROX/helper-scripts/rapid/prox_ctrl.py
index 9f4539c..a9497e1 100644
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/prox_ctrl.py
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/prox_ctrl.py
@@ -198,10 +198,11 @@ class prox_sock(object):
self._send('reset stats')
def lat_stats(self, cores, tasks=[0]):
- min_lat = 999999999
- max_lat = avg_lat = 0
+ result = {}
+ result['lat_min'] = 999999999
+ result['lat_max'] = result['lat_avg'] = 0
number_tasks_returning_stats = 0
- buckets = [0] * 128
+ result['buckets'] = [0] * 128
self._send('lat all stats %s %s' % (','.join(map(str, cores)),
','.join(map(str, tasks))))
for core in cores:
@@ -214,15 +215,15 @@ class prox_sock(object):
(potential incompatibility between scripts and PROX)")
raise Exception("lat stats error")
number_tasks_returning_stats += 1
- min_lat = min(int(stats[0]),min_lat)
- max_lat = max(int(stats[1]),max_lat)
- avg_lat += int(stats[2])
+ result['lat_min'] = min(int(stats[0]),result['lat_min'])
+ result['lat_max'] = max(int(stats[1]),result['lat_max'])
+ result['lat_avg'] += int(stats[2])
#min_since begin = int(stats[3])
#max_since_begin = int(stats[4])
- tsc = int(stats[5]) # Taking the last tsc as the timestamp since
+ result['lat_tsc'] = int(stats[5]) # Taking the last tsc as the timestamp since
# PROX will return the same tsc for each
# core/task combination
- hz = int(stats[6])
+ result['lat_hz'] = int(stats[6])
#coreid = int(stats[7])
#taskid = int(stats[8])
mis_ordered = int(stats[9])
@@ -234,17 +235,18 @@ class prox_sock(object):
reply (potential incompatibility between scripts \
and PROX)")
raise Exception("lat bucket reply error")
- buckets[0] = int(stats[1])
+ result['buckets'][0] = int(stats[1])
for i in range(1, 128):
stats = self._recv().split(':')
- buckets[i] = int(stats[1])
- avg_lat = old_div(avg_lat,number_tasks_returning_stats)
+ result['buckets'][i] = int(stats[1])
+ result['lat_avg'] = old_div(result['lat_avg'],
+ number_tasks_returning_stats)
self._send('stats latency(0).used')
used = float(self._recv())
self._send('stats latency(0).total')
total = float(self._recv())
- return (min_lat, max_lat, avg_lat, (old_div(used,total)), tsc, hz,
- buckets)
+ result['lat_used'] = old_div(used,total)
+ return (result)
def irq_stats(self, core, bucket, task=0):
self._send('stats task.core(%s).task(%s).irq(%s)' %
diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_flowsizetest.py b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_flowsizetest.py
index 042fc8d..d65afd6 100644
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_flowsizetest.py
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_flowsizetest.py
@@ -18,6 +18,7 @@
##
import sys
import time
+import copy
from math import ceil
from statistics import mean
from past.utils import old_div
@@ -99,6 +100,8 @@ class FlowSizeTest(RapidTest):
def run(self):
result_details = {'Details': 'Nothing'}
TestResult = 0
+ end_data = {}
+ iteration_prefix = {}
for imix in self.test['imixs']:
size = mean(imix)
self.gen_machine.set_udp_packet_size(imix)
@@ -119,7 +122,8 @@ class FlowSizeTest(RapidTest):
self.sut_machine.reset_stats()
flow_number = self.gen_machine.set_flows(flow_number)
self.set_background_flows(self.background_machines, flow_number)
- endspeed = None
+# endspeed = None
+ end_data['speed'] = None
speed = self.get_start_speed_and_init(size)
while True:
attempts += 1
@@ -131,137 +135,108 @@ class FlowSizeTest(RapidTest):
self.set_background_speed(self.background_machines, speed)
self.start_background_traffic(self.background_machines)
# Get statistics now that the generation is stable and initial ARP messages are dealt with
- pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg,lat_perc , lat_perc_max, lat_max, abs_tx,abs_rx,abs_dropped, abs_tx_fail, drop_rate, lat_min, lat_used, r, actual_duration, avg_bg_rate, bucket_size, buckets = self.run_iteration(float(self.test['runtime']),flow_number,size,speed)
+ iteration_data = self.run_iteration(
+ float(self.test['runtime']),flow_number,size,speed)
+ iteration_data['speed'] = speed
self.stop_background_traffic(self.background_machines)
- if r > 1:
- retry_warning = bcolors.WARNING + ' {:1} retries needed'.format(r) + bcolors.ENDC
+ if iteration_data['r'] > 1:
+ retry_warning = bcolors.WARNING + ' {:1} retries needed'.format(iteration_data['r']) + bcolors.ENDC
else:
retry_warning = ''
# Drop rate is expressed in percentage. lat_used is a ratio (0 to 1). The sum of these 2 should be 100%.
# If the sum is lower than 95, it means that more than 5% of the latency measurements where dropped for accuracy reasons.
- if (drop_rate + lat_used * 100) < 95:
- lat_warning = bcolors.WARNING + ' Latency accuracy issue?: {:>3.0f}%'.format(lat_used*100) + bcolors.ENDC
+ if (iteration_data['drop_rate'] + iteration_data['lat_used'] * 100) < 95:
+ lat_warning = bcolors.WARNING + ' Latency accuracy issue?: {:>3.0f}%'.format(iteration_data['lat_used']*100) + bcolors.ENDC
else:
lat_warning = ''
+ iteration_prefix = {'speed' : bcolors.ENDC,
+ 'lat_avg' : bcolors.ENDC,
+ 'lat_perc' : bcolors.ENDC,
+ 'lat_max' : bcolors.ENDC,
+ 'abs_drop_rate' : bcolors.ENDC,
+ 'drop_rate' : bcolors.ENDC}
if self.test['test'] == 'fixed_rate':
- endspeed = speed
- endpps_req_tx = None
- endpps_tx = None
- endpps_sut_tx = None
- endpps_rx = None
- endlat_avg = lat_avg
- endlat_perc = lat_perc
- endlat_perc_max = lat_perc_max
- endlat_max = lat_max
- endbuckets = buckets
- endabs_dropped = abs_dropped
- enddrop_rate = drop_rate
- endabs_tx = abs_tx
- endabs_rx = abs_rx
- endavg_bg_rate = avg_bg_rate
+ end_data = copy.deepcopy(iteration_data)
+ end_prefix = copy.deepcopy(iteration_prefix)
if lat_warning or retry_warning:
endwarning = '| | {:177.177} |'.format(retry_warning + lat_warning)
success = True
- TestResult = TestResult + pps_rx # fixed rate testing result is strange: we just report the pps received
- speed_prefix = lat_avg_prefix = lat_perc_prefix = lat_max_prefix = abs_drop_rate_prefix = drop_rate_prefix = bcolors.ENDC
+ #TestResult = TestResult + iteration_data['pps_rx'] # fixed rate testing result is strange: we just report the pps received
# The following if statement is testing if we pass the success criteria of a certain drop rate, average latency and maximum latency below the threshold
# The drop rate success can be achieved in 2 ways: either the drop rate is below a treshold, either we want that no packet has been lost during the test
# This can be specified by putting 0 in the .test file
- elif ((drop_rate < self.test['drop_rate_threshold']) or (abs_dropped==self.test['drop_rate_threshold']==0)) and (lat_avg< self.test['lat_avg_threshold']) and (lat_perc< self.test['lat_perc_threshold']) and (lat_max < self.test['lat_max_threshold']):
- if (old_div((self.get_pps(speed,size) - pps_tx),self.get_pps(speed,size)))>0.01:
- speed_prefix = bcolors.WARNING
- if abs_tx_fail > 0:
- gen_warning = bcolors.WARNING + ' Network limit?: requesting {:<.3f} Mpps and getting {:<.3f} Mpps - {} failed to be transmitted'.format(self.get_pps(speed,size), pps_tx, abs_tx_fail) + bcolors.ENDC
+ elif ((iteration_data['drop_rate'] < self.test['drop_rate_threshold']) or (iteration_data['abs_dropped']==self.test['drop_rate_threshold']==0)) and (iteration_data['lat_avg']< self.test['lat_avg_threshold']) and (iteration_data['lat_perc']< self.test['lat_perc_threshold']) and (iteration_data['lat_max'] < self.test['lat_max_threshold']):
+ if (old_div((self.get_pps(speed,size) - iteration_data['pps_tx']),self.get_pps(speed,size)))>0.01:
+ iteration_prefix['speed'] = bcolors.WARNING
+ if iteration_data['abs_tx_fail'] > 0:
+ gen_warning = bcolors.WARNING + ' Network limit?: requesting {:<.3f} Mpps and getting {:<.3f} Mpps - {} failed to be transmitted'.format(self.get_pps(speed,size), iteration_data['pps_tx'], iteration_data['abs_tx_fail']) + bcolors.ENDC
else:
- gen_warning = bcolors.WARNING + ' Generator limit?: requesting {:<.3f} Mpps and getting {:<.3f} Mpps'.format(self.get_pps(speed,size), pps_tx) + bcolors.ENDC
+ gen_warning = bcolors.WARNING + ' Generator limit?: requesting {:<.3f} Mpps and getting {:<.3f} Mpps'.format(self.get_pps(speed,size), iteration_data['pps_tx']) + bcolors.ENDC
else:
- speed_prefix = bcolors.ENDC
+ iteration_prefix['speed'] = bcolors.ENDC
gen_warning = ''
- endspeed = speed
- endspeed_prefix = speed_prefix
- endpps_req_tx = pps_req_tx
- endpps_tx = pps_tx
- endpps_sut_tx = pps_sut_tx
- endpps_rx = pps_rx
- endlat_avg = lat_avg
- endlat_perc = lat_perc
- endlat_perc_max = lat_perc_max
- endlat_max = lat_max
- endbuckets = buckets
- endabs_dropped = None
- enddrop_rate = drop_rate
- endabs_tx = abs_tx
- endabs_rx = abs_rx
- endavg_bg_rate = avg_bg_rate
+ end_data = copy.deepcopy(iteration_data)
+ end_prefix = copy.deepcopy(iteration_prefix)
+ end_data['abs_dropped'] = None
if lat_warning or gen_warning or retry_warning:
endwarning = '| | {:186.186} |'.format(retry_warning + lat_warning + gen_warning)
success = True
success_message=' SUCCESS'
- speed_prefix = lat_avg_prefix = lat_perc_prefix = lat_max_prefix = abs_drop_rate_prefix = drop_rate_prefix = bcolors.ENDC
- RapidLog.debug(self.report_result(-attempts,size,speed,pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg,lat_perc,lat_perc_max,lat_max,abs_tx,abs_rx,abs_dropped,actual_duration,speed_prefix,lat_avg_prefix,lat_max_prefix,abs_drop_rate_prefix,drop_rate_prefix)+ success_message + retry_warning + lat_warning + gen_warning)
+ RapidLog.debug(self.report_result(-attempts, size,
+ iteration_data, iteration_prefix) + success_message +
+ retry_warning + lat_warning + gen_warning)
else:
success_message=' FAILED'
- abs_drop_rate_prefix = bcolors.ENDC
- if ((abs_dropped>0) and (self.test['drop_rate_threshold'] ==0)):
- abs_drop_rate_prefix = bcolors.FAIL
- if (drop_rate < self.test['drop_rate_threshold']):
- drop_rate_prefix = bcolors.ENDC
+ if ((iteration_data['abs_dropped']>0) and (self.test['drop_rate_threshold'] ==0)):
+ iteration_prefix['abs_drop_rate'] = bcolors.FAIL
+ if (iteration_data['drop_rate'] < self.test['drop_rate_threshold']):
+ iteration_prefix['drop_rate'] = bcolors.ENDC
else:
- drop_rate_prefix = bcolors.FAIL
- if (lat_avg< self.test['lat_avg_threshold']):
- lat_avg_prefix = bcolors.ENDC
+ iteration_prefix['drop_rate'] = bcolors.FAIL
+ if (iteration_data['lat_avg']< self.test['lat_avg_threshold']):
+ iteration_prefix['lat_avg'] = bcolors.ENDC
else:
- lat_avg_prefix = bcolors.FAIL
- if (lat_perc< self.test['lat_perc_threshold']):
- lat_perc_prefix = bcolors.ENDC
+ iteration_prefix['lat_avg'] = bcolors.FAIL
+ if (iteration_data['lat_perc']< self.test['lat_perc_threshold']):
+ iteration_prefix['lat_perc'] = bcolors.ENDC
else:
- lat_perc_prefix = bcolors.FAIL
- if (lat_max< self.test['lat_max_threshold']):
- lat_max_prefix = bcolors.ENDC
+ iteration_prefix['lat_perc'] = bcolors.FAIL
+ if (iteration_data['lat_max']< self.test['lat_max_threshold']):
+ iteration_prefix['lat_max'] = bcolors.ENDC
else:
- lat_max_prefix = bcolors.FAIL
- if ((old_div((self.get_pps(speed,size) - pps_tx),self.get_pps(speed,size)))<0.001):
- speed_prefix = bcolors.ENDC
+ iteration_prefix['lat_max'] = bcolors.FAIL
+ if ((old_div((self.get_pps(speed,size) - iteration_data['pps_tx']),self.get_pps(speed,size)))<0.001):
+ iteration_prefix['speed'] = bcolors.ENDC
else:
- speed_prefix = bcolors.FAIL
+ iteration_prefix['speed'] = bcolors.FAIL
success = False
- RapidLog.debug(self.report_result(-attempts,size,speed,pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg,lat_perc,lat_perc_max,lat_max,abs_tx,abs_rx,abs_dropped,actual_duration,speed_prefix,lat_avg_prefix,lat_perc_prefix,lat_max_prefix,abs_drop_rate_prefix,drop_rate_prefix)+ success_message + retry_warning + lat_warning)
+ RapidLog.debug(self.report_result(-attempts, size,
+ iteration_data, iteration_prefix) +
+ success_message + retry_warning + lat_warning)
speed = self.new_speed(speed, size, success)
if self.test['test'] == 'increment_till_fail':
if not success:
break
elif self.resolution_achieved():
break
- if endspeed is not None:
- speed_prefix = lat_avg_prefix = lat_perc_prefix = lat_max_prefix = abs_drop_rate_prefix = drop_rate_prefix = bcolors.ENDC
- RapidLog.info(self.report_result(flow_number,size,endspeed,endpps_req_tx,endpps_tx,endpps_sut_tx,endpps_rx,endlat_avg,endlat_perc,endlat_perc_max,endlat_max,endabs_tx,endabs_rx,endabs_dropped,actual_duration,speed_prefix,lat_avg_prefix,lat_perc_prefix,lat_max_prefix,abs_drop_rate_prefix,drop_rate_prefix))
- if endavg_bg_rate:
- tot_avg_rx_rate = endpps_rx + (endavg_bg_rate * len(self.background_machines))
+ if end_data['speed'] is not None:
+ RapidLog.info(self.report_result(flow_number, size,
+ end_data, end_prefix))
+ if end_data['avg_bg_rate']:
+ tot_avg_rx_rate = end_data['pps_rx'] + (end_data['avg_bg_rate'] * len(self.background_machines))
endtotaltrafficrate = '| | Total amount of traffic received by all generators during this test: {:>4.3f} Gb/s {:7.3f} Mpps {} |'.format(RapidTest.get_speed(tot_avg_rx_rate,size) , tot_avg_rx_rate, ' '*84)
RapidLog.info (endtotaltrafficrate)
if endwarning:
RapidLog.info (endwarning)
RapidLog.info("+--------+------------------+-------------+-------------+-------------+------------------------+----------+----------+----------+-----------+-----------+-----------+-----------+-------+----+")
if self.test['test'] != 'fixed_rate':
- TestResult = TestResult + endpps_rx
- result_details = {'test': self.test['testname'],
- 'environment_file': self.test['environment_file'],
- 'Flows': flow_number,
- 'Size': size,
- 'RequestedSpeed': RapidTest.get_pps(endspeed,size),
- 'CoreGenerated': endpps_req_tx,
- 'SentByNIC': endpps_tx,
- 'FwdBySUT': endpps_sut_tx,
- 'RevByCore': endpps_rx,
- 'AvgLatency': endlat_avg,
- 'PCTLatency': endlat_perc,
- 'MaxLatency': endlat_max,
- 'PacketsSent': endabs_tx,
- 'PacketsReceived': endabs_rx,
- 'PacketsLost': endabs_dropped,
- 'bucket_size': bucket_size,
- 'buckets': endbuckets}
- result_details = self.post_data('rapid_flowsizetest', result_details)
+ TestResult = TestResult + end_data['pps_rx']
+ end_data['test'] = self.test['testname']
+ end_data['environment_file'] = self.test['environment_file']
+ end_data['Flows'] = flow_number
+ end_data['Size'] = size
+ end_data['RequestedSpeed'] = RapidTest.get_pps(end_data['speed'] ,size)
+ result_details = self.post_data('rapid_flowsizetest', end_data)
else:
RapidLog.info('|{:>7}'.format(str(flow_number))+" | Speed 0 or close to 0")
self.gen_machine.stop_latency_cores()
diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py
index 8dfdc80..ee9ed79 100644
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py
@@ -58,30 +58,38 @@ class ImpairTest(RapidTest):
sys.stdout.flush()
time.sleep(1)
# Get statistics now that the generation is stable and NO ARP messages any more
- pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg, lat_perc, lat_perc_max, lat_max, abs_tx, abs_rx, abs_dropped, abs_tx_fail, drop_rate, lat_min, lat_used, r, actual_duration, _,bucket_size, buckets = self.run_iteration(float(self.test['runtime']),flow_number,size,speed)
+ iteration_data = self.run_iteration(float(self.test['runtime']),flow_number,size,speed)
+ iteration_data['speed'] = speed
# Drop rate is expressed in percentage. lat_used is a ratio (0 to 1). The sum of these 2 should be 100%.
# If the sum is lower than 95, it means that more than 5% of the latency measurements where dropped for accuracy reasons.
- if (drop_rate + lat_used * 100) < 95:
- lat_warning = bcolors.WARNING + ' Latency accuracy issue?: {:>3.0f}%'.format(lat_used*100) + bcolors.ENDC
+ if (iteration_data['drop_rate'] + iteration_data['lat_used'] * 100) < 95:
+ lat_warning = bcolors.WARNING + ' Latency accuracy issue?: {:>3.0f}%'.format(iteration_data['lat_used']*100) + bcolors.ENDC
else:
lat_warning = ''
- RapidLog.info(self.report_result(attempts,size,speed,pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg,lat_perc,lat_perc_max,lat_max,abs_tx,abs_rx,abs_dropped,actual_duration))
+ iteration_prefix = {'speed' : '',
+ 'lat_avg' : '',
+ 'lat_perc' : '',
+ 'lat_max' : '',
+ 'abs_drop_rate' : '',
+ 'drop_rate' : ''}
+ RapidLog.info(self.report_result(attempts, size, iteration_data,
+ iteration_prefix))
result_details = {'test': self.test['test'],
'environment_file': self.test['environment_file'],
'Flows': flow_number,
'Size': size,
'RequestedSpeed': RapidTest.get_pps(speed,size),
- 'CoreGenerated': pps_req_tx,
- 'SentByNIC': pps_tx,
- 'FwdBySUT': pps_sut_tx,
- 'RevByCore': pps_rx,
- 'AvgLatency': lat_avg,
- 'PCTLatency': lat_perc,
- 'MaxLatency': lat_max,
- 'PacketsLost': abs_dropped,
- 'DropRate': drop_rate,
- 'bucket_size': bucket_size,
- 'buckets': buckets}
+ 'CoreGenerated': iteration_data['pps_req_tx'],
+ 'SentByNIC': iteration_data['pps_tx'],
+ 'FwdBySUT': iteration_data['pps_sut_tx'],
+ 'RevByCore': iteration_data['pps_rx'],
+ 'AvgLatency': iteration_data['lat_avg'],
+ 'PCTLatency': iteration_data['lat_perc'],
+ 'MaxLatency': iteration_data['lat_max'],
+ 'PacketsLost': iteration_data['abs_dropped'],
+ 'DropRate': iteration_data['drop_rate'],
+ 'bucket_size': iteration_data['bucket_size'],
+ 'buckets': iteration_data['buckets']}
result_details = self.post_data('rapid_impairtest', result_details)
self.gen_machine.stop_latency_cores()
return (True, result_details)
diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py
index 3c13d1a..b431e5b 100644
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py
@@ -125,64 +125,63 @@ class RapidTest(object):
return (var[test])
@staticmethod
- def report_result(flow_number, size, speed, pps_req_tx, pps_tx, pps_sut_tx,
- pps_rx, lat_avg, lat_perc, lat_perc_max, lat_max, tx, rx, tot_drop,
- elapsed_time,speed_prefix='', lat_avg_prefix='', lat_perc_prefix='',
- lat_max_prefix='', abs_drop_rate_prefix='', drop_rate_prefix=''):
+ def report_result(flow_number, size, data, prefix):
if flow_number < 0:
flow_number_str = '| ({:>4}) |'.format(abs(flow_number))
else:
flow_number_str = '|{:>7} |'.format(flow_number)
- if pps_req_tx is None:
+ if data['pps_req_tx'] is None:
pps_req_tx_str = '{0: >14}'.format(' NA |')
else:
- pps_req_tx_str = '{:>7.3f} Mpps |'.format(pps_req_tx)
- if pps_tx is None:
+ pps_req_tx_str = '{:>7.3f} Mpps |'.format(data['pps_req_tx'])
+ if data['pps_tx'] is None:
pps_tx_str = '{0: >14}'.format(' NA |')
else:
- pps_tx_str = '{:>7.3f} Mpps |'.format(pps_tx)
- if pps_sut_tx is None:
+ pps_tx_str = '{:>7.3f} Mpps |'.format(data['pps_tx'])
+ if data['pps_sut_tx'] is None:
pps_sut_tx_str = '{0: >14}'.format(' NA |')
else:
- pps_sut_tx_str = '{:>7.3f} Mpps |'.format(pps_sut_tx)
- if pps_rx is None:
+ pps_sut_tx_str = '{:>7.3f} Mpps |'.format(data['pps_sut_tx'])
+ if data['pps_rx'] is None:
pps_rx_str = '{0: >25}'.format('NA |')
else:
pps_rx_str = bcolors.OKBLUE + '{:>4.1f} Gb/s |{:7.3f} Mpps {}|'.format(
- RapidTest.get_speed(pps_rx,size),pps_rx,bcolors.ENDC)
- if tot_drop is None:
+ RapidTest.get_speed(data['pps_rx'],size),data['pps_rx'],bcolors.ENDC)
+ if data['abs_dropped'] is None:
tot_drop_str = ' | NA | '
else:
- tot_drop_str = ' | {:>9.0f} | '.format(tot_drop)
- if lat_perc is None:
- lat_perc_str = ' |{:^10.10}|'.format('NA')
- elif lat_perc_max == True:
- lat_perc_str = '|>{}{:>5.0f} us{} |'.format(lat_perc_prefix,
- float(lat_perc), bcolors.ENDC)
+ tot_drop_str = ' | {:>9.0f} | '.format(data['abs_dropped'])
+ if data['lat_perc'] is None:
+ lat_perc_str = '|{:^10.10}|'.format('NA')
+ elif data['lat_perc_max'] == True:
+ lat_perc_str = '|>{}{:>5.0f} us{} |'.format(prefix['lat_perc'],
+ float(data['lat_perc']), bcolors.ENDC)
else:
- lat_perc_str = '| {}{:>5.0f} us{} |'.format(lat_perc_prefix,
- float(lat_perc), bcolors.ENDC)
- if elapsed_time is None:
+ lat_perc_str = '| {}{:>5.0f} us{} |'.format(prefix['lat_perc'],
+ float(data['lat_perc']), bcolors.ENDC)
+ if data['actual_duration'] is None:
elapsed_time_str = ' NA |'
else:
- elapsed_time_str = '{:>3.0f} |'.format(elapsed_time)
- return(flow_number_str + '{:>5.1f}'.format(speed) + '% ' + speed_prefix
- + '{:>6.3f}'.format(RapidTest.get_pps(speed,size)) + ' Mpps|' +
+ elapsed_time_str = '{:>3.0f} |'.format(data['actual_duration'])
+ return(flow_number_str + '{:>5.1f}'.format(data['speed']) + '% ' + prefix['speed']
+ + '{:>6.3f}'.format(RapidTest.get_pps(data['speed'],size)) + ' Mpps|' +
pps_req_tx_str + pps_tx_str + bcolors.ENDC + pps_sut_tx_str +
- pps_rx_str + lat_avg_prefix + ' {:>6.0f}'.format(lat_avg) +
- ' us' + lat_perc_str +lat_max_prefix+'{:>6.0f}'.format(lat_max)
- + ' us | ' + '{:>9.0f}'.format(tx) + ' | {:>9.0f}'.format(rx) +
- ' | '+ abs_drop_rate_prefix+ '{:>9.0f}'.format(tx-rx) +
- tot_drop_str +drop_rate_prefix +
- '{:>5.2f}'.format(100*old_div(float(tx-rx),tx)) + bcolors.ENDC +
+ pps_rx_str + prefix['lat_avg'] + ' {:>6.0f}'.format(data['lat_avg']) +
+ ' us' + lat_perc_str +prefix['lat_max']+'{:>6.0f}'.format(data['lat_max'])
+ + ' us | ' + '{:>9.0f}'.format(data['abs_tx']) + ' | {:>9.0f}'.format(data['abs_rx']) +
+ ' | '+ prefix['abs_drop_rate']+ '{:>9.0f}'.format(data['abs_tx']-data['abs_rx']) +
+ tot_drop_str + prefix['drop_rate'] +
+ '{:>5.2f}'.format(100*old_div(float(data['abs_tx']-data['abs_rx']),data['abs_tx'])) + bcolors.ENDC +
' |' + elapsed_time_str)
-
+
def run_iteration(self, requested_duration, flow_number, size, speed):
BUCKET_SIZE_EXP = self.gen_machine.bucket_size_exp
LAT_PERCENTILE = self.test['lat_percentile']
- r = 0;
+ iteration_data= {}
+ time_loop_data= {}
+ iteration_data['r'] = 0;
sleep_time = 2
- while (r < self.test['maxr']):
+ while (iteration_data['r'] < self.test['maxr']):
self.gen_machine.start_latency_cores()
time.sleep(sleep_time)
# Sleep_time is needed to be able to do accurate measurements to check for packet loss. We need to make this time large enough so that we do not take the first measurement while some packets from the previous tests migth still be in flight
@@ -207,6 +206,7 @@ class RapidTest(object):
self.gen_machine.set_generator_speed(speed)
if self.background_machines:
self.set_background_speed(self.background_machines, speed)
+ iteration_data['speed'] = time_loop_data['speed'] = speed
time.sleep(2) ## Needs to be 2 seconds since this 1 sec is the time that PROX uses to refresh the stats. Note that this can be changed in PROX!! Don't do it.
start_bg_gen_stats = []
for bg_gen_machine in self.background_machines:
@@ -221,66 +221,76 @@ class RapidTest(object):
t2_sut_rx, t2_sut_non_dp_rx, t2_sut_tx, t2_sut_non_dp_tx, t2_sut_drop, t2_sut_tx_fail, t2_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats()
t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc, tsc_hz = self.gen_machine.core_stats()
tx = t2_tx - t1_tx
- dp_tx = tx - (t2_non_dp_tx - t1_non_dp_tx )
- dp_rx = t2_rx - t1_rx - (t2_non_dp_rx - t1_non_dp_rx)
- tot_dp_drop = dp_tx - dp_rx
+ iteration_data['abs_tx'] = tx - (t2_non_dp_tx - t1_non_dp_tx )
+ iteration_data['abs_rx'] = t2_rx - t1_rx - (t2_non_dp_rx - t1_non_dp_rx)
+ iteration_data['abs_dropped'] = iteration_data['abs_tx'] - iteration_data['abs_rx']
if tx == 0:
RapidLog.critical("TX = 0. Test interrupted since no packet has been sent.")
- if dp_tx == 0:
+ if iteration_data['abs_tx'] == 0:
RapidLog.critical("Only non-dataplane packets (e.g. ARP) sent. Test interrupted since no packet has been sent.")
# Ask PROX to calibrate the bucket size once we have a PROX function to do this.
# Measure latency statistics per second
- lat_min, lat_max, lat_avg, used_avg, t2_lat_tsc, lat_hz, buckets = self.gen_machine.lat_stats()
- lat_samples = sum(buckets)
+ iteration_data.update(self.gen_machine.lat_stats())
+ t2_lat_tsc = iteration_data['lat_tsc']
sample_count = 0
- for sample_percentile, bucket in enumerate(buckets,start=1):
+ for sample_percentile, bucket in enumerate(iteration_data['buckets'],start=1):
sample_count += bucket
- if sample_count > (lat_samples * LAT_PERCENTILE):
+ if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE:
break
- percentile_max = (sample_percentile == len(buckets))
- sample_percentile = sample_percentile * float(2 ** BUCKET_SIZE_EXP) / (old_div(float(lat_hz),float(10**6)))
+ iteration_data['lat_perc_max'] = (sample_percentile == len(iteration_data['buckets']))
+ iteration_data['bucket_size'] = float(2 ** BUCKET_SIZE_EXP) / (old_div(float(iteration_data['lat_hz']),float(10**6)))
+ time_loop_data['bucket_size'] = iteration_data['bucket_size']
+ iteration_data['lat_perc'] = sample_percentile * iteration_data['bucket_size']
if self.test['test'] == 'fixed_rate':
- RapidLog.info(self.report_result(flow_number,size,speed,None,None,None,None,lat_avg,sample_percentile,percentile_max,lat_max, dp_tx, dp_rx , None, None))
+ iteration_data['pps_req_tx'] = None
+ iteration_data['pps_tx'] = None
+ iteration_data['pps_sut_tx'] = None
+ iteration_data['pps_rx'] = None
+ iteration_data['lat_perc'] = None
+ iteration_data['actual_duration'] = None
+ iteration_prefix = {'speed' : '',
+ 'lat_avg' : '',
+ 'lat_perc' : '',
+ 'lat_max' : '',
+ 'abs_drop_rate' : '',
+ 'drop_rate' : ''}
+ RapidLog.info(self.report_result(flow_number, size,
+ iteration_data, iteration_prefix ))
tot_rx = tot_non_dp_rx = tot_tx = tot_non_dp_tx = tot_drop = 0
- lat_avg = used_avg = 0
- buckets_total = buckets
- tot_lat_samples = sum(buckets)
+ iteration_data['lat_avg'] = iteration_data['lat_used'] = 0
tot_lat_measurement_duration = float(0)
- tot_core_measurement_duration = float(0)
+ iteration_data['actual_duration'] = float(0)
tot_sut_core_measurement_duration = float(0)
tot_sut_rx = tot_sut_non_dp_rx = tot_sut_tx = tot_sut_non_dp_tx = tot_sut_drop = tot_sut_tx_fail = tot_sut_tsc = 0
lat_avail = core_avail = sut_avail = False
- while (tot_core_measurement_duration - float(requested_duration) <= 0.1) or (tot_lat_measurement_duration - float(requested_duration) <= 0.1):
+ while (iteration_data['actual_duration'] - float(requested_duration) <= 0.1) or (tot_lat_measurement_duration - float(requested_duration) <= 0.1):
time.sleep(0.5)
- lat_min_sample, lat_max_sample, lat_avg_sample, used_sample, t3_lat_tsc, lat_hz, buckets = self.gen_machine.lat_stats()
+ time_loop_data.update(self.gen_machine.lat_stats())
# Get statistics after some execution time
- if t3_lat_tsc != t2_lat_tsc:
- single_lat_measurement_duration = (t3_lat_tsc - t2_lat_tsc) * 1.0 / lat_hz # time difference between the 2 measurements, expressed in seconds.
+ if time_loop_data['lat_tsc'] != t2_lat_tsc:
+ single_lat_measurement_duration = (time_loop_data['lat_tsc'] - t2_lat_tsc) * 1.0 / time_loop_data['lat_hz'] # time difference between the 2 measurements, expressed in seconds.
# A second has passed in between to lat_stats requests. Hence we need to process the results
tot_lat_measurement_duration = tot_lat_measurement_duration + single_lat_measurement_duration
- if lat_min > lat_min_sample:
- lat_min = lat_min_sample
- if lat_max < lat_max_sample:
- lat_max = lat_max_sample
- lat_avg = lat_avg + lat_avg_sample * single_lat_measurement_duration # Sometimes, There is more than 1 second between 2 lat_stats. Hence we will take the latest measurement
- used_avg = used_avg + used_sample * single_lat_measurement_duration # and give it more weigth.
- lat_samples = sum(buckets)
- tot_lat_samples += lat_samples
+ if iteration_data['lat_min'] > time_loop_data['lat_min']:
+ iteration_data['lat_min'] = time_loop_data['lat_min']
+ if iteration_data['lat_max'] < time_loop_data['lat_max']:
+ iteration_data['lat_max'] = time_loop_data['lat_max']
+ iteration_data['lat_avg'] = iteration_data['lat_avg'] + time_loop_data['lat_avg'] * single_lat_measurement_duration # Sometimes, There is more than 1 second between 2 lat_stats. Hence we will take the latest measurement
+ iteration_data['lat_used'] = iteration_data['lat_used'] + time_loop_data['lat_used'] * single_lat_measurement_duration # and give it more weigth.
sample_count = 0
- for sample_percentile, bucket in enumerate(buckets,start=1):
+ for sample_percentile, bucket in enumerate(time_loop_data['buckets'],start=1):
sample_count += bucket
- if sample_count > lat_samples * LAT_PERCENTILE:
+ if sample_count > sum(time_loop_data['buckets']) * LAT_PERCENTILE:
break
- percentile_max = (sample_percentile == len(buckets))
- bucket_size = float(2 ** BUCKET_SIZE_EXP) / (old_div(float(lat_hz),float(10**6)))
- sample_percentile = sample_percentile * bucket_size
- buckets_total = [buckets_total[i] + buckets[i] for i in range(len(buckets_total))]
- t2_lat_tsc = t3_lat_tsc
+ time_loop_data['lat_perc_max'] = (sample_percentile == len(time_loop_data['buckets']))
+ time_loop_data['lat_perc'] = sample_percentile * iteration_data['bucket_size']
+ iteration_data['buckets'] = [iteration_data['buckets'][i] + time_loop_data['buckets'][i] for i in range(len(iteration_data['buckets']))]
+ t2_lat_tsc = time_loop_data['lat_tsc']
lat_avail = True
t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc, tsc_hz = self.gen_machine.core_stats()
if t3_tsc != t2_tsc:
- single_core_measurement_duration = (t3_tsc - t2_tsc) * 1.0 / tsc_hz # time difference between the 2 measurements, expressed in seconds.
- tot_core_measurement_duration = tot_core_measurement_duration + single_core_measurement_duration
+ time_loop_data['actual_duration'] = (t3_tsc - t2_tsc) * 1.0 / tsc_hz # time difference between the 2 measurements, expressed in seconds.
+ iteration_data['actual_duration'] = iteration_data['actual_duration'] + time_loop_data['actual_duration']
delta_rx = t3_rx - t2_rx
tot_rx += delta_rx
delta_non_dp_rx = t3_non_dp_rx - t2_non_dp_rx
@@ -291,8 +301,8 @@ class RapidTest(object):
tot_non_dp_tx += delta_non_dp_tx
delta_dp_tx = delta_tx -delta_non_dp_tx
delta_dp_rx = delta_rx -delta_non_dp_rx
- delta_dp_drop = delta_dp_tx - delta_dp_rx
- tot_dp_drop += delta_dp_drop
+ time_loop_data['abs_dropped'] = delta_dp_tx - delta_dp_rx
+ iteration_data['abs_dropped'] += time_loop_data['abs_dropped']
delta_drop = t3_drop - t2_drop
tot_drop += delta_drop
t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc = t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc
@@ -313,37 +323,30 @@ class RapidTest(object):
if self.test['test'] == 'fixed_rate':
if lat_avail == core_avail == True:
lat_avail = core_avail = False
- pps_req_tx = (delta_tx + delta_drop - delta_rx)/single_core_measurement_duration/1000000
- pps_tx = delta_tx/single_core_measurement_duration/1000000
+ time_loop_data['pps_req_tx'] = (delta_tx + delta_drop - delta_rx)/time_loop_data['actual_duration']/1000000
+ time_loop_data['pps_tx'] = delta_tx/time_loop_data['actual_duration']/1000000
if self.sut_machine != None and sut_avail:
- pps_sut_tx = delta_sut_tx/single_sut_core_measurement_duration/1000000
+ time_loop_data['pps_sut_tx'] = delta_sut_tx/single_sut_core_measurement_duration/1000000
sut_avail = False
else:
- pps_sut_tx = None
- pps_rx = delta_rx/single_core_measurement_duration/1000000
- RapidLog.info(self.report_result(flow_number, size,
- speed, pps_req_tx, pps_tx, pps_sut_tx, pps_rx,
- lat_avg_sample, sample_percentile, percentile_max,
- lat_max_sample, delta_dp_tx, delta_dp_rx,
- tot_dp_drop, single_core_measurement_duration))
- variables = {
- 'Flows': flow_number,
- 'Size': size,
- 'RequestedSpeed': self.get_pps(speed,size),
- 'CoreGenerated': pps_req_tx,
- 'SentByNIC': pps_tx,
- 'FwdBySUT': pps_sut_tx,
- 'RevByCore': pps_rx,
- 'AvgLatency': lat_avg_sample,
- 'PCTLatency': sample_percentile,
- 'MaxLatency': lat_max_sample,
- 'PacketsSent': delta_dp_tx,
- 'PacketsReceived': delta_dp_rx,
- 'PacketsLost': tot_dp_drop,
- 'bucket_size': bucket_size,
- 'buckets': buckets}
-
- self.post_data('rapid_flowsizetest', variables)
+ time_loop_data['pps_sut_tx'] = None
+ time_loop_data['pps_rx'] = delta_rx/time_loop_data['actual_duration']/1000000
+ time_loop_data['abs_tx'] = delta_dp_tx
+ time_loop_data['abs_rx'] = delta_dp_rx
+ time_loop_prefix = {'speed' : '',
+ 'lat_avg' : '',
+ 'lat_perc' : '',
+ 'lat_max' : '',
+ 'abs_drop_rate' : '',
+ 'drop_rate' : ''}
+ RapidLog.info(self.report_result(flow_number, size, time_loop_data,
+ time_loop_prefix))
+ time_loop_data['test'] = self.test['testname']
+ time_loop_data['environment_file'] = self.test['environment_file']
+ time_loop_data['Flows'] = flow_number
+ time_loop_data['Size'] = size
+ time_loop_data['RequestedSpeed'] = RapidTest.get_pps(speed, size)
+ _ = self.post_data('rapid_flowsizetest', time_loop_data)
end_bg_gen_stats = []
for bg_gen_machine in self.background_machines:
bg_rx, bg_non_dp_rx, bg_tx, bg_non_dp_tx, _, _, bg_tsc, bg_hz = bg_gen_machine.core_stats()
@@ -353,6 +356,8 @@ class RapidTest(object):
"bg_hz" : bg_hz
}
end_bg_gen_stats.append(dict(bg_gen_stat))
+ if self.background_machines:
+ self.stop_background_traffic(self.background_machines)
i = 0
bg_rates =[]
while i < len(end_bg_gen_stats):
@@ -361,69 +366,65 @@ class RapidTest(object):
start_bg_gen_stats[i]['bg_tsc']) * 1.0 / end_bg_gen_stats[i]['bg_hz']))
i += 1
if len(bg_rates):
- avg_bg_rate = sum(bg_rates) / len(bg_rates)
- RapidLog.debug('Average Background traffic rate: {:>7.3f} Mpps'.format(avg_bg_rate))
+ iteration_data['avg_bg_rate'] = sum(bg_rates) / len(bg_rates)
+ RapidLog.debug('Average Background traffic rate: {:>7.3f} Mpps'.format(iteration_data['avg_bg_rate']))
else:
- avg_bg_rate = None
+ iteration_data['avg_bg_rate'] = None
#Stop generating
self.gen_machine.stop_gen_cores()
- r += 1
- lat_avg = old_div(lat_avg, float(tot_lat_measurement_duration))
- used_avg = old_div(used_avg, float(tot_lat_measurement_duration))
+ iteration_data['r'] += 1
+ iteration_data['lat_avg'] = old_div(iteration_data['lat_avg'], float(tot_lat_measurement_duration))
+ iteration_data['lat_used'] = old_div(iteration_data['lat_used'], float(tot_lat_measurement_duration))
t4_tsc = t2_tsc
while t4_tsc == t2_tsc:
t4_rx, t4_non_dp_rx, t4_tx, t4_non_dp_tx, t4_drop, t4_tx_fail, t4_tsc, abs_tsc_hz = self.gen_machine.core_stats()
if self.test['test'] == 'fixed_rate':
- t4_lat_tsc = t2_lat_tsc
- while t4_lat_tsc == t2_lat_tsc:
- lat_min_sample, lat_max_sample, lat_avg_sample, used_sample, t4_lat_tsc, lat_hz, buckets = self.gen_machine.lat_stats()
+ iteration_data['lat_tsc'] = t2_lat_tsc
+ while iteration_data['lat_tsc'] == t2_lat_tsc:
+ iteration_data.update(self.gen_machine.lat_stats())
sample_count = 0
- lat_samples = sum(buckets)
- for percentile, bucket in enumerate(buckets,start=1):
+ for percentile, bucket in enumerate(iteration_data['buckets'],start=1):
sample_count += bucket
- if sample_count > lat_samples * LAT_PERCENTILE:
+ if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE:
break
- percentile_max = (percentile == len(buckets))
- percentile = percentile * bucket_size
- lat_max = lat_max_sample
- lat_avg = lat_avg_sample
+ iteration_data['lat_perc_max'] = (percentile == len(iteration_data['buckets']))
+ iteration_data['lat_perc'] = percentile * iteration_data['bucket_size']
delta_rx = t4_rx - t2_rx
delta_non_dp_rx = t4_non_dp_rx - t2_non_dp_rx
delta_tx = t4_tx - t2_tx
delta_non_dp_tx = t4_non_dp_tx - t2_non_dp_tx
delta_dp_tx = delta_tx -delta_non_dp_tx
delta_dp_rx = delta_rx -delta_non_dp_rx
- dp_tx = delta_dp_tx
- dp_rx = delta_dp_rx
- tot_dp_drop += delta_dp_tx - delta_dp_rx
- pps_req_tx = None
- pps_tx = None
- pps_sut_tx = None
- pps_rx = None
- drop_rate = 100.0*(dp_tx-dp_rx)/dp_tx
- tot_core_measurement_duration = None
+ iteration_data['abs_tx'] = delta_dp_tx
+ iteration_data['abs_rx'] = delta_dp_rx
+ iteration_data['abs_dropped'] += delta_dp_tx - delta_dp_rx
+ iteration_data['pps_req_tx'] = None
+ iteration_data['pps_tx'] = None
+ iteration_data['pps_sut_tx'] = None
+ iteration_data['drop_rate'] = 100.0*(iteration_data['abs_tx']-iteration_data['abs_rx'])/iteration_data['abs_tx']
+ iteration_data['actual_duration'] = None
break ## Not really needed since the while loop will stop when evaluating the value of r
else:
sample_count = 0
- buckets = buckets_total
- for percentile, bucket in enumerate(buckets_total,start=1):
+ for percentile, bucket in enumerate(iteration_data['buckets'],start=1):
sample_count += bucket
- if sample_count > tot_lat_samples * LAT_PERCENTILE:
+ if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE:
break
- percentile_max = (percentile == len(buckets_total))
- percentile = percentile * bucket_size
- pps_req_tx = (tot_tx + tot_drop - tot_rx)/tot_core_measurement_duration/1000000.0 # tot_drop is all packets dropped by all tasks. This includes packets dropped at the generator task + packets dropped by the nop task. In steady state, this equals to the number of packets received by this VM
- pps_tx = tot_tx/tot_core_measurement_duration/1000000.0 # tot_tx is all generated packets actually accepted by the interface
- pps_rx = tot_rx/tot_core_measurement_duration/1000000.0 # tot_rx is all packets received by the nop task = all packets received in the gen VM
+ iteration_data['lat_perc_max'] = (percentile == len(iteration_data['buckets']))
+ iteration_data['lat_perc'] = percentile * iteration_data['bucket_size']
+ iteration_data['pps_req_tx'] = (tot_tx + tot_drop - tot_rx)/iteration_data['actual_duration']/1000000.0 # tot_drop is all packets dropped by all tasks. This includes packets dropped at the generator task + packets dropped by the nop task. In steady state, this equals to the number of packets received by this VM
+ iteration_data['pps_tx'] = tot_tx/iteration_data['actual_duration']/1000000.0 # tot_tx is all generated packets actually accepted by the interface
+ iteration_data['pps_rx'] = tot_rx/iteration_data['actual_duration']/1000000.0 # tot_rx is all packets received by the nop task = all packets received in the gen VM
if self.sut_machine != None and sut_avail:
- pps_sut_tx = tot_sut_tx / tot_sut_core_measurement_duration / 1000000.0
+ iteration_data['pps_sut_tx'] = tot_sut_tx / tot_sut_core_measurement_duration / 1000000.0
else:
- pps_sut_tx = None
- dp_tx = (t4_tx - t1_tx) - (t4_non_dp_tx - t1_non_dp_tx)
- dp_rx = (t4_rx - t1_rx) - (t4_non_dp_rx - t1_non_dp_rx)
- tot_dp_drop = dp_tx - dp_rx
- drop_rate = 100.0*tot_dp_drop/dp_tx
- if ((drop_rate < self.test['drop_rate_threshold']) or (tot_dp_drop == self.test['drop_rate_threshold'] ==0) or (tot_dp_drop > self.test['maxz'])):
+ iteration_data['pps_sut_tx'] = None
+ iteration_data['abs_tx'] = (t4_tx - t1_tx) - (t4_non_dp_tx - t1_non_dp_tx)
+ iteration_data['abs_rx'] = (t4_rx - t1_rx) - (t4_non_dp_rx - t1_non_dp_rx)
+ iteration_data['abs_dropped'] = iteration_data['abs_tx'] - iteration_data['abs_rx']
+ iteration_data['drop_rate'] = 100.0*iteration_data['abs_dropped']/iteration_data['abs_tx']
+ if ((iteration_data['drop_rate'] < self.test['drop_rate_threshold']) or (iteration_data['abs_dropped'] == self.test['drop_rate_threshold'] ==0) or (iteration_data['abs_dropped'] > self.test['maxz'])):
break
self.gen_machine.stop_latency_cores()
- return(pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg,percentile,percentile_max,lat_max,dp_tx,dp_rx,tot_dp_drop,(t4_tx_fail - t1_tx_fail),drop_rate,lat_min,used_avg,r,tot_core_measurement_duration,avg_bg_rate,bucket_size,buckets)
+ iteration_data['abs_tx_fail'] = t4_tx_fail - t1_tx_fail
+ return (iteration_data)