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derkling/201909_UtilEst_Tests_Convergence.ipynb

Created September 18, 2019 18:42
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201909_UtilEst_Tests_Convergence.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 11:16:54,769 INFO : root : Using LISA logging configuration:\n",
"2019-09-18 11:16:54,770 INFO : root : /data/Code/lisa/logging.conf\n"
]
}
],
"source": [
"import logging\n",
"from lisa.utils import setup_logging\n",
"setup_logging(level=logging.DEBUG)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"# Generate plots inline\n",
"%matplotlib inline\n",
"%pylab inline\n",
"%config IPCompleter.use_jedi = False"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Target Connection"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 11:16:55,647 INFO : root : Generating grammar tables from /usr/lib/python3.5/lib2to3/Grammar.txt\n",
"2019-09-18 11:16:55,673 INFO : root : Generating grammar tables from /usr/lib/python3.5/lib2to3/PatternGrammar.txt\n",
"2019-09-18 11:16:57,545 INFO : lisa.target.Target : Creating result directory: /data/Code/lisa/results/Target-juno-20190918_111657.545184\n",
"2019-09-18 11:16:57,547 INFO : lisa.target.Target : linux juno target connection settings:\n",
"2019-09-18 11:16:57,548 INFO : lisa.target.Target : port : 22\n",
"2019-09-18 11:16:57,549 INFO : lisa.target.Target : host : 192.168.90.1\n",
"2019-09-18 11:16:57,551 INFO : lisa.target.Target : password : None\n",
"2019-09-18 11:16:57,552 INFO : lisa.target.Target : username : root\n",
"2019-09-18 11:16:57,622 INFO : lisa.target.Target : Devlib modules to load: bl, cgroups, cpufreq, cpuidle, devfreq, fastboot, gem5stats, gpufreq, hotplug, hwmon, mbed-fan, odroidxu3-fan, sched, thermal\n",
"2019-09-18 11:17:01,961 WARNING : LinuxTarget : Module devfreq is not supported by the target\n",
"2019-09-18 11:17:01,963 WARNING : LinuxTarget : Module fastboot is not supported by the target\n",
"2019-09-18 11:17:01,965 WARNING : LinuxTarget : Module gem5stats is not supported by the target\n",
"2019-09-18 11:17:02,124 WARNING : LinuxTarget : Module gpufreq is not supported by the target\n",
"2019-09-18 11:17:07,155 WARNING : LinuxTarget : Module odroidxu3-fan is not supported by the target\n",
"2019-09-18 11:17:09,398 INFO : sched : Scheduler sched_domain procfs entries found\n",
"2019-09-18 11:17:09,399 INFO : sched : Detected kernel compiled with SCHED_DEBUG=y\n",
"2019-09-18 11:17:09,400 INFO : sched : CPU capacity sysfs entries found\n",
"2019-09-18 11:17:11,341 INFO : CGroups : Available controllers:\n",
"2019-09-18 11:17:12,153 INFO : CGroups : cpuset : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:12,639 INFO : CGroups : cpu : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:13,125 INFO : CGroups : cpuacct : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:13,611 INFO : CGroups : blkio : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:14,098 INFO : CGroups : memory : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:14,584 INFO : CGroups : devices : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:15,068 INFO : CGroups : perf_event : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:15,555 INFO : CGroups : hugetlb : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:16,041 INFO : CGroups : pids : /home/root/devlib-target/cgroups/devlib_cgh1\n",
"2019-09-18 11:17:16,205 WARNING : lisa.target.Target : Failed to initialized \"devfreq\" devlib Module\n",
"2019-09-18 11:17:16,206 WARNING : lisa.target.Target : Failed to initialized \"fastboot\" devlib Module\n",
"2019-09-18 11:17:16,207 WARNING : lisa.target.Target : Failed to initialized \"gem5stats\" devlib Module\n",
"2019-09-18 11:17:16,208 WARNING : lisa.target.Target : Failed to initialized \"gpufreq\" devlib Module\n",
"2019-09-18 11:17:16,209 WARNING : lisa.target.Target : Failed to initialized \"mbed-fan\" devlib Module\n",
"2019-09-18 11:17:16,210 WARNING : lisa.target.Target : Failed to initialized \"odroidxu3-fan\" devlib Module\n",
"2019-09-18 11:17:16,211 INFO : lisa.target.Target : Tools to install: ['rt-app', 'dmesg']\n",
"2019-09-18 11:17:16,849 INFO : lisa.platforms.platinfo.PlatformInfo : Attempting to read energy model from target\n",
"2019-09-18 11:17:17,331 ERROR : lisa.platforms.platinfo.PlatformInfo : Couldn't read target energy model: Unable to probe for energy model on target.\n",
"2019-09-18 11:17:21,113 INFO : lisa.target.Target : Effective platform information:\n",
"|- abi from target (str): arm64\n",
"|- cpu-capacities from target (dict): {0: 383, 1: 1024, 2: 1024, 3: 383, 4: 383, 5: 383}\n",
"|- cpus-count from target (int): 6\n",
"|- freq-domains from target (list): [[0, 3, 4, 5], [1, 2]]\n",
"|- freqs from target (dict): {0: [450000, 800000, 950000], 1: [600000, 1000000, 1200000], 2: [600000, 1000000, 1200000], 3: [450000, 800000, 950000], 4: [450000, 800000, 950000], 5: [450000, 800000, 950000]}\n",
"+- kernel:\n",
" |- config from target (TypedKernelConfig): <kernel config>\n",
" |- version from target (KernelVersion): 5.3.0-rc1-00114-g3c488fb34898 8 SMP PREEMPT Tue Sep 17 17:19:11 BST 2019\n",
"|- name from target-conf (str): juno\n",
"|- os from target (str): linux\n",
"+- rtapp:\n",
" |- calib from target (DeferredValue): <lazy value of RTA.get_cpu_calibrations>\n",
"|- capacity-classes from target(platform-info/cpu-capacities) (list): [[0, 3, 4, 5], [1, 2]]\n"
]
}
],
"source": [
"from lisa.target import Target, TargetConf\n",
"\n",
"target = Target(\n",
" name='juno',\n",
" kind='linux',\n",
" host='192.168.90.1',\n",
" username='root',\n",
" tools = ['rt-app', 'dmesg'],\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"def provide_calibration(calibration):\n",
" target.plat_info[\"rtapp\"].add_src(\"user\", {\"calib\" : calibration})\n",
"provide_calibration({0: 591, 1: 264, 2: 264, 3: 589, 4: 589, 5: 589})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Test Task Estimated Utilization"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['rtapp_loop',\n",
" 'sched_load_avg_task',\n",
" 'sched_load_se',\n",
" 'sched_switch',\n",
" 'sched_util_est_cfs',\n",
" 'sched_util_est_task',\n",
" 'sched_wakeup',\n",
" 'rtapp_task',\n",
" 'rtapp_loop',\n",
" 'rtapp_main',\n",
" 'rtapp_event',\n",
" 'rtapp_stats']"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from lisa.tests.staging.scheduler.util_tracking import Convergence\n",
"from lisa.trace import FtraceCollector\n",
"\n",
"events = Convergence.ftrace_conf['events'] + ['rtapp_task', 'rtapp_loop', 'rtapp_main', 'rtapp_event', 'rtapp_stats']\n",
"events"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 11:17:23,020 WARNING : LinuxTarget : Event [rtapp_loop] not available for tracing\n",
"2019-09-18 11:17:23,024 WARNING : LinuxTarget : Event [sched_load_avg_task] not available for tracing\n",
"2019-09-18 11:17:23,035 WARNING : LinuxTarget : Event [rtapp_task] not available for tracing\n",
"2019-09-18 11:17:23,038 WARNING : LinuxTarget : Event [rtapp_loop] not available for tracing\n",
"2019-09-18 11:17:23,041 WARNING : LinuxTarget : Event [rtapp_main] not available for tracing\n",
"2019-09-18 11:17:23,043 WARNING : LinuxTarget : Event [rtapp_event] not available for tracing\n",
"2019-09-18 11:17:23,046 WARNING : LinuxTarget : Event [rtapp_stats] not available for tracing\n",
"2019-09-18 11:17:23,476 INFO : lisa.target.Target : Creating result directory: /data/Code/lisa/results/Target-juno-20190918_111657.545184/Convergence-20190918_111723.475832\n",
"2019-09-18 11:17:23,638 INFO : lisa.target.Target : Disabling idle states for all domains\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"['rtapp_loop', 'sched_load_avg_task', 'sched_load_se', 'sched_switch', 'sched_util_est_cfs', 'sched_util_est_task', 'sched_wakeup', 'rtapp_task', 'rtapp_loop', 'rtapp_main', 'rtapp_event', 'rtapp_stats']\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 11:17:29,751 INFO : lisa.wlgen.rta.RTA : Creating target's run_dir: /home/root/devlib-target/lisa/wlgen/rta_convergence_20190918_111729_WqsyQb\n",
"2019-09-18 11:17:30,472 INFO : lisa.wlgen.rta.RTA : Calibration value: 264\n",
"2019-09-18 11:17:30,475 INFO : lisa.wlgen.rta.RTA : Default policy: SCHED_OTHER\n",
"2019-09-18 11:17:30,476 INFO : lisa.wlgen.rta.RTA : ------------------------\n",
"2019-09-18 11:17:30,477 INFO : lisa.wlgen.rta.RTA : task [test_task], sched: using default policy\n",
"2019-09-18 11:17:30,478 INFO : lisa.wlgen.rta.RTA : | start delay: 0.000000 [s]\n",
"2019-09-18 11:17:30,479 INFO : lisa.wlgen.rta.RTA : | loops count: 1\n",
"2019-09-18 11:17:30,480 INFO : lisa.wlgen.rta.RTA : + phase_000001\n",
"2019-09-18 11:17:30,481 INFO : lisa.wlgen.rta.Phase : | duration 5.000000 [s] (25 loops)\n",
"2019-09-18 11:17:30,482 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 75 %\n",
"2019-09-18 11:17:30,483 INFO : lisa.wlgen.rta.Phase : | run_time 150000 [us], sleep_time 50000 [us]\n",
"2019-09-18 11:17:30,484 INFO : lisa.wlgen.rta.RTA : + phase_000002\n",
"2019-09-18 11:17:30,485 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,486 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 50 %\n",
"2019-09-18 11:17:30,486 INFO : lisa.wlgen.rta.Phase : | run_time 100000 [us], sleep_time 100000 [us]\n",
"2019-09-18 11:17:30,487 INFO : lisa.wlgen.rta.RTA : + phase_000003\n",
"2019-09-18 11:17:30,488 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,489 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 30 %\n",
"2019-09-18 11:17:30,490 INFO : lisa.wlgen.rta.Phase : | run_time 60000 [us], sleep_time 140000 [us]\n",
"2019-09-18 11:17:30,490 INFO : lisa.wlgen.rta.RTA : + phase_000004\n",
"2019-09-18 11:17:30,491 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,492 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 10 %\n",
"2019-09-18 11:17:30,493 INFO : lisa.wlgen.rta.Phase : | run_time 20000 [us], sleep_time 180000 [us]\n",
"2019-09-18 11:17:30,494 INFO : lisa.wlgen.rta.RTA : + phase_000005\n",
"2019-09-18 11:17:30,494 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,495 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 5 %\n",
"2019-09-18 11:17:30,496 INFO : lisa.wlgen.rta.Phase : | run_time 10000 [us], sleep_time 190000 [us]\n",
"2019-09-18 11:17:30,496 INFO : lisa.wlgen.rta.RTA : + phase_000006\n",
"2019-09-18 11:17:30,497 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,498 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 10 %\n",
"2019-09-18 11:17:30,499 INFO : lisa.wlgen.rta.Phase : | run_time 20000 [us], sleep_time 180000 [us]\n",
"2019-09-18 11:17:30,500 INFO : lisa.wlgen.rta.RTA : + phase_000007\n",
"2019-09-18 11:17:30,500 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,501 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 30 %\n",
"2019-09-18 11:17:30,502 INFO : lisa.wlgen.rta.Phase : | run_time 60000 [us], sleep_time 140000 [us]\n",
"2019-09-18 11:17:30,503 INFO : lisa.wlgen.rta.RTA : + phase_000008\n",
"2019-09-18 11:17:30,503 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,504 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 50 %\n",
"2019-09-18 11:17:30,505 INFO : lisa.wlgen.rta.Phase : | run_time 100000 [us], sleep_time 100000 [us]\n",
"2019-09-18 11:17:30,506 INFO : lisa.wlgen.rta.RTA : + phase_000009\n",
"2019-09-18 11:17:30,506 INFO : lisa.wlgen.rta.Phase : | duration 1.000000 [s] (5 loops)\n",
"2019-09-18 11:17:30,507 INFO : lisa.wlgen.rta.Phase : | period 200000 [us], duty_cycle 60 %\n",
"2019-09-18 11:17:30,508 INFO : lisa.wlgen.rta.Phase : | run_time 120000 [us], sleep_time 80000 [us]\n",
"2019-09-18 11:17:35,960 WARNING : lisa.target.Target : Could not freeze userspace: freezer cgroup controller not available on the target\n",
"2019-09-18 11:17:35,963 INFO : lisa.wlgen.rta.RTA : Execution start: /home/root/devlib-target/bin/rt-app /home/root/devlib-target/lisa/wlgen/rta_convergence_20190918_111729_WqsyQb/rta_convergence.json 2>&1\n",
"2019-09-18 11:17:49,148 INFO : lisa.wlgen.rta.RTA : Execution complete\n",
"2019-09-18 11:17:54,273 INFO : lisa.target.Target : Re-enabling idle states for all domains\n"
]
}
],
"source": [
"ftrace_coll = FtraceCollector(target, events=events, buffer_size=10240)\n",
"print(ftrace_coll.events)\n",
"\n",
"bundle = Convergence.from_target(target, ftrace_coll=ftrace_coll)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Load data from bundle"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 19:25:55,382 INFO : root : Using LISA logging configuration:\n",
"2019-09-18 19:25:55,384 INFO : root : /data/Code/lisa/logging.conf\n"
]
}
],
"source": [
"import logging\n",
"from lisa.utils import setup_logging\n",
"setup_logging(level=logging.DEBUG)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 19:26:12,916 WARNING : py.warnings : /data/Code/lisa/.lisa-venv-3.5/lib/python3.5/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['trace']\n",
"`%matplotlib` prevents importing * from pylab and numpy\n",
" \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"# Generate plots inline\n",
"%config IPCompleter.use_jedi = False\n",
"%pylab inline\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"from lisa.tests.staging.scheduler.util_tracking import Convergence\n",
"\n",
"bundle = Convergence.from_dir('/data/Code/lisa/results/Target-juno-20190917_125440.895112/Convergence-20190917_125504.516961')"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"|- buffer-size from default (int): 10240\n",
"|- events from Convergence(required) (list): ['rtapp_loop', 'sched_load_avg_task', 'sched_load_se', 'sched_switch', 'sched_util_est_cfs', 'sched_util_est_task', 'sched_wakeup']\n",
"|- functions from default (list): []\n"
]
}
],
"source": [
"print(bundle.ftrace_conf)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['rtapp_task',\n",
" 'rtapp_event',\n",
" 'sched_wakeup',\n",
" 'rtapp_loop',\n",
" 'sched_switch',\n",
" 'sched_util_est_cfs',\n",
" 'sched_load_se',\n",
" 'rtapp_stats',\n",
" 'sched_util_est_task',\n",
" 'rtapp_main']"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Ensure we get a trace with all the \"additional\" events available\n",
"events = Convergence.ftrace_conf['events'] + ['rtapp_task', 'rtapp_loop', 'rtapp_main', 'rtapp_event', 'rtapp_stats']\n",
"trace = bundle.get_trace(events=events)\n",
"trace.available_events"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/data/Code/lisa/results/Target-juno-20190917_125440.895112/Convergence-20190917_125504.516961/trace.dat'"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trace.trace_path"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"#trace.show()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"RefTime(kernel=0.8513259999454021, user=1126790211056.0)"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trace.analysis.rta.rtapp_reftime"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"PhaseWindow(id=8, start=12.85006899992004, end=13.850063999881968)"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trace.analysis.rta.task_phase_at('test_task-0', 13.2)"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[TaskID(pid=18141, comm='rt-app'), TaskID(pid=18142, comm='test_task-0')]"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trace.analysis.rta.rtapp_tasks"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"PhaseWindow(id=0, start=0.8628360000438988, end=5.850063999881968)\n",
"PhaseWindow(id=1, start=5.850070999935269, end=6.850062999874353)\n",
"PhaseWindow(id=2, start=6.850070999935269, end=7.850062999874353)\n",
"PhaseWindow(id=3, start=7.850070999935269, end=8.850061000091955)\n",
"PhaseWindow(id=4, start=8.85006899992004, end=9.85006200009957)\n",
"PhaseWindow(id=5, start=9.850069999927655, end=10.850061000091955)\n",
"PhaseWindow(id=6, start=10.85006899992004, end=11.85006200009957)\n",
"PhaseWindow(id=7, start=11.850069999927655, end=12.85006200009957)\n",
"PhaseWindow(id=8, start=12.85006899992004, end=13.850063999881968)\n"
]
}
],
"source": [
"for p in trace.analysis.rta.task_phase_windows('test_task-0'):\n",
" print(p)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" <th></th>\n",
" <th>duration</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Time</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0.862836</th>\n",
" <td>4.987228</td>\n",
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" <td>0.999992</td>\n",
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"text/plain": [
" duration\n",
"Time \n",
"0.862836 4.987228\n",
"5.850071 0.999992\n",
"6.850071 0.999992\n",
"7.850071 0.999990\n",
"8.850069 0.999993\n",
"9.850070 0.999991\n",
"10.850069 0.999993\n",
"11.850070 0.999992\n",
"12.850069 0.999995"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = trace.analysis.rta.df_phases('test_task-0')\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 19:26:15,493 WARNING : py.warnings : /data/Code/lisa/.lisa-venv-3.5/lib/python3.5/site-packages/matplotlib/figure.py:2369: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
" warnings.warn(\"This figure includes Axes that are not compatible \"\n",
"\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 1152x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = trace.analysis.load_tracking.plot_task_signals('test_task-0', signals=['util'])\n",
"trace.analysis.tasks.plot_task_activation('test_task-0', overlay=True, axis=ax, active_value=1200, sleep_value=0, alpha=.2);"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['rtapp_task',\n",
" 'rtapp_event',\n",
" 'sched_wakeup',\n",
" 'rtapp_loop',\n",
" 'sched_switch',\n",
" 'sched_util_est_cfs',\n",
" 'sched_load_se',\n",
" 'rtapp_stats',\n",
" 'sched_util_est_task',\n",
" 'rtapp_main']"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tv = trace.get_view(trace.analysis.rta.task_phase_window('test_task-0', 1))\n",
"tv.available_events"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"task = trace.get_task_id('test_task-0')\n",
"ax = trace.analysis.load_tracking.plot_task_signals(task, signals=['util', 'util_est_enqueued', 'util_est_ewma'])\n",
"trace.analysis.rta.plot_phases(task, axis=ax);"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2019-09-18 19:26:17,023 WARNING : py.warnings : /data/Code/lisa/.lisa-venv-3.5/lib/python3.5/site-packages/matplotlib/figure.py:2369: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n",
" warnings.warn(\"This figure includes Axes that are not compatible \"\n",
"\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1152x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = tv.analysis.load_tracking.plot_task_signals('test_task-0', signals=['util'])\n",
"tv.analysis.tasks.plot_task_activation('test_task-0', overlay=True, axis=ax, active_value=1200, sleep_value=0, alpha=.2);"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1152x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = trace.analysis.load_tracking.plot_task_signals('test_task-0', signals=['util', 'util_est_enqueued', 'util_est_ewma'])\n",
"trace.analysis.rta.plot_phases('test_task-0', axis=ax);"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"phase1 = trace.analysis.rta.task_phase_window('test_task-0', 5)\n",
"phase2 = trace.analysis.rta.task_phase_window('test_task-0', 8)\n",
"\n",
"tv = trace.get_view((phase1.start, phase2.end))"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1152x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = tv.analysis.load_tracking.plot_task_signals('test_task-0', signals=['util', 'util_est_enqueued', 'util_est_ewma']);\n",
"tv.analysis.rta.plot_phases('test_task-0', axis=ax);"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [],
"source": [
"phase1 = trace.analysis.rta.task_phase_window('test_task-0', 8)\n",
"tv = trace.get_view((phase1.start, phase1.end))"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 1152x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"ax = tv.analysis.load_tracking.plot_task_signals('test_task-0', signals=['util', 'util_est_enqueued', 'util_est_ewma']);\n",
"tv.analysis.rta.plot_phases('test_task-0', axis=ax);"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"PhaseWindow(id=0, start=0.8628360000438988, end=5.850063999881968)\n",
"PhaseWindow(id=1, start=5.850070999935269, end=6.850062999874353)\n",
"PhaseWindow(id=2, start=6.850070999935269, end=7.850062999874353)\n",
"PhaseWindow(id=3, start=7.850070999935269, end=8.850061000091955)\n",
"PhaseWindow(id=4, start=8.85006899992004, end=9.85006200009957)\n",
"PhaseWindow(id=5, start=9.850069999927655, end=10.850061000091955)\n",
"PhaseWindow(id=6, start=10.85006899992004, end=11.85006200009957)\n",
"PhaseWindow(id=7, start=11.850069999927655, end=12.85006200009957)\n",
"PhaseWindow(id=8, start=12.85006899992004, end=13.850063999881968)\n"
]
}
],
"source": [
"for phase in trace.analysis.rta.task_phase_windows('test_task-0'):\n",
" print(phase)"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>duration</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Time</th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0.862836</th>\n",
" <td>4.987228</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5.850071</th>\n",
" <td>0.999992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6.850071</th>\n",
" <td>0.999992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7.850071</th>\n",
" <td>0.999990</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8.850069</th>\n",
" <td>0.999993</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9.850070</th>\n",
" <td>0.999991</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10.850069</th>\n",
" <td>0.999993</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11.850070</th>\n",
" <td>0.999992</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12.850069</th>\n",
" <td>0.999995</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" duration\n",
"Time \n",
"0.862836 4.987228\n",
"5.850071 0.999992\n",
"6.850071 0.999992\n",
"7.850071 0.999990\n",
"8.850069 0.999993\n",
"9.850070 0.999991\n",
"10.850069 0.999993\n",
"11.850070 0.999992\n",
"12.850069 0.999995"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trace.analysis.rta.df_phases('test_task-0')"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [],
"source": [
"#%%debug\n",
"results = bundle.test_areas()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"PASSED: {FastRamp=False, PhasesStats={0=PhaseStats(start=0.8628360000438988, end=5.850063999881968, area_util=4097.830691914773, area_enqueued=4711.793828886235, area_ewma=4128.18465591711), 1=PhaseStats(start=5.850070999935269, end=6.850062999874353, area_util=745.5899419579655, area_enqueued=796.5373680100311, area_ewma=835.1429290126543), 2=PhaseStats(start=6.850070999935269, end=7.850062999874353, area_util=612.2703149565496, area_enqueued=652.9066869819071, area_ewma=742.5591399846599), 3=PhaseStats(start=7.850070999935269, end=8.850061000091955, area_util=296.56763099553064, area_enqueued=306.3439569969196, area_ewma=497.65220800437964), 4=PhaseStats(start=8.85006899992004, end=9.85006200009957, area_util=166.35380299203098, area_enqueued=170.30594497034326, area_ewma=278.416283945553), 5=PhaseStats(start=9.850069999927655, end=10.850061000091955, area_util=292.5141479994636, area_enqueued=302.4856340121478, area_ewma=265.19951200741343), 6=PhaseStats(start=10.85006899992004, end=11.85006200009957, area_util=605.394406968262, area_enqueued=647.7093650035094, area_ewma=470.11014698445797), 7=PhaseStats(start=11.850069999927655, end=12.85006200009957, area_util=733.4957379603293, area_enqueued=790.1173978613224, area_ewma=668.0179088760633), 8=PhaseStats(start=12.85006899992004, end=13.850063999881968, area_util=770.7784239815082, area_enqueued=822.3580258507282, area_ewma=770.0905798650347)}}\n"
]
}
],
"source": [
"print(results)"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [],
"source": [
"getattr(results.metrics, 'Reasons', None)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [],
"source": [
"results = bundle.test_activations()"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"PASSED: {Signals={1=ActivationSignals(time=1.0500439999159425, util_avg=999, util_est_enqueued=999, util_est_ewma=249), 2=ActivationSignals(time=1.250044000102207, util_avg=975, util_est_enqueued=975, util_est_ewma=430), 3=ActivationSignals(time=1.4500450000632554, util_avg=969, util_est_enqueued=969, util_est_ewma=564), 4=ActivationSignals(time=1.6500450000166893, util_avg=969, util_est_enqueued=969, util_est_ewma=665), 5=ActivationSignals(time=1.8500439999625087, util_avg=969, util_est_enqueued=969, util_est_ewma=741), 6=ActivationSignals(time=2.0500439999159425, util_avg=969, util_est_enqueued=969, util_est_ewma=798), 7=ActivationSignals(time=2.250044999876991, util_avg=969, util_est_enqueued=969, util_est_ewma=840), 8=ActivationSignals(time=2.450044000055641, util_avg=969, util_est_enqueued=969, util_est_ewma=872), 9=ActivationSignals(time=2.650044000009075, util_avg=969, util_est_enqueued=969, util_est_ewma=896), 10=ActivationSignals(time=2.8500439999625087, util_avg=969, util_est_enqueued=969, util_est_ewma=914), 11=ActivationSignals(time=3.050044999923557, util_avg=969, util_est_enqueued=969, util_est_ewma=927), 12=ActivationSignals(time=3.250044000102207, util_avg=969, util_est_enqueued=969, util_est_ewma=937), 13=ActivationSignals(time=3.450044000055641, util_avg=969, util_est_enqueued=969, util_est_ewma=945), 14=ActivationSignals(time=3.6500450000166893, util_avg=969, util_est_enqueued=969, util_est_ewma=951), 15=ActivationSignals(time=3.850044999970123, util_avg=969, util_est_enqueued=969, util_est_ewma=955), 16=ActivationSignals(time=4.0500439999159425, util_avg=969, util_est_enqueued=969, util_est_ewma=958), 17=ActivationSignals(time=4.250044999876991, util_avg=969, util_est_enqueued=969, util_est_ewma=960), 18=ActivationSignals(time=4.450044000055641, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 19=ActivationSignals(time=4.650044000009075, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 20=ActivationSignals(time=4.850043999962509, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 21=ActivationSignals(time=5.0500439999159425, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 22=ActivationSignals(time=5.250043000094593, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 23=ActivationSignals(time=5.450044000055641, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 24=ActivationSignals(time=5.650045000016689, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 25=ActivationSignals(time=5.850044999970123, util_avg=969, util_est_enqueued=968, util_est_ewma=960), 26=ActivationSignals(time=6.0500439999159425, util_avg=891, util_est_enqueued=891, util_est_ewma=942), 27=ActivationSignals(time=6.250042000086978, util_avg=867, util_est_enqueued=867, util_est_ewma=923), 28=ActivationSignals(time=6.450044000055641, util_avg=867, util_est_enqueued=867, util_est_ewma=909), 29=ActivationSignals(time=6.65004300000146, util_avg=866, util_est_enqueued=867, util_est_ewma=898), 30=ActivationSignals(time=6.850043999962509, util_avg=866, util_est_enqueued=867, util_est_ewma=890), 31=ActivationSignals(time=7.050042999908328, util_avg=702, util_est_enqueued=703, util_est_ewma=843), 32=ActivationSignals(time=7.250043000094593, util_avg=685, util_est_enqueued=685, util_est_ewma=803), 33=ActivationSignals(time=7.450043000048026, util_avg=684, util_est_enqueued=685, util_est_ewma=773), 34=ActivationSignals(time=7.650044000009075, util_avg=685, util_est_enqueued=685, util_est_ewma=751), 35=ActivationSignals(time=7.850042999954894, util_avg=685, util_est_enqueued=685, util_est_ewma=734), 36=ActivationSignals(time=8.050042999908328, util_avg=323, util_est_enqueued=323, util_est_ewma=631), 37=ActivationSignals(time=8.250043000094593, util_avg=313, util_est_enqueued=313, util_est_ewma=551), 38=ActivationSignals(time=8.450043000048026, util_avg=305, util_est_enqueued=305, util_est_ewma=489), 39=ActivationSignals(time=8.65004300000146, util_avg=305, util_est_enqueued=305, util_est_ewma=443), 40=ActivationSignals(time=8.850042999954894, util_avg=313, util_est_enqueued=313, util_est_ewma=410), 41=ActivationSignals(time=9.050042999908328, util_avg=174, util_est_enqueued=175, util_est_ewma=351), 42=ActivationSignals(time=9.250042000086978, util_avg=171, util_est_enqueued=171, util_est_ewma=306), 43=ActivationSignals(time=9.450043000048026, util_avg=171, util_est_enqueued=171, util_est_ewma=272), 44=ActivationSignals(time=9.650044000009075, util_avg=171, util_est_enqueued=171, util_est_ewma=246), 45=ActivationSignals(time=9.850042999954894, util_avg=171, util_est_enqueued=171, util_est_ewma=227), 46=ActivationSignals(time=10.050043999915943, util_avg=310, util_est_enqueued=311, util_est_ewma=248), 47=ActivationSignals(time=10.250043000094593, util_avg=305, util_est_enqueued=305, util_est_ewma=262), 48=ActivationSignals(time=10.450043000048026, util_avg=305, util_est_enqueued=305, util_est_ewma=272), 49=ActivationSignals(time=10.65004300000146, util_avg=313, util_est_enqueued=313, util_est_ewma=282), 50=ActivationSignals(time=10.850042999954894, util_avg=305, util_est_enqueued=305, util_est_ewma=287), 51=ActivationSignals(time=11.050043999915943, util_avg=676, util_est_enqueued=677, util_est_ewma=384), 52=ActivationSignals(time=11.250044000102207, util_avg=684, util_est_enqueued=685, util_est_ewma=459), 53=ActivationSignals(time=11.450043000048026, util_avg=684, util_est_enqueued=685, util_est_ewma=515), 54=ActivationSignals(time=11.65004300000146, util_avg=684, util_est_enqueued=685, util_est_ewma=557), 55=ActivationSignals(time=11.850042999954894, util_avg=684, util_est_enqueued=685, util_est_ewma=589), 56=ActivationSignals(time=12.050043999915943, util_avg=858, util_est_enqueued=859, util_est_ewma=656), 57=ActivationSignals(time=12.250043000094593, util_avg=867, util_est_enqueued=867, util_est_ewma=708), 58=ActivationSignals(time=12.450043000048026, util_avg=866, util_est_enqueued=867, util_est_ewma=747), 59=ActivationSignals(time=12.65004300000146, util_avg=866, util_est_enqueued=867, util_est_ewma=777), 60=ActivationSignals(time=12.850042999954894, util_avg=866, util_est_enqueued=867, util_est_ewma=799), 61=ActivationSignals(time=13.050043999915943, util_avg=914, util_est_enqueued=915, util_est_ewma=828), 62=ActivationSignals(time=13.250043000094593, util_avg=919, util_est_enqueued=919, util_est_ewma=850), 63=ActivationSignals(time=13.450044000055641, util_avg=919, util_est_enqueued=919, util_est_ewma=867), 64=ActivationSignals(time=13.65004500001669, util_avg=919, util_est_enqueued=919, util_est_ewma=880), 65=ActivationSignals(time=13.850044999970123, util_avg=919, util_est_enqueued=919, util_est_ewma=889)}}\n"
]
}
],
"source": [
"print(results)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [],
"source": [
"getattr(results.metrics, 'Reasons', None)"
]
}
],
"metadata": {
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