ipynb/thermal/ThermalSensorCharacterisation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Thermal Sensor Measurements"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The goal of this experiment is to measure temperature on Juno R2 board using the available sensors. In order to do that we will run a busy-loop workload of about 5 minutes and collect traces for the `thermal_temperature` event.\n",
    "\n",
    "Measurements must be done **with** and **without** fan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import logging\n",
    "from conf import LisaLogging\n",
    "LisaLogging.setup()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%pylab inline\n",
    "\n",
    "import os\n",
    "\n",
    "# Support to access the remote target\n",
    "import devlib\n",
    "from env import TestEnv\n",
    "\n",
    "# Support to configure and run RTApp based workloads\n",
    "from wlgen import RTA, Periodic\n",
    "\n",
    "# Support for trace events analysis\n",
    "from trace import Trace\n",
    "\n",
    "# Suport for FTrace events parsing and visualization\n",
    "import trappy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Target Configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our target is a Juno R2 development board running Linux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Setup a target configuration\n",
    "my_target_conf = {\n",
    "    \n",
    "    # Target platform and board\n",
    "    \"platform\"    : 'linux',\n",
    "    \"board\"       : 'juno',\n",
    "    \n",
    "    # Target board IP/MAC address\n",
    "    \"host\"        : '192.168.0.1',\n",
    "    \n",
    "    # Login credentials\n",
    "    \"username\"    : 'root',\n",
    "    \"password\"    : '',\n",
    "    \n",
    "    # RTApp calibration values (comment to let LISA do a calibration run)\n",
    "    \"rtapp-calib\" :  {\n",
    "        \"0\": 318, \"1\": 125, \"2\": 124, \"3\": 318, \"4\": 318, \"5\": 319\n",
    "    },\n",
    "    \n",
    "    # Tools required by the experiments\n",
    "    \"tools\"   : [ 'rt-app', 'trace-cmd' ],    \n",
    "    \"exclude_modules\" : ['hwmon'],\n",
    "    \n",
    "    # FTrace events to collect for all the tests configuration which have\n",
    "    # the \"ftrace\" flag enabled\n",
    "    \"ftrace\"  : {\n",
    "         \"events\" : [\n",
    "            \"thermal_temperature\",\n",
    "            # Use sched_switch event to recognize tasks on kernelshark\n",
    "            \"sched_switch\",\n",
    "            # cdev_update has been used to show that \"step_wise\" thermal governor introduces noise\n",
    "            # because it keeps changing the state of the cooling devices and therefore\n",
    "            # the available OPPs\n",
    "            #\"cdev_update\",\n",
    "         ],\n",
    "         \"buffsize\" : 80 * 1024,\n",
    "    },\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tests execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Initialize a test environment using:\n",
    "# the provided target configuration (my_target_conf)\n",
    "te = TestEnv(target_conf=my_target_conf)\n",
    "target = te.target"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Workloads configuration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Create a new RTApp workload generator using the calibration values\n",
    "# reported by the TestEnv module\n",
    "rtapp_big = RTA(target, 'big', calibration=te.calibration())\n",
    "\n",
    "big_tasks = dict()\n",
    "for cpu in target.bl.bigs:\n",
    "    big_tasks['busy_big'+str(cpu)] = Periodic(duty_cycle_pct=100,\n",
    "                                              duration_s=360,     # 6 minutes\n",
    "                                              cpus=str(cpu)       # pinned to a given cpu\n",
    "                                             ).get()\n",
    "\n",
    "# Configure this RTApp instance to:\n",
    "rtapp_big.conf(\n",
    "    # 1. generate a \"profile based\" set of tasks\n",
    "    kind='profile',\n",
    "    \n",
    "    # 2. define the \"profile\" of each task\n",
    "    params=big_tasks,\n",
    "    \n",
    "    # 3. Set load reference for task calibration\n",
    "    loadref='big',\n",
    "    \n",
    "    # 4. use this folder for task logfiles\n",
    "    run_dir=target.working_directory\n",
    ");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "rtapp_little = RTA(target, 'little', calibration=te.calibration())\n",
    "\n",
    "little_tasks = dict()\n",
    "for cpu in target.bl.littles:\n",
    "    little_tasks['busy_little'+str(cpu)] = Periodic(duty_cycle_pct=100,\n",
    "                                                    duration_s=360,\n",
    "                                                    cpus=str(cpu)).get()\n",
    "\n",
    "rtapp_little.conf(\n",
    "    kind='profile',\n",
    "    params=little_tasks,\n",
    "    # Allow the task duration to be calibrated for the littles (default is for big)\n",
    "    loadref='little',\n",
    "    run_dir=target.working_directory\n",
    ");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Workload execution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "logging.info('#### Setup FTrace')\n",
    "te.ftrace.start()\n",
    "\n",
    "logging.info('#### Start RTApp execution')\n",
    "# Run tasks on the bigs in background to allow execution of following instruction\n",
    "rtapp_big.run(out_dir=te.res_dir, background=True)\n",
    "# Run tasks on the littles and then wait 2 minutes for device to cool down\n",
    "rtapp_little.run(out_dir=te.res_dir, end_pause_s=120.0)\n",
    "\n",
    "logging.info('#### Stop FTrace')\n",
    "te.ftrace.stop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Trace Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "In order to analyze the trace we will plot it using `TRAPpy`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Collect the trace\n",
    "trace_file = os.path.join(te.res_dir, 'trace.dat')\n",
    "logging.info('#### Save FTrace: %s', trace_file)\n",
    "te.ftrace.get_trace(trace_file)\n",
    "# Parse trace\n",
    "therm_trace = trappy.FTrace(trace_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "therm_trace.thermal.data_frame.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Plot the data\n",
    "therm_plot = trappy.ILinePlot(therm_trace,\n",
    "                              signals=['thermal:temp'],\n",
    "                              filters={'thermal_zone': [\"soc\"]},\n",
    "                              title='Juno R2 SoC Temperature w/o fans')\n",
    "therm_plot.view()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The `pmic` sensor if off-chip and therefore it is not useful to get its temperature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Extract a data frame for each zone\n",
    "df = therm_trace.thermal.data_frame\n",
    "soc_df = df[df.thermal_zone == \"soc\"]\n",
    "big_df = df[df.thermal_zone == \"big_cluster\"]\n",
    "little_df = df[df.thermal_zone == \"little_cluster\"]\n",
    "gpu0_df = df[df.thermal_zone == \"gpu0\"]\n",
    "gpu1_df = df[df.thermal_zone == \"gpu1\"]\n",
    "# Build new trace\n",
    "juno_trace = trappy.BareTrace(name = \"Juno_R2\")\n",
    "juno_trace.add_parsed_event(\"SoC\", soc_df)\n",
    "juno_trace.add_parsed_event(\"big_Cluster\", big_df)\n",
    "juno_trace.add_parsed_event(\"LITTLE_Cluster\", little_df)\n",
    "juno_trace.add_parsed_event(\"gpu0\", gpu0_df)\n",
    "juno_trace.add_parsed_event(\"gpu1\", gpu1_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Plot the data for all sensors\n",
    "juno_signals = ['SoC:temp', 'big_Cluster:temp', 'LITTLE_Cluster:temp', 'gpu0:temp', 'gpu1:temp']\n",
    "therm_plot = trappy.ILinePlot([juno_trace],\n",
    "                              signals=juno_signals,\n",
    "                              title='Juno R2 Temperature all traces')\n",
    "therm_plot.view()"
   ]
  }
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