Global_latency_demo_v2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from trace import Trace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parse trace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "lh = os.getenv('LISA_HOME')\n",
    "d = \"{}/ipynb/tutorial/example_results/\".format(lh)\n",
    "# with open(\"{}/platform.json\".format(d)) as f:\n",
    "with open('{}/ignored/foo.json'.format(lh)) as f:\n",
    "    platform = json.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "trace = Trace(platform, '/home/brendan/Downloads/joel_trace/trace.html'.format(d), ['sched_switch', 'sched_wakeup'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get DataFrame with `sched_switch` & `sched_wakeup`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "switch_in = trace.data_frame.trace_event('sched_switch')[['next_pid']]\n",
    "wake = trace.data_frame.trace_event('sched_wakeup')[['pid']]\n",
    "df = wake.join(switch_in, how='outer')\n",
    "df = df.rename(columns={'next_pid': 'switch_in_pid', 'pid': 'wake_pid'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find wakeup latencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wake_pid         22.0\n",
      "switch_in_pid     NaN\n",
      "Name: 0.587284, dtype: float64\n",
      "wake_pid         22.0\n",
      "switch_in_pid     NaN\n",
      "Name: 0.587284, dtype: float64\n",
      "wake_pid         22.0\n",
      "switch_in_pid     NaN\n",
      "Name: 0.587284, dtype: float64\n",
      "wake_pid         22.0\n",
      "switch_in_pid     NaN\n",
      "Name: 0.587284, dtype: float64\n",
      "1 loop, best of 3: 9.84 s per loop\n"
     ]
    }
   ],
   "source": [
    "wakeup_times = {}\n",
    "results = []\n",
    "index = []\n",
    "def f(row):\n",
    "    time = row.name\n",
    "    if time == 0.58728400000000391:\n",
    "        print row\n",
    "    if not np.isnan(row.wake_pid):\n",
    "        wakeup_times[row.wake_pid] = time\n",
    "    else:\n",
    "        pid = row.switch_in_pid\n",
    "        if pid in wakeup_times:\n",
    "            lat = time - wakeup_times[pid]\n",
    "            results.append((pid, lat))\n",
    "            index.append(wakeup_times[pid])\n",
    "\n",
    "def g():\n",
    "    switch_in = trace.data_frame.trace_event('sched_switch')[['next_pid']]\n",
    "    wake = trace.data_frame.trace_event('sched_wakeup')[['pid']]\n",
    "    df = wake.join(switch_in, how='outer')\n",
    "    df = df.rename(columns={'next_pid': 'switch_in_pid', 'pid': 'wake_pid'})\n",
    "    df.apply(f, axis=1)\n",
    "    return pd.DataFrame(results, index=index, columns=['pid', 'wakeup_latency'])\n",
    "%timeit ldf = g()"
   ]
  }
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