1{ 2 "cells": [ 3 { 4 "cell_type": "markdown", 5 "metadata": { 6 "run_control": { 7 "frozen": false, 8 "read_only": false 9 } 10 }, 11 "source": [ 12 "# Analysis of PELT signal error due to skip last window update" 13 ] 14 }, 15 { 16 "cell_type": "code", 17 "execution_count": 1, 18 "metadata": { 19 "collapsed": false, 20 "run_control": { 21 "frozen": false, 22 "marked": false, 23 "read_only": false 24 } 25 }, 26 "outputs": [ 27 { 28 "name": "stderr", 29 "output_type": "stream", 30 "text": [ 31 "2017-07-25 18:34:56,088 INFO : root : Using LISA logging configuration:\n", 32 "2017-07-25 18:34:56,090 INFO : root : /home/joelaf/repo/lisa-aosp/external/lisa/logging.conf\n" 33 ] 34 } 35 ], 36 "source": [ 37 "import logging\n", 38 "from conf import LisaLogging\n", 39 "LisaLogging.setup()" 40 ] 41 }, 42 { 43 "cell_type": "code", 44 "execution_count": 2, 45 "metadata": { 46 "collapsed": false, 47 "run_control": { 48 "frozen": false, 49 "marked": false, 50 "read_only": false 51 } 52 }, 53 "outputs": [], 54 "source": [ 55 "# Generate plots inline\n", 56 "%matplotlib inline\n", 57 "import json\n", 58 "import os\n", 59 "from trace import Trace\n", 60 "import numpy\n", 61 "import pandas as pd\n", 62 "import matplotlib.pyplot as plt\n", 63 "import trappy\n", 64 "\n", 65 "path_to_dat = \"/home/joelaf/repo/lisa-aosp/external/lisa/ipynb/scratchpad/pelt-error/trace.dat\"" 66 ] 67 }, 68 { 69 "cell_type": "markdown", 70 "metadata": { 71 "run_control": { 72 "frozen": false, 73 "read_only": false 74 } 75 }, 76 "source": [ 77 "## Parse Trace and Profiling Data" 78 ] 79 }, 80 { 81 "cell_type": "code", 82 "execution_count": 3, 83 "metadata": { 84 "collapsed": false, 85 "run_control": { 86 "frozen": false, 87 "marked": false, 88 "read_only": false 89 } 90 }, 91 "outputs": [], 92 "source": [ 93 "trace = Trace(None, path_to_dat, events=[ 'sched_switch', 'pelt_update' ])" 94 ] 95 }, 96 { 97 "cell_type": "markdown", 98 "metadata": { 99 "collapsed": true, 100 "run_control": { 101 "frozen": false, 102 "read_only": false 103 } 104 }, 105 "source": [ 106 "## Trace visualization" 107 ] 108 }, 109 { 110 "cell_type": "code", 111 "execution_count": 4, 112 "metadata": { 113 "collapsed": false, 114 "run_control": { 115 "frozen": false, 116 "marked": false, 117 "read_only": false 118 } 119 }, 120 "outputs": [ 121 { 122 "data": { 123 "text/html": [ 124 "<style>\n", 125 "/*\n", 126 " * Copyright 2015-2017 ARM Limited\n", 127 " *\n", 128 " * Licensed under the Apache License, Version 2.0 (the \"License\");\n", 129 " * you may not use this file except in compliance with the License.\n", 130 " * You may obtain a copy of the License at\n", 131 " *\n", 132 " * http://www.apache.org/licenses/LICENSE-2.0\n", 133 " *\n", 134 " * Unless required by applicable law or agreed to in writing, software\n", 135 " * distributed under the License is distributed on an \"AS IS\" BASIS,\n", 136 " * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n", 137 " * See the License for the specific language governing permissions and\n", 138 " * limitations under the License.\n", 139 " */\n", 140 "\n", 141 ".d3-tip {\n", 142 " line-height: 1;\n", 143 " padding: 12px;\n", 144 " background: rgba(0, 0, 0, 0.6);\n", 145 " color: #fff;\n", 146 " border-radius: 2px;\n", 147 " position: absolute !important;\n", 148 " z-index: 99999;\n", 149 "}\n", 150 "\n", 151 ".d3-tip:after {\n", 152 " box-sizing: border-box;\n", 153 " pointer-events: none;\n", 154 " display: inline;\n", 155 " font-size: 10px;\n", 156 " width: 100%;\n", 157 " line-height: 1;\n", 158 " color: rgba(0, 0, 0, 0.6);\n", 159 " content: \"\\25BC\";\n", 160 " position: absolute !important;\n", 161 " z-index: 99999;\n", 162 " text-align: center;\n", 163 "}\n", 164 "\n", 165 ".d3-tip.n:after {\n", 166 " margin: -1px 0 0 0;\n", 167 " top: 100%;\n", 168 " left: 0;\n", 169 "}\n", 170 "\n", 171 ".contextRect {\n", 172 " fill: lightgray;\n", 173 " fill-opacity: 0.5;\n", 174 " stroke: black;\n", 175 " stroke-width: 1;\n", 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"cell_type": "code", 270 "execution_count": 5, 271 "metadata": { 272 "collapsed": false 273 }, 274 "outputs": [ 275 { 276 "data": { 277 "text/plain": [ 278 "Index([u'__comm', u'__cpu', u'__line', u'__pid', u'__tgid', u'acc_load_avg',\n", 279 " u'acc_util_avg', u'cfs_rq', u'delta_us', u'load_avg', u'load_err',\n", 280 " u'load_sum', u'sum_err', u'util_avg', u'util_err'],\n", 281 " dtype='object')" 282 ] 283 }, 284 "execution_count": 5, 285 "metadata": {}, 286 "output_type": "execute_result" 287 } 288 ], 289 "source": [ 290 "df = trace.data_frame.trace_event('pelt_update')\n", 291 "rq_df = df[df.cfs_rq == 1]\n", 292 "rq_df.columns" 293 ] 294 }, 295 { 296 "cell_type": "code", 297 "execution_count": 6, 298 "metadata": { 299 "collapsed": false 300 }, 301 "outputs": [ 302 { 303 "name": "stdout", 304 "output_type": "stream", 305 "text": [ 306 "UTIL ERROR\n" 307 ] 308 }, 309 { 310 "data": { 311 "text/html": [ 312 "<table style=\"border-style: hidden;\">\n", 313 "<tr>\n", 314 "<td style=\"border-style: hidden;\"><div class=\"ilineplot\" id=\"fig_9fb104a68b8b43debeafadd416b51f51\"></div></td>\n", 315 "</tr>\n", 316 "<tr>\n", 317 "<td style=\"border-style: hidden;\"><div style=\"text-align:center\" id=\"fig_9fb104a68b8b43debeafadd416b51f51_legend\"></div></td>\n", 318 "</tr>\n", 319 "</table>\n", 320 "<script>\n", 321 "var fig_9fb104a68b8b43debeafadd416b51f51_data = {\"logscale\": false, \"strokeWidth\": 1.0, \"pointSize\": 2, \"name\": \"fig_9fb104a68b8b43debeafadd416b51f51\", \"step_plot\": false, \"fill_graph\": false, \"title\": \"\", \"drawPoints\": false, \"per_line\": 1, \"height\": 400, \"rangesel\": false, \"data\": {\"labels\": [\"index\", \"Trace 0:pelt_update:util_avg\", \"Trace 0:pelt_update:acc_util_avg\"], \"data\": [[1.09999999997612e-05, 255, 255], [5.699999999952965e-05, 255, 255], [0.0005100000000002325, 260, 260], [0.000512000000000068, 255, 266], [0.002489999999999881, 255, 255], [0.007591000000000125, 228, 228], [0.009558999999999873, 354, 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388 " /* TRAPPY_PUBLISH_IMPORT = \"plotter/js/ILinePlot.js\" */\n", 389 " /* TRAPPY_PUBLISH_REMOVE_START */\n", 390 " var ilp_req = require.config( {\n", 391 "\n", 392 " paths: {\n", 393 " \"dygraph-sync\": '/nbextensions/plotter_scripts/ILinePlot/synchronizer',\n", 394 " \"dygraph\": '/nbextensions/plotter_scripts/ILinePlot/dygraph-combined',\n", 395 " \"ILinePlot\": '/nbextensions/plotter_scripts/ILinePlot/ILinePlot',\n", 396 " \"underscore\": '/nbextensions/plotter_scripts/ILinePlot/underscore-min',\n", 397 " },\n", 398 "\n", 399 " shim: {\n", 400 " \"dygraph-sync\": [\"dygraph\"],\n", 401 " \"ILinePlot\": {\n", 402 "\n", 403 " \"deps\": [\"dygraph-sync\", \"dygraph\", \"underscore\"],\n", 404 " \"exports\": \"ILinePlot\"\n", 405 " }\n", 406 " }\n", 407 " });\n", 408 " /* TRAPPY_PUBLISH_REMOVE_STOP */\n", 409 " ilp_req([\"require\", \"ILinePlot\"], function() { /* TRAPPY_PUBLISH_REMOVE_LINE */\n", 410 " ILinePlot.generate(fig_1f01fdec8fa347758094d7b73cb64817_data);\n", 411 " }); /* TRAPPY_PUBLISH_REMOVE_LINE */\n", 412 " </script>\n", 413 " " 414 ], 415 "text/plain": [ 416 "<IPython.core.display.HTML object>" 417 ] 418 }, 419 "metadata": {}, 420 "output_type": "display_data" 421 } 422 ], 423 "source": [ 424 "# Plot the accurate and the actual signals for the RQ\n", 425 "print 'UTIL ERROR'\n", 426 "trappy.ILinePlot(trace.ftrace,\n", 427 " signals = [\n", 428 " 'pelt_update:util_avg',\n", 429 " 'pelt_update:acc_util_avg',\n", 430 " ]).view()\n", 431 "\n", 432 "print 'LOAD ERROR'\n", 433 "trappy.ILinePlot(trace.ftrace,\n", 434 " signals = [\n", 435 " 'pelt_update:load_avg',\n", 436 " 'pelt_update:acc_load_avg',\n", 437 " ]).view()" 438 ] 439 }, 440 { 441 "cell_type": "markdown", 442 "metadata": {}, 443 "source": [ 444 "Data showing util/load errors on the RQ (cpu 1) when thread0 running\n", 445 "-------------------------------\n", 446 "Note that, as expected, the error exists only for cases where delta is < 1ms (now - last_update_time)" 447 ] 448 }, 449 { 450 "cell_type": "code", 451 "execution_count": 31, 452 "metadata": { 453 "collapsed": false, 454 "scrolled": false 455 }, 456 "outputs": [ 457 { 458 "name": "stdout", 459 "output_type": "stream", 460 "text": [ 461 "number of errors: 11\n" 462 ] 463 }, 464 { 465 "name": "stderr", 466 "output_type": "stream", 467 "text": [ 468 "/home/joelaf/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:3: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n", 469 " app.launch_new_instance()\n", 470 "/home/joelaf/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:8: FutureWarning: sort(columns=....) is deprecated, use sort_values(by=.....)\n" 471 ] 472 }, 473 { 474 "data": { 475 "text/html": [ 476 "<div>\n", 477 "<table border=\"1\" class=\"dataframe\">\n", 478 " <thead>\n", 479 " <tr style=\"text-align: right;\">\n", 480 " <th></th>\n", 481 " <th>__comm</th>\n", 482 " <th>acc_load_avg</th>\n", 483 " <th>util_avg</th>\n", 484 " <th>acc_util_avg</th>\n", 485 " <th>util_err</th>\n", 486 " <th>delta_us</th>\n", 487 " <th>load_sum</th>\n", 488 " <th>sum_err</th>\n", 489 " <th>load_avg</th>\n", 490 " <th>load_err</th>\n", 491 " <th>util_err_pc</th>\n", 492 " </tr>\n", 493 " <tr>\n", 494 " <th>Time</th>\n", 495 " <th></th>\n", 496 " <th></th>\n", 497 " <th></th>\n", 498 " <th></th>\n", 499 " <th></th>\n", 500 " <th></th>\n", 501 " <th></th>\n", 502 " <th></th>\n", 503 " <th></th>\n", 504 " <th></th>\n", 505 " <th></th>\n", 506 " </tr>\n", 507 " </thead>\n", 508 " <tbody>\n", 509 " <tr>\n", 510 " <th>6.986053</th>\n", 511 " <td>thread0</td>\n", 512 " <td>91</td>\n", 513 " <td>76</td>\n", 514 " <td>89</td>\n", 515 " <td>13</td>\n", 516 " <td>45</td>\n", 517 " <td>4356860</td>\n", 518 " <td>-46080</td>\n", 519 " <td>76</td>\n", 520 " <td>15</td>\n", 521 " <td>17.105263</td>\n", 522 " </tr>\n", 523 " <tr>\n", 524 " <th>3.749162</th>\n", 525 " <td>thread0</td>\n", 526 " <td>88</td>\n", 527 " <td>75</td>\n", 528 " <td>87</td>\n", 529 " <td>12</td>\n", 530 " <td>519</td>\n", 531 " <td>4219977</td>\n", 532 " <td>-531456</td>\n", 533 " <td>76</td>\n", 534 " <td>12</td>\n", 535 " <td>16.000000</td>\n", 536 " </tr>\n", 537 " <tr>\n", 538 " <th>3.749187</th>\n", 539 " <td>thread0</td>\n", 540 " <td>88</td>\n", 541 " <td>75</td>\n", 542 " <td>87</td>\n", 543 " <td>12</td>\n", 544 " <td>28</td>\n", 545 " <td>4248649</td>\n", 546 " <td>-28672</td>\n", 547 " <td>76</td>\n", 548 " <td>12</td>\n", 549 " <td>16.000000</td>\n", 550 " </tr>\n", 551 " <tr>\n", 552 " <th>6.986014</th>\n", 553 " <td>thread0</td>\n", 554 " <td>90</td>\n", 555 " <td>76</td>\n", 556 " <td>88</td>\n", 557 " <td>12</td>\n", 558 " <td>590</td>\n", 559 " <td>4310780</td>\n", 560 " <td>-604160</td>\n", 561 " <td>76</td>\n", 562 " <td>14</td>\n", 563 " <td>15.789474</td>\n", 564 " </tr>\n", 565 " <tr>\n", 566 " <th>4.355859</th>\n", 567 " <td>thread0</td>\n", 568 " <td>85</td>\n", 569 " <td>73</td>\n", 570 " <td>83</td>\n", 571 " <td>10</td>\n", 572 " <td>435</td>\n", 573 " <td>4059408</td>\n", 574 " <td>-445440</td>\n", 575 " <td>74</td>\n", 576 " <td>11</td>\n", 577 " <td>13.698630</td>\n", 578 " </tr>\n", 579 " <tr>\n", 580 " <th>4.355883</th>\n", 581 " <td>thread0</td>\n", 582 " <td>85</td>\n", 583 " <td>73</td>\n", 584 " <td>83</td>\n", 585 " <td>10</td>\n", 586 " <td>27</td>\n", 587 " <td>4087056</td>\n", 588 " <td>-27648</td>\n", 589 " <td>74</td>\n", 590 " <td>11</td>\n", 591 " <td>13.698630</td>\n", 592 " </tr>\n", 593 " <tr>\n", 594 " <th>6.075973</th>\n", 595 " <td>thread0</td>\n", 596 " <td>86</td>\n", 597 " <td>75</td>\n", 598 " <td>85</td>\n", 599 " <td>10</td>\n", 600 " <td>27</td>\n", 601 " <td>4125064</td>\n", 602 " <td>-27648</td>\n", 603 " <td>75</td>\n", 604 " <td>11</td>\n", 605 " <td>13.333333</td>\n", 606 " </tr>\n", 607 " <tr>\n", 608 " <th>5.982620</th>\n", 609 " <td>thread0</td>\n", 610 " <td>227</td>\n", 611 " <td>211</td>\n", 612 " <td>225</td>\n", 613 " <td>14</td>\n", 614 " <td>684</td>\n", 615 " <td>10844301</td>\n", 616 " <td>-700416</td>\n", 617 " <td>212</td>\n", 618 " <td>15</td>\n", 619 " <td>6.635071</td>\n", 620 " </tr>\n", 621 " <tr>\n", 622 " <th>0.736533</th>\n", 623 " <td>thread0</td>\n", 624 " <td>401</td>\n", 625 " <td>380</td>\n", 626 " <td>398</td>\n", 627 " <td>18</td>\n", 628 " <td>854</td>\n", 629 " <td>19171804</td>\n", 630 " <td>-874496</td>\n", 631 " <td>383</td>\n", 632 " <td>18</td>\n", 633 " <td>4.736842</td>\n", 634 " </tr>\n", 635 " <tr>\n", 636 " <th>4.983089</th>\n", 637 " <td>thread0</td>\n", 638 " <td>398</td>\n", 639 " <td>385</td>\n", 640 " <td>396</td>\n", 641 " <td>11</td>\n", 642 " <td>545</td>\n", 643 " <td>19047561</td>\n", 644 " <td>-558080</td>\n", 645 " <td>387</td>\n", 646 " <td>11</td>\n", 647 " <td>2.857143</td>\n", 648 " </tr>\n", 649 " <tr>\n", 650 " <th>4.983090</th>\n", 651 " <td>thread0</td>\n", 652 " <td>398</td>\n", 653 " <td>385</td>\n", 654 " <td>396</td>\n", 655 " <td>11</td>\n", 656 " <td>1</td>\n", 657 " <td>19047561</td>\n", 658 " <td>0</td>\n", 659 " <td>387</td>\n", 660 " <td>11</td>\n", 661 " <td>2.857143</td>\n", 662 " </tr>\n", 663 " </tbody>\n", 664 "</table>\n", 665 "</div>" 666 ], 667 "text/plain": [ 668 " __comm acc_load_avg util_avg acc_util_avg util_err delta_us \\\n", 669 "Time \n", 670 "6.986053 thread0 91 76 89 13 45 \n", 671 "3.749162 thread0 88 75 87 12 519 \n", 672 "3.749187 thread0 88 75 87 12 28 \n", 673 "6.986014 thread0 90 76 88 12 590 \n", 674 "4.355859 thread0 85 73 83 10 435 \n", 675 "4.355883 thread0 85 73 83 10 27 \n", 676 "6.075973 thread0 86 75 85 10 27 \n", 677 "5.982620 thread0 227 211 225 14 684 \n", 678 "0.736533 thread0 401 380 398 18 854 \n", 679 "4.983089 thread0 398 385 396 11 545 \n", 680 "4.983090 thread0 398 385 396 11 1 \n", 681 "\n", 682 " load_sum sum_err load_avg load_err util_err_pc \n", 683 "Time \n", 684 "6.986053 4356860 -46080 76 15 17.105263 \n", 685 "3.749162 4219977 -531456 76 12 16.000000 \n", 686 "3.749187 4248649 -28672 76 12 16.000000 \n", 687 "6.986014 4310780 -604160 76 14 15.789474 \n", 688 "4.355859 4059408 -445440 74 11 13.698630 \n", 689 "4.355883 4087056 -27648 74 11 13.698630 \n", 690 "6.075973 4125064 -27648 75 11 13.333333 \n", 691 "5.982620 10844301 -700416 212 15 6.635071 \n", 692 "0.736533 19171804 -874496 383 18 4.736842 \n", 693 "4.983089 19047561 -558080 387 11 2.857143 \n", 694 "4.983090 19047561 0 387 11 2.857143 " 695 ] 696 }, 697 "execution_count": 31, 698 "metadata": {}, 699 "output_type": "execute_result" 700 } 701 ], 702 "source": [ 703 "errpc_fn = (lambda row: (row['util_err'] * 100.0 / row['util_avg']))\n", 704 "\n", 705 "err_df = rq_df[(rq_df.util_err > 10) | (rq_df.load_err > 10)][rq_df['__comm'] == 'thread0']\n", 706 "err_df = err_df[['__comm', 'acc_load_avg', 'util_avg', 'acc_util_avg', \\\n", 707 " 'util_err', 'delta_us', 'load_sum', 'sum_err', 'load_avg', 'load_err']]\n", 708 "\n", 709 "err_df['util_err_pc'] = err_df.apply(errpc_fn ,axis=1)\n", 710 "\n", 711 "err_df = err_df.sort(columns=['util_err_pc'], ascending=False)\n", 712 "print 'number of errors: ' + str(len(err_df))\n", 713 "\n", 714 "err_df.head(40)\n" 715 ] 716 }, 717 { 718 "cell_type": "markdown", 719 "metadata": {}, 720 "source": [ 721 "# Summary of issues\n", 722 "\n", 723 "### * At 5.98s, there is a 6% error in util_avg 225 vs 211) - this causes a glitch and makes the signal less smooth\n", 724 "----\n", 725 "\n", 726 "\n", 727 "\n", 728 "### * At 3.06s, there is a 3% error in util_avg - causing lowered peak of util_avg (397 -> 387) with delta ~450us\n", 729 "\n" 730 ] 731 }, 732 { 733 "cell_type": "markdown", 734 "metadata": {}, 735 "source": [ 736 "<p style=\"page-break-after:always;\"></p>\n", 737 "# Histogram of Errors before and after fix\n", 738 "\n", 739 "## BEFORE: util_avg and load_avg occurences of errors" 740 ] 741 }, 742 { 743 "cell_type": "code", 744 "execution_count": 8, 745 "metadata": { 746 "collapsed": false, 747 "scrolled": false 748 }, 749 "outputs": [ 750 { 751 "name": "stderr", 752 "output_type": "stream", 753 "text": [ 754 "/home/joelaf/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n", 755 " if __name__ == '__main__':\n" 756 ] 757 }, 758 { 759 "data": { 760 "image/png": 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PAABgBJQ/AACAEVD+AAAARkD5AwAAGAHlDwAAYASUPwAAgBFQ/gAAAEZA+QMA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\nk5yfyQkWpmaOjN9J8ndJdk/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761 "text/plain": [ 762 "<matplotlib.figure.Figure at 0x7f31e572f0d0>" 763 ] 764 }, 765 "metadata": {}, 766 "output_type": "display_data" 767 } 768 ], 769 "source": [ 770 "df = rq_df[(rq_df.util_err > 0) | (rq_df.load_err > 0)][rq_df['__comm'] == 'thread0']\n", 771 "df = df[(df.util_err > 0) | (df.load_err > 0)]\n", 772 "df = df[['util_err', 'load_err']].plot(kind='hist', figsize=(15,7), bins=60, xlim=(0, 20), xticks=range(0,20), stacked=True, title = 'Occurence of errors > 10 counts', )" 773 ] 774 }, 775 { 776 "cell_type": "markdown", 777 "metadata": {}, 778 "source": [ 779 "## AFTER fix: util_avg and load_avg occurences of errors" 780 ] 781 }, 782 { 783 "cell_type": "markdown", 784 "metadata": {}, 785 "source": [ 786 "" 787 ] 788 }, 789 { 790 "cell_type": "code", 791 "execution_count": null, 792 "metadata": { 793 "collapsed": true 794 }, 795 "outputs": [], 796 "source": [] 797 }, 798 { 799 "cell_type": "code", 800 "execution_count": null, 801 "metadata": { 802 "collapsed": true 803 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