basics/matmul/compiler_opt/gcc_opt_flags.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5429e851-f070-4ee4-81ea-dcf9fdaf3795",
   "metadata": {
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    "tags": []
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   "source": [
    "# Imports, definitions and compiler path\n",
    "\n",
    "The GCC optimization flags are listed here: https://gcc.gnu.org/onlinedocs/gcc/Optimize-Options.html\n",
    "\n",
    "Note that some optimizations made by the compiler do not have an explicit flag, therefore they cannot be individually called. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "defcc79f-7227-4e70-af54-f843055da321",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import subprocess\n",
    "import matplotlib.pyplot as plt\n",
    "import sys\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "87271db7-ecd4-454e-8e51-0b93b14e036c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gfortran is available\n"
     ]
    }
   ],
   "source": [
    "# set environment (gfortran here)\n",
    "# If you start this notebook from a conda env, sometimes your PATH variable will not include everything that is under your user-defined environment (it may not load your ~/.bashrc). \n",
    "# In my case, I ran this notebook in a Mac where GCC was installed via Homebrew. Therefore, I had to do:\n",
    "# os.environ['PATH'] = os.environ['PATH'] + ':/opt/homebrew/bin'\n",
    "# for this to work properly. On a shared environment this is less likely to happen, but you may need to do a 'module load gcc'\n",
    "try:\n",
    "    comp = subprocess.run(['gfortran', '--version'])\n",
    "    print('gfortran is available')\n",
    "except:\n",
    "    print('gfortran could not be found. Make sure your PATH is set up correctly.')\n",
    "    sys.exit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "e745bb16-f8b3-411d-92ab-dfbfd4a25ac8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# define compiler name and source file name\n",
    "compiler = 'gfortran'\n",
    "sourcefile = 'matmul.f90'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2a538d07-7bbc-408f-affd-7b7fca87915d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def retrieve_time(stdout):\n",
    "    \"\"\"\n",
    "    Retrieves time from subprocesses.run.stdout (specific to this code)\n",
    "    You may have to adjust this depending on the standard Fortran format output of your machine.\n",
    "    \"\"\"\n",
    "    x = str(stdout)\n",
    "    x = x.replace(\"s\", \"\")\n",
    "    x = x.replace(\"\\\\n\", \"\")\n",
    "    x = x.replace(\"b\", \"\")\n",
    "    x = x.replace(\"'\", \"\")\n",
    "    return float(x[-25:-8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "a9a83115-b480-40ea-91de-e3b8f3f8007f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# list of flags from GCC documentation\n",
    "o1flags=\"-fauto-inc-dec -fbranch-count-reg -fcombine-stack-adjustments -fcompare-elim -fcprop-registers -fdce -fdefer-pop -fdelayed-branch -fdse -fforward-propagate -fguess-branch-probability -fif-conversion -fif-conversion2 -finline-functions-called-once -fipa-profile -fipa-pure-const -fipa-reference -fipa-reference-addressable -fmerge-constants -fmove-loop-invariants -fomit-frame-pointer -freorder-blocks -fshrink-wrap -fshrink-wrap-separate -fsplit-wide-types -fssa-backprop -fssa-phiopt -ftree-bit-ccp -ftree-ccp -ftree-ch -ftree-coalesce-vars -ftree-copy-prop -ftree-dce -ftree-dominator-opts -ftree-dse -ftree-forwprop -ftree-fre -ftree-phiprop -ftree-pta -ftree-scev-cprop -ftree-sink -ftree-slsr -ftree-sra -ftree-ter -funit-at-a-time\"\n",
    "o1flags_list = o1flags.split(\" \")\n",
    "\n",
    "o2flags=\"-falign-functions -falign-jumps -falign-labels -falign-loops -fcaller-saves -fcode-hoisting -fcrossjumping -fcse-follow-jumps -fcse-skip-blocks -fdelete-null-pointer-checks -fdevirtualize -fdevirtualize-speculatively -fexpensive-optimizations -ffinite-loops -fgcse -fgcse-lm -fhoist-adjacent-loads -finline-functions -finline-small-functions -findirect-inlining -fipa-bit-cp -fipa-cp -fipa-icf -fipa-ra -fipa-sra -fipa-vrp -fisolate-erroneous-paths-dereference -flra-remat -foptimize-sibling-calls -foptimize-strlen -fpartial-inlining -fpeephole2 -freorder-blocks-algorithm=stc -freorder-blocks-and-partition -freorder-functions -frerun-cse-after-loop -fschedule-insns -fschedule-insns2 -fsched-interblock -fsched-spec -fstore-merging -fstrict-aliasing -fthread-jumps -ftree-builtin-call-dce -ftree-pre -ftree-switch-conversion -ftree-tail-merge -ftree-vrp\"\n",
    "o2flags_list = o2flags.split(\" \")\n",
    "\n",
    "o3flags=\"-fgcse-after-reload -fipa-cp-clone -floop-interchange -floop-unroll-and-jam -fpeel-loops -fpredictive-commoning -fsplit-loops -fsplit-paths -ftree-loop-distribution -ftree-loop-vectorize -ftree-partial-pre -ftree-slp-vectorize -funswitch-loops -fvect-cost-model -fvect-cost-model=dynamic -fversion-loops-for-strides\"\n",
    "o3flags_list = o3flags.split(\" \")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8429ff74-0297-49ad-a423-2d5d6afb6677",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "# Using explicit individual flags"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c6f7f06-88c0-4b0d-867f-da8062892779",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## GCC O1 Flags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "50c535c2-d62e-43c3-a2ab-d58715566327",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-fauto-inc-dec b' Matrix multiplication took:    2.4272870000000002       s\\n'\n",
      "-fbranch-count-reg b' Matrix multiplication took:    2.4028450000000001       s\\n'\n",
      "-fcombine-stack-adjustments b' Matrix multiplication took:    2.4098210000000000       s\\n'\n",
      "-fcompare-elim b' Matrix multiplication took:    2.4021340000000002       s\\n'\n",
      "-fcprop-registers b' Matrix multiplication took:    2.4295399999999998       s\\n'\n",
      "-fdce b' Matrix multiplication took:    2.4273130000000003       s\\n'\n",
      "-fdefer-pop b' Matrix multiplication took:    2.4448910000000001       s\\n'\n",
      "-fdelayed-branch b' Matrix multiplication took:    2.4013720000000003       s\\n'\n",
      "-fdse b' Matrix multiplication took:    2.4012390000000003       s\\n'\n",
      "-fforward-propagate b' Matrix multiplication took:    2.4033850000000001       s\\n'\n",
      "-fguess-branch-probability b' Matrix multiplication took:    2.4008650000000000       s\\n'\n",
      "-fif-conversion b' Matrix multiplication took:    2.4196670000000000       s\\n'\n",
      "-fif-conversion2 b' Matrix multiplication took:    2.4014759999999997       s\\n'\n",
      "-finline-functions-called-once b' Matrix multiplication took:    2.4081579999999998       s\\n'\n",
      "-fipa-profile b' Matrix multiplication took:    2.4681949999999997       s\\n'\n",
      "-fipa-pure-const b' Matrix multiplication took:    2.4035730000000002       s\\n'\n",
      "-fipa-reference b' Matrix multiplication took:    2.4070960000000001       s\\n'\n",
      "-fipa-reference-addressable b' Matrix multiplication took:    2.4081120000000000       s\\n'\n",
      "-fmerge-constants b' Matrix multiplication took:    2.4423480000000000       s\\n'\n",
      "-fmove-loop-invariants b' Matrix multiplication took:    2.3992540000000000       s\\n'\n",
      "-fomit-frame-pointer b' Matrix multiplication took:    2.4120349999999999       s\\n'\n",
      "-freorder-blocks b' Matrix multiplication took:    2.4023209999999997       s\\n'\n",
      "-fshrink-wrap b' Matrix multiplication took:    2.4555609999999999       s\\n'\n",
      "-fshrink-wrap-separate b' Matrix multiplication took:    2.4314119999999999       s\\n'\n",
      "-fsplit-wide-types b' Matrix multiplication took:    2.4310829999999997       s\\n'\n",
      "-fssa-backprop b' Matrix multiplication took:    2.4361160000000002       s\\n'\n",
      "-fssa-phiopt b' Matrix multiplication took:    2.4583869999999997       s\\n'\n",
      "-ftree-bit-ccp b' Matrix multiplication took:    2.4202059999999999       s\\n'\n",
      "-ftree-ccp b' Matrix multiplication took:    2.4120159999999999       s\\n'\n",
      "-ftree-ch b' Matrix multiplication took:    2.4543990000000000       s\\n'\n",
      "-ftree-coalesce-vars b' Matrix multiplication took:    2.4089990000000001       s\\n'\n",
      "-ftree-copy-prop b' Matrix multiplication took:    2.4269360000000000       s\\n'\n",
      "-ftree-dce b' Matrix multiplication took:    2.4025900000000000       s\\n'\n",
      "-ftree-dominator-opts b' Matrix multiplication took:    2.4428619999999999       s\\n'\n",
      "-ftree-dse b' Matrix multiplication took:    2.4093679999999997       s\\n'\n",
      "-ftree-forwprop b' Matrix multiplication took:    2.4157050000000000       s\\n'\n",
      "-ftree-fre b' Matrix multiplication took:    2.4411600000000000       s\\n'\n",
      "-ftree-phiprop b' Matrix multiplication took:    2.4448999999999996       s\\n'\n",
      "-ftree-pta b' Matrix multiplication took:    2.4467400000000001       s\\n'\n",
      "-ftree-scev-cprop b' Matrix multiplication took:    2.4303879999999998       s\\n'\n",
      "-ftree-sink b' Matrix multiplication took:    2.4022139999999998       s\\n'\n",
      "-ftree-slsr b' Matrix multiplication took:    2.4426070000000002       s\\n'\n",
      "-ftree-sra b' Matrix multiplication took:    2.4260989999999998       s\\n'\n",
      "-ftree-ter b' Matrix multiplication took:    2.4436449999999996       s\\n'\n",
      "-funit-at-a-time b' Matrix multiplication took:    2.4153130000000003       s\\n'\n",
      "ALL b' Matrix multiplication took:    2.4704919999999997       s\\n'\n"
     ]
    }
   ],
   "source": [
    "t1=[]\n",
    "for flag in o1flags_list:\n",
    "        comp = subprocess.run([compiler, flag, sourcefile], capture_output=True)\n",
    "        if comp.returncode != 0:\n",
    "            print('Compilation with this flag failed', flag)\n",
    "            print('Error message: ', comp.stderr)\n",
    "        else:\n",
    "            run = subprocess.run(['./a.out'], capture_output=True)\n",
    "            print(flag, run.stdout)\n",
    "            t1.append(retrieve_time(run.stdout))\n",
    "# now combine all flags\n",
    "cmd = o1flags_list.copy()\n",
    "cmd.insert(0, compiler)\n",
    "cmd.append(sourcefile)\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('ALL', run.stdout)\n",
    "    t1.append(retrieve_time(run.stdout))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "6cb4854d-8159-434c-958e-f687bbc004ec",
   "metadata": {},
   "outputs": [
    {
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MapjqIakHkZlRzyKHkXYub+26z1bANiWFVr2KTwE2JbOlfoVcfuOVg1fZzMzMBrJkCSxcCMuXQ0T+XbjQQaOZ2RpAEWt3zpf58+fH0qVLp7saZmZmM9e8eRkk9po7F5Ytm+ramJlZD0mXRMT8frdN9zqMZmZmNtNdf33ZdjMzGxoOGM3MzGxyjbXmsddCNjMbeg4YzczMbHIdcQTMnj162+zZud3MzIaaA0YzMzObXAsWwOLFOWdRyr+LF+d2MzMbalO+DqOZmZmthRYscIBoZrYGcg+jmZmZmZmZ9eWA0czMzMzMzPpywGhmZmZmZmZ9OWA0MzMzMzOzvhwwmpmZTYYlS2DePJg1K/8uWTLdNTIzMyvmLKlmZmZtW7IEFi6ElSvz+vLleR2cKdTMzNYo7mE0MzNr26JFI8Fix8qVud3MzGwN4oDRzMysbddfX7bdzMxsSNUakirpccAzgMcB9wc2BP4CXAOcA3wzIm6arEqamZmtUebMyWGo/babmZmtQcbtYZT0CklXAucDbwZmA78GfgbcBDwWOA74vaQTJW09udU1MzNbAxxxBMyePXrb7Nm53dZ8TmhkZmuRMXsYJV0O3Bf4AvBy4LKIiD732xTYG1gA/ELSgRHx5Umqr5mZ2fDrJLZZtCiHoc6Zk8GiE96s+ZzQyMzWMuoTA+YN0puBT0fEbbULk3YEtoyIM9qp3uSbP39+LF26dLqrYWZmZmuCefP6DzeeOxeWLZvq2piZtULSJRExv99tY/YwRsT/lD5QRFwOXF66n5mZmdkawQmNzGwt0zhLqqTNJD1G0vptVsjMzMxsaI2VuMgJjcxshqoVMEp6l6Qju64/CVgGXAT8WtK2k1M9MzMzsyHihEZmtpap28P4MuDarusfJoee7gP8GXh/u9UyMzMzG0ILFsDixTlnUcq/ixc74Y2ZzVi11mEEHkAup4GkLYCdgCdHxI8lrQd8YpLqZ2ZmZjZcFixwgGhma426PYx3AetV/z8JuA34aXX9RmCzlutlZmZmZmZm06xuwPgL4GWSNgJeCZwTEf+qbnsQcMNkVM7MzMzMzMymT90hqYcD3wIWAP8Cnt5127OAn7dcLzMzMzMzM5tmtQLGiDhD0sOARwOXRcRvu24+F6+9aGZmZmZmNuPU7WEkIq4Druuz/TOt1sjMzMzMzMyGwphzGCU9urQwSRtI2m6wKpmZmZmZmdkwGC/pzbmSvi3pGZLGTY4jaY6kd5I9kHu3WkMzMzMzMzObFuMNSX0o8H4y2c3Nki4g5yreCNwO3Bt4MLAzsD0ZLP5nRHxxUmtsZmZmZmZmU2LMgDEifg+8UtI7gAPJzKhvATbsutt1ZNKbdwBnRERMYl3NzMzMzMxsCk24DmNE3BARH4qIPSPinsBmwP2B9SNim4g4MCJOrxMsSjpU0sWSbpZ0o6TTJG1ft7KStpW0QtItPdt3lxR9Lp5PaWZmZmZm1tCEAWOviPh7RPwpIv7V4PF2B44BngDsCdwJnClps4l2lLQecArZozmWfwe26rr8ukEdzczMzMzMjIJlNdoQEU/vvi5pf+AfwC7AaRPs/iHgCuAcYLcx7nNDRPxl0HqamZmZmZlZgx7Glm1c1eGm8e4kaS8y++rBE5S3VNIfJZ0laY+W6mhmZmZmZrZWmu6A8SjgMuCCse4gaSvgs8D+EbFijLv9EXg98HxgX+Aa4CxJTxqjzIWSlkpaeuONNw5QfTMzMzMzs5lrSoekdpP0MWBXYNeIuGucu54MHBsRF451h4i4hgwSOy6QNA94K33mPEbEYmAxwPz5853Z1czMzMzMrI9p6WGU9HHgJcCeEXHtBHffEzhM0p2S7gSOB+5ZXV84zn4/A7Ztp8ZmZmZmZmZrn6IeRkmPAJ4E3Af4TET8SdK/AX8eZ7hobxlHAS8Gdo+Iq2vsskPP9ecCi4Cdgd+Ps98jyaGqZmZmZmZm1kCtgFHS+uTQ0H0BAUFmNf0T8GHgf4F31CjnU8D+wD7ATZK2rG66JSJuqe5zJLBzRDwZICKu6iljPnB393ZJbwaWAb8A1gNeVj3G8+s8PzMzMzMzM1td3SGpRwBPIYO9+5FBY8f3gaf326mPg8jMqGeRvX+dy1u77rMVsE3N8jrWAz5CLrvxE3Ju5F4R8fXCcszMzMzMzKxSd0jqS4B3RcQXJa3Tc9t1wLw6hUSEatzngAluPxE4sWfbh8meTjMzMzMzM2tJ3R7G+wC/GqeM9dupjpmZmZmZmQ2LugHjdcDjx7htZ0YvaWFmZmZmZmYzQN2A8QvAOyQtIOcLAoSkPYD/AD43GZUzMzMzMzOz6VM3YPww8F3gJOBv1bbzgDOB0yPi6Emom5mZmZnZ2mXJEpg3D2bNyr9Llkx3jWwtVyvpTUTcBby4Whbj6cB9gb+SweI5k1g/MzMzM7O1w5IlsHAhrFyZ15cvz+sACxZMX71sraaImO46TKv58+fH0qVLp7saZmZmZra2mzcvg8Rec+fCsmVTXRtbi0i6JCLm97ut7rIanYJErpO4Qe9tEXFts+qZmZmZmRnXX1+23WwK1AoYJd0H+BTwvHH26V2f0czMzMzM6pozp38P45w5U18Xs0rdHsbjgT2ATwJXA3dMWo3MzMzMzNZGRxwxeg4jwOzZud1smtQNGPcADomIEyexLmZmZmZma69OYptFi3IY6pw5GSw64Y1No7oB49+AP09mRczMzMzM1noLFjhAtKFSdx3Go4HXVUlvzNY+XhPJzMzMJuLzBZuB6q7D+DFJ9wd+KelM4KbV7xKHtV47s2HgNZHMzMxsIj5fsBmq1jqMkp4FfA1Yf4y7RESskVlSvQ6jTchrIpmZmdlEfL5ga7Dx1mGsOyT1Y8DFwI7A+hExq+eyRgaLZrV4TSQzMzObiM8XbIaqGzDOAT4QEVdGxL8ms0JmQ2estY+8JpKZmZl1+HzBZqi6AeOlwP0nsyJmQ+uII3INpG5eE8nMzMy6+XxhODkR0cDqBowHA2+VtMtkVsZsKC1YAIsX5xwEKf8uXuwJ7GZmZjbC5wvDp5OIaPlyiBhJROSgsUjdpDf/B2wCbATcCvy95y4REXNbr90UcNIbMzMzM7MZyImIahsv6U2tZTWAs4CJI0szMzMzM7Nh4ERErai7DuMBk1wPMzMzM1vTLFkCixblCficOTlfz0MwbVjMmdO/h9GJiIrUncNoZmZmZjbC88NsItOdcMaJiFoxZsAo6eWS7tP1/7iXqauymZkNrek+OTCzqbNoEaxcOXrbypW53WwYGhSciKgVYya9kXQ38LiIuKj6fzwREeu0Xrsp4KQ3ZmYt6ZwcdJ9Azp7tH2ezmWrWrAwEeklw90SnjjbjOeHMGmW8pDfjBYxzgT9GxB3V/+OKiD5HxPBzwGhm1hKfHJitXfyZt/G4QWGN0ihLancAuKYGg2ZmNoWcjc5s7XLEEf1HFXh+mIETzswgtZLeSLpL0s5j3PYYSXe1Wy0zM1vjjHUS4JMDs5nJ88NsPE44M2PUzZKqcW5bB6/RaGZmPjkwW/ssWJDDT+++O/+uycGik3a1yw0KM8a46zBKmsVIsDirut5tQ+CZwF8moW5mZrYm6ZwEeE02M1vT9Cbt6mT0BH+HDWLBAr9+M8B4SW8OA95Ts5xjIuJNrdVqCjnpjZmZmdlazgl8bC3XKOkN8OPO/mTgeDzwu5773A78EvhOzYocCuwLPLTa90Lg0Ii4qub+2wI/JwPdjca4z65V3a+OiO3rlGtmZmZmazEn7TIb03hZUs8BzgGQFMBnI+IPAz7e7sAxwMVkIHo4cKakh0fE38bbUdJ6wCnAucBuY9zn3sAXgLOABwxYVzMzMzNbGzijp9mYaiW9iYj3tRAsEhFPj4gTIuKqiLgS2B/YAtilxu4fAq4ATh3nPscDnwcuGLSuZmZmZraWcNIuszHVzZI6WTau6nDTeHeStBewN3DwOPc5CNgS+ECbFTQzMzOzGc4ZPc3GNG6W1ClwFHAZ4/QIStoK+Cywb0SskFZf4UPSDsBhwOMi4q5+9zEzMzMzG5Mzepr1NW0Bo6SPAbsCu0bEXePc9WTg2Ii4cIxy1ifnNr41Iq6r+dgLgYUAczw23czMzMzMrK8xl9WY1AeVPg68GNgjIq6e4L4BdAeUIoex3gUcBPwAuK7nPp31I+8CnhURPxirfC+rYWZmZmZma7Omy2pMVmWOIoPF3ScKFis79Fx/LrAI2Bn4PXBLn/scBDwVeB6wbJD6mpmZmZmZra1qB4ySHgy8EJgDbNBzc0TEq2qU8SkyM+o+wE2StqxuuiUibqnucySwc0Q8uSr4qp4y5gN392zvvc8NwO1113c0MzMzMzOz1dUKGCU9l1zOYhZwA3B7z13qjms9qPp7Vs/29wHvrf7fCtimZnlmZmZmZmY2SWrNYZR0JfBHYEFE3DjptZpCnsNoZmZmZmZrszbmMD4Y+M+ZFiyamZmZmZnZ2GbVvN/VwH0msyJmZmZmZmY2XOoGjG8H3lklvjEzMzMzM7O1QN0hqe8lexh/JenXwN96bo+I2K3NipmZmZmZmdn0qhsw3gVcM5kVMTMzMzMzs+FSK2CMiN0nuR5mZmZmZmY2ZOrOYTQzMzMzM7O1TO2AUdJWkj4i6WJJv5V0kaQPS9pyMitoZmZm02zJEpg3D2bNyr9Llkx3jczMbIrUChglPQS4DDgYuAW4CLgVOAS4TNK2k1VBMzMzm0ZLlsDChbB8OUTk34ULHTSama0l6vYwfgi4GXhIROwRES+JiD2AhwD/qG43MzOzmWbRIli5cvS2lStzu5mZzXh1A8Y9gHdHxLLujRGxnFxyY492q2VmZmZD4frry7abmdmMUjdgXA9YMcZtK6rbzczMbKaZM6dsu5mZzSh1A8bLgDdJGnV/SQIOqm43MzOzmeaII2D27NHbZs/O7WZmNuPVWocROBz4DvArSV8G/ghsCewHbAvsNTnVMzMzs2m1YEH+XbQoh6HOmZPBYme7mZnNaIqIeneUngF8AHgUICCAS8i5jWdMWg0n2fz582Pp0qXTXQ0zMzMzM7NpIemSiJjf77a6PYxExOnA6ZJmA/cGboqIlRPsZmZmZmZmZmuo2gFjRxUkOlA0MzMzMzOb4cYMGCW9BzguIv5Q/T+eiIj3t1s1MzMzMzMzm07j9TC+Fzgd+EP1/3gCcMBoZmZmZmY2g4wZMEbErH7/m5mZmZmZ2dqhViAoaY6ke4xx27qSvHqvmZmZmZnZDFO35/A6cjmNfnasbjczMzMzM7MZpG7AqHFuuwdwdwt1MTMzMzMzsyEyXpbUewGbdW16gKQH99xtQ+AVwJ/ar5qZmZmZmZlNp/GypB4CHEZmQA3gq2PcT9X9zMzMzMzMbAYZL2D8JrCMDAg/B3wA+G3PfW4HfhkRV0xG5czMzMzMzGz6jLesxuXA5QCSAvhORPx1qipmZma21luyBBYtguuvhzlz4IgjYMGC6a6VmZmtRcbrYVwlIj4/2RUxMzOzLkuWwMKFsHJlXl++PK+Dg0YzM5sydbOkIml7SR+X9D1JP+q5nDWZlTQzM1vrLFo0Eix2rFyZ20ssWQLz5sGsWfl3yZK2amhmZmuBWj2Mkh4LnEPOadwWuAK4NzAH+B3wm0mqn5mZ2drp+uvLtvfjXkozMxtQ3R7G/wd8Hfh3MgnOqyJiHvAUYB0yIY6ZmZm1Zc6csu39tNVLaWZma626AeMjgJPJ5TUgg0Qi4kdksHhknUIkHSrpYkk3S7pR0mmStq9bWUnbSloh6Zae7btJOl/SXyX9U9LVkt5at1wzM7Ohc8QRMHv26G2zZ+f2utropTSzNY+HoluL6gaM9wBujYi7gb8BW3Xddg1QN+jbHTgGeAKwJ3AncKakzSbaUdJ6wCnAuX1uvgX4BPAk4OFkEPs+SQfVrJeZmdlwWbAAFi+GuXNByr+LF5cNJW2jl9LM1iydoejLl0PEyFB0B43WkCJi4jtJlwAfjYgvSvoRcDOwb3Xz54EnRMQ2xQ8ubQT8A9gnIk6b4L4fB+5FzqX8ZERsNMH9vw7cHhEvGe9+8+fPj6VLlxbV28zMbI3QO4cRspeyNPA0szXHvHkZJPaaOxeWLZvq2tgaQtIlETG/3211exhPI3sHIeczPpMMGm8CXgp8rGHdNq7qcNN4d5K0F7A3cHCdQiU9iuzFPKdhvWxYeEiFmVlzbfRSmtmaxUPRrWW1ehhX2ykDsucDs4HTI+IHjR5c+gqZdXV+RNw1xn22Ai4B9o2ICyUdwBg9jJJ+B2xBZn99X0QcPkaZC4GFAHPmzHnM8n6tMDb93DJuZmZmVsY9jNZAGz2Mo0TEpRHxroh4ywDB4seAXYHnjxUsVk4Gjo2IC2sU+0RgPvA64M2S9u93p4hYHBHzI2L+FltsUVp1myrO7mdmZmZWpo2EWWZdagWMkh4n6YVj3LZftU5jbdV8xJcAe0bEtRPcfU/gMEl3SroTOB64Z3V9YfcdI+K6iLgyIj5LDpN9b0m9bMh4SIWZmZlZGQ9Ft5atW/N+R9I/OynAw4DXk4HdhCQdBbwY2D0irq6xyw49158LLAJ2Bn4/zn6zgPXr1MmG1Jw5/YdUOLufmZmZ2dgWLHCAaK2pOyR1R2CsIaEXkes0TkjSp4ADyd7FmyRtWV026rrPkZLO6lyPiKu6L2SQeHd1/aZqnzdJ2rtap3FbSa8C3koOZ7U1lYdUmJmZmZlNq7o9jBswdnC5DnDPmuV01kU8q2f7+xgZProVULpExzrAh4B55NqOvwXeAXy6sBwbJp2WsUWLchjqnDkZLLrFzMzMzMxsSpSsw7g0Il7b57bPAI+NiEe2X73J53UYzczMzMxsbTZeltS6PYyfBj4j6Wbgs8DvgAeQS1O8ipGeQzMzMzMzM5shas1h7Mo6+h/Ar4AVwNXV9Y9HxOJJq+HaxgvVt8+vqZmZmZlZI3V7GImIt0o6FngKcB/gL8CZNZbFsLp6F6pfvjyvg+ftNeXX1MzMzMyssVpzGGeyoZrDOG9e/2Uk5s6FZcumujYzg19TMzObqZYscWI4M2tFozmMkuYAf4yIf1X/jysivJr6oLxQffv8mpqZ2UzkETRmNkXGm8N4HfCo6v9l1fXxLjaosRak90L1zfk1NTOzmWjRopFgsWPlytxuZtai8QLGV5LrGXb+n+hig/JC9e3za2pmZjORR9DY2sLJC6fdmENSI+LzXf+fOCW1Wdt5ofr2+TU1M7OZaM6c/nP0PYLGZhIPvR4KTnozTElvzMzMzOroPZGGHEGzeLFPpG3mcPLCKdM06c3nCh4jIuJVxTUzMzMzs3IeQWNrAw+9HgrjrcO4J1C3+3Ht7qY0MzMzm2oLFjhAtJnNQ6+HwnhzGOdNYT3MzMzMzMxGHHFE/6HXTl44pcbLkmpmZmZmZjY9FizIeblz54KUfz1Pd8qNNyR1FEnrAC8HHg88APg9cD5wUkTcNTnVMzMzMzOztZaHXk+7Wj2MkuYCvwCOB54B3Lf6+zngqup2MzMzMzMzm0HqDkn9JLAJsGtEzImInSJiDvBEYFPg6MmqoJmZmZmZmU2PugHjnsChEXF+98aI+Cnwzup2MzMzMzMzm0HqBoy3ADeMcdsNwMoxbjMzMzMzM7M1VN2A8WTgdWPc9lrgC+1Ux8zMzMzMzIZF3SypvwH2k3Ql8DXgz8D9gBcAGwPfl/TKzp0j4nNtV9TMzMzMzMymVt2A8VPV3wcC/97n9mO6/g8ye6qZmZmZmZmtweoGjFtPai3MzMzMzMxs6NQKGCNi+WRXxMzMzMzMzIZL3aQ3ZmZmZmZmtpYZs4dR0rXA8yLicknXkXMTxxIRsU3rtTMzMzMzM7NpM96Q1HOAm7v+Hy9gNDMzMzMzsxlmzIAxIg7s+v+AKamNmZmZmZmZDY1acxglvUfS/ce4bStJ72m3WmZmZmZmZjbd6ia9OYxcg7Gf+1e3m5mZmZmZ2QxSN2DUOLfdG7i9hbqYmZmZmZnZEBkvS+ruwJ5dm14rae+eu20I7AX8ovWamZmZmZmZ2bQar4dxN+Bd1SWAA7uudy5vAm4DDq7zYJIOlXSxpJsl3SjpNEnb162spG0lrZB0S8/2fSX9oCpzhaSfSXpO3XLNzMxsDbBkCcybB7Nm5d8lS6a7RmZmM96YAWNEvC8iZkXELHJI6uM617suG0TEoyPigpqPtztwDPAEsvfyTuBMSZtNtKOk9YBTgHP73Lwb8COyt/NRwPeAb0h6Ys16mZmZ2TBbsgQWLoTlyyEi/y5c6KDRzGyS1ZrDWAWHFw36YBHx9Ig4ISKuiogrgf2BLYBdauz+IeAK4NQ+5R4SER+MiIsi4jcR8T7gEmCfQetsZpPAvQRmVmrRIli5cvS2lStzu5mZTZrx5jDOKSkoIq5v8Pgbk0HrTePdSdJewN7Ao4HnF5Q9brlmNg06vQSdE79OLwHAggXTVy8zG27Xj3GaMdZ2MzNrxZgBI7CMnLtY1zoNHv8o4DJgzCGtkrYCPgvsGxErpPEStq7a5w3kMiAnjXH7QmAhwJw5RXGxmQ1qvF4CB4xmNpY5c7KBqd92MzObNOMFjK+kLGAsIuljwK7ArhFx1zh3PRk4NiIurFnu84H/Bl4cEX1+WSAiFgOLAebPnz9pz9HM+nAvgZk1ccQRo0cnAMyendvNzGzSjBkwRsSJk/Wgkj4OvBjYIyKuneDuewK7STqsszswS9KdwEFV8Ncp9/lkr+LLI+Lbk1B1MxuUewnMrInOCIRFi7KBac6cDBY9MsHMbFKN18M4KSQdRQaLu0fE1TV22aHn+nOBRcDOwO+7yn0h8HngFRHx1Zaqa2Ztcy+BmTW1YIEDRDOzKVYrYJT0uQnuEhHxqhrlfIrMjLoPcJOkLaubbomIW6r7HAnsHBFPrgq+qqeM+cDd3dslvZjsWXwrcG5XuXdExN8mqpeZTSH3EpiZmZmtMer2MO7J6vMZNyMzkf69utRxUPX3rJ7t7wPeW/2/FbBNzfI6Xkc+l/+pLh3nkGs/mtkwcS+BmZmZ2RqhVsAYEfP6bZf0JODTQK0zv4iYMMVpRBwwwe0nAif2bNu9zuObmZmZmZlZfbMG2TkizgU+DhzdTnXMzMzMzMxsWAwUMFauBR7VQjlmZmZmZmY2RAYKGCWtCxwA/K6V2piZmZmZmdnQqJsl9Ud9Nq8HPAS4D5l0xszMzMzMzGaQullSZ7F6ltQVwNeBUyLix21WyszMzMzMzKZf3Sypu09yPczMzMzMzGzItJH0xszMzMzMzGagMXsYJe1ZUlBE9JvnaGZmZmZmZmuo8YaknsnIvEWNcZ+obgtgnRbrZWZmZmZWz5IlsGgRXH89zJkDRxwBCxZMd63MZoSJ5jCuAL5WXW6d/OqYmZmZmRVYsgQWLoSVK/P68uV5HRw0WjvW8gYJRfQmP61ukHYDXg48n5zr+A3g8zNt6On8+fNj6dKl010NMzMzM2ti3rwMEnvNnQvLlk11bWym6W2QAJg9GxYvnlFBo6RLImJ+39vGChi7dt4A2BfYH3gK8EdgCfCFiPhVy3Wdcg4YzczMzNZgs2ZBv/NZCe6+e+rrYzPLWtIgMV7AOGGW1Ii4LSK+GBHPBOYARwHPAq6S9Ml2q2pmZmZmVmDOnLLtZiWuv75s+wxUuqzGX4Fl1SWAe7dcHzMzMzOz+o44IocIdps9O7ebDcoNEvUCRkm7SPo0ORz188AtwF7kMFUzMzMzs+mxYEHOJ5s7N4ehzp074+aX2TRyg8S46zD+GxkQvgyYB5wLvBU4NSJumZLamZmZmZlNZMECB4g2OTrHlbOk9rlBuhu4Gfg6cBLQZ7bniIi4tvXaTQEnvTEzMzMzs7XZeElvJlqHcRPgAOAVNR5nncJ6mZmZmZmZ2RAbL2A8cMpqYWZmZmZmZkNnzIAxIj4/lRUxMzMzMzOz4VK6rIaZmZmZmZmtJRwwmpmZmZmZWV8OGM3MzMzMzKwvB4xmZjbzLFkC8+bBrFn5d8mS6a6RDQsfG2ZmRSZaVsPMzGzNsmQJLFwIK1fm9eXL8zqsVQstWx8+NszMiikiprsO02r+/PmxdOnS6a6GmZm1Zd68DAR6zZ0Ly5ZNdW1smPjYMDPrS9IlETG/320ekmpmZjPL9deXbbe1h48NM7NiDhjNzGxmmTOnbLutPXxsmJkVc8BoZmYzyxFHwOzZo7fNnp3bbe3mY8PMrJgDRjMzm1kWLIDFi3NempR/Fy92UhPzsWFm1sCUJr2RdCiwL/BQ4HbgQuDQiLiq5v7bAj8n671R1/atgI8Cjwa2BU6KiAPqlOmkN2ZmZmZmtjYbpqQ3uwPHAE8A9gTuBM6UtNlEO0paDzgFOLfPzesDfwE+CPysrcqamZmZmZmtzaY0YIyIp0fECRFxVURcCewPbAHsUmP3DwFXAKf2KXdZRBwcEScCf2uzzmstL2xsZmZmZrbWW3eaH39jMmi9abw7SdoL2Jsccvr8KajX2s0LG5uZmZmZGdOf9OYo4DLggrHuUM1P/Cywf0SsaONBJS2UtFTS0htvvLGNImeWRYtGgsWOlStzu5mZmVmbPKrJbKhNW8Ao6WPArsDzI+Kuce56MnBsRFzY1mNHxOKImB8R87fYYou2ip05vLCxmZmZTYXOqKblyyFiZFSTg0azoTEtAaOkjwMvAfaMiGsnuPuewGGS7pR0J3A8cM/q+sLJrutayQsbm5mZTS73qiWPajIbelMeMEo6CngpGSxeXWOXHYBHdl3eA/yz+n+1BDjWAi9sbGZmNnncqzbCo5rMht6UBoySPgUcSPYu3iRpy+rSvabikZLO6lyvMqquugC/B+6urt/Utd8jJT0S2ATYrLr+8Kl6bjOKFzY2MzObPO5VG+FRTWZDb6p7GA8iM6OeBfyx6/LWrvtsBWzToOxLq8sTgWdX/39vkMqu1RYsgGXL4O6786+DRZuJPCRsNL8eZlPDvWojPKrJbOhN6bIaEaEa9zlggttPBE5sUraZ2SpePmY0vx5mU2fOnPyM9du+tul8vyxalAHznDkZLPp7x2xoKCKmuw7Tav78+bF06dLproaZTbV58/qfsM2dm73qaxu/HmZTp7eBBrJXzdM/zGyaSLokIub3u22612E0M5seHhI2ml8Ps6njXAFmtgZxwGhma6eZlmhh0PmHM+31MBt2zhVgZmsIB4xmtnaaSYkW2kjRP5NeDzMzM2uNA0YzWzvNpCFhbaTon0mvh5mZmbXGSW+c9MbM1nSzZmXPYi8ph7uZmZmZjcNJb8zMZjLPPzQzM7NJ4oDRzGxN5/mHZmZmNkkcMJqZrek8/9DMzMwmybrTXQEzM2vBggUOEM3MzKx17mE0MzMzMzOzvhwwmpmZmZmZWV8OGM3MzMzMzKwvB4xmZmZmZmbWlwNGMzMzMzMz68sBo5mZmZmZmfXlgNHMzMzMzMz6csBoZjbdliyBefNg1qz8u2TJdNfIzMzMDHDAaLb2cXAyXJYsgYULYflyiMi/Cxf6fTEzM7Oh4IDRbG3i4GT4LFoEK1eO3rZyZW43MzMzm2YOGGci9yDZWBycDJ/rry/bbmZmZjaFHDDONO5BsvE4OBk+c+aUbTcza4sbmM2sBgeMM417kGw8Dk6GzxFHwOzZo7fNnp3bbfr4RNpmOjcwm1lNDhhnmmHqQfIJ1/BxcDJ8FiyAxYth7lyQ8u/ixbndpodPpG1t4AZmm4jP46yiiJjuOkyr+fPnx9KlS6e7Gu2ZNy9PbnrNnQvLlk1dPTonXN0/RrNn+0R4GCxZkicE11+fPYtHHOH3xKzbsHyPmk2mWbOyQaSXBHffPfX1seHi87i1jqRLImJ+39scMM6wgHFYPuA+4TKzNZVPpG1t4N9pG4+Pj7XOeAGjh6TONMMyvG2YhsYOCw/taJdfT5ssnutrawNPUbDx+DzOujhgnIkWLMjWn7vvzr/TMXTAJ1yjtTUnykFS8hwzm0w+kba1wbA0MNtw8nmcdXHAaJPDJ1yjtZFcYFiCpGEIWp2swSaTT6RtbTEMDcw2nHweZ108h3GmzWEcJk6uMqKNOVHDMJ9gWObIeo6ZmZnZ5PJ53FrFSW/G4YDRpkQbwd4wBEnDELQOUz3MzMzMZoChSXoj6VBJF0u6WdKNkk6TtH3B/ttKWiHplj637SbpEkm3SbpW0uvarb3ZANoY2jEM8wmGZRK8h8qYmZmZTYmpnsO4O3AM8ARgT+BO4ExJm020o6T1gFOAc/vctjXwPeB84FHAkcDRkp7fWs3NBtHGnKhhCJKGIWgFzzEzMzMzmyLTOiRV0kbAP4B9IuK0Ce77ceBewDnAJyNio67bPgTsGxHbdm07Dvj3iHj8eOV6SKqtUaZ7PsGwzGE0MzMzs9YMzZDUPjau6nDTeHeStBewN3DwGHd5PPCDnm1nAPMl3WPQSpoNjenOaOeePTMzM7O1ynQHjEcBlwEXjHUHSVsBnwX2j4gVY9xtS+DPPdv+DKwLbN6nzIWSlkpaeuONNzapt9naa7qDVpv5hmHpFjMzMwOmMWCU9DFgV+D5EXHXOHc9GTg2Ii6coMjesbUaYzsRsTgi5kfE/C222KJ2nc3MbJINy3qjZmZmBkxTwFjNR3wJsGdEXDvB3fcEDpN0p6Q7geOBe1bXF1b3+RPZy9jtvmRSnb+2WHUzM5tMixaNniMLeX3Roumpj5mZ2Vpu3al+QElHAS8Gdo+Iq2vsskPP9ecCi4Cdgd9X2y4A9um531OBpRHxr+a1NTOzKTUsS7eYmZkZMPXrMH4KOJDsXbxJ0pbVpTvj6ZGSzupcj4irui9kkHh3db2TLOfTwAMl/Y+kh0l6NXAA8JGpem5mZtaCYVm6xczMzICpH5J6EJkZ9Szgj12Xt3bdZytgm5JCI+I64FnAk8gkOouAgyPia4NX2czMpswwrDdqZmZmq0zpkNSIUI37HDDB7ScCJ/bZfg7w6IZVMzOzYdDJujud642amZnZKlM+h9HMzGxcCxY4QDQzMxsS070Oo5mZmZmZmQ0pB4xmZmZmZmbWlwNGMzMzMzMz68sBo5mZmZmZmfXlgNHMzMzMzMz6csBoZmZmZmZmfTlgNDMzMzMzs74cMJqZmZmZmVlfDhjNzMzMzMysLweMZmZmZmZm1pciYrrrMK0k3Qgsn+569LE58BeX4TKGuIxhqIPLcBmTXcYw1MFluIzJLmMY6uAyXMZklzEMdWirjMkwNyK26HtLRPgyhBdgqctwGcNcxjDUwWW4jMkuYxjq4DJcxmSXMQx1cBkuY7LLGIY6tFXGVF88JNXMzMzMzMz6csBoZmZmZmZmfTlgHF6LXYbLGPIyhqEOLsNlTHYZw1AHl+EyJruMYaiDy3AZk13GMNShrTKm1Fqf9MbMzMzMzMz6cw+jmZmZmZmZ9eWA0czMzMzMzPpywGhmZjOC0oOmux5mZmYziQPGISLpnpJmdV2fJWn2dNZD0kMkPUfSPRqWtYmkzTqXhmXMkrRJk33bIGlfSR+T9FFJz5vGeuwq6cDq/y0kbT0Nddi7+xhd00maK+kp1f8bStq4QRkbSnpow8df7T1s8r628TzaJOnekh7RYL9dJN2z+v9l1edubt39Iyflf7P0cYfZsL23TUg6q862mmVtMshrIOnRkg6W9CZJj25aziAkbSNp/er/3av63Gua6tL4+6tPWdP9Wz3t721Vj4GO0aqM+0qa07k02H89SY+QtIOk9Rrs/6o+2z5YsP8sSU8ofdy2SVpH0pnTXY9+JP10uutQYsac+M0QZwHdAeJsoOhAl3SlpCt6Lj+R9HFJ96lZzLnABpIeUNXpQODEwnq8VtKfgSuAS6rL0oL9v1h96d4T+CVwjaS3FdZhtqR3S/psdX1bSXsXlnEM8DrgSuAq4LWSPlVYxhaS3ilpsaTPdS6FZRwG/BdwaLXpHsDJhWUM/HoALwZ+LenDkh5WuG+nHutLemn1mrync6m57yaSjpR0kqSX9tx2TGE9XgN8FfhMtemBFAYbkp4NXAacXl1/pKRvFxTxtT7bvlpYhzaeRxuflR9X789mwOXACZI+VlIGcCywUtKOwNuB5cAXCsu4UNJOhfuMUh3fm0i6h6SzJP1F0ssKy9hA0lskfV3S1yT9h6QNCsto471t47k8WNJp1b43SPqWpAfX2G+D6njYXNmI0Gk8nAfcv7AO8yVdSf6mXCXpckmPKSzjPcDngfsAm5PH6LsKy3iIpM9K+oGkH3UuJWWQn/u7JP0bcDywNfDFwnq0cXwN+v3V1m/1Q6pj86rq+iMavC9tvLf3k3S8pO9X1x+uPoHTOPu3cYw+R9KvgeuAc4BlwPcLy9gL+C3wCeCTwG8kPbOkDOAFkhZ0lXkMsEXdnSPibuCjhY/Zl6TtJb1Q0ss7l4J63EX+pmw6YB3aOH/qVdwQMK0iwpchuQCX1dk2QRkfBo4EdqguR1SX/wJOq1nGz6u/bwLeXv1/aWE9fg1sPuhrASwAPkYGSFcUlvFl8qTzqur6hg1ez19QZROurs8CflFYxvnAh4AXAs/vXEpfD0Dd78N0vB7VfpsArwUuBC4AFgIbF+x/eldd/rNzqbnv14APAvsA366ur9993Ba+puv1vKZXFpZxCbBp6fsCbFcdB78F9u26HNDg+GrjebTxWbm0+vtq4H0Nj9HOd897gFc1fF9/CdxVvbZXkI09pfW4rPr7PPIkdDPg8sIyvkIGA3tUl8XAqdPw3rbxXC4E9gfWrS4vA35WY79DyBPf26u/ncvlwBsL63AF8MSu67s2eF9/BWzQdX1D4FeFZVwOvB7YGXhM51JYRuc4fxvwpur/SwvLaOP4avT9NcbxNchv9TnV69ldj6um4b39Pvk7fXl1fd2Sz1tLx+jlZNB7aXV9D2BxYRlXA//WdX0b4OrCMjYEfgi8hGy0+5+S/asy3kf+zql0364yDgPOBv4MnAD8CfhqYRlfAa6vPi+f6FwKy2jl/KmnzOsH2X+qL+tiw+RWSY+OiJ8DVC1T/ywsY5eI2KXr+pWSfhoRuxS0KkvS48kfgE7rWumx8ltgZeE+3e6hHAa7D/DJiPiXpNI1YLaJiBdJeglARPxTkgrLuIZsBVpeXX8Q+aNQYnZE/FfhPr3uiIjovAZVa26pNl4PIuJmSV8jvzDfTJ6Ivk3SJyLi6BpFPDAinlH6uJVtIuL51f/flLQI+JGk5zQo6/aIuKPzEkhaFyg9xu6MiH80eBkfCuwN3At4dtf2FcBrCstq43m0cWysK2kr8oRrUeG+HSskHUoGJE+StA55AlqitCW9n85jPgv4UkT8rcl7HBE7dl0/W9LlhWW08d628VwUESd1XT9Z0hsn2ikijgKOkvSmmt8N41kRET/pKvs8SSsKy1gGbADcVl1fn/ytKnFnRBxbuE+vf1WftVcw8vkvPc7bOL6afn916/dbXVrG7Ii4qGe/OwvLWMbg7+3mEfGV6juIiLhT0l0F+7dxjP4rIv6qHNI5KyLOlvShwjJuiIjfdF2/Frihzo4aPXXo1eSIhp8Ch0vaLCL+VlCPtwD3BO6UdBvZ6B0RUTJs+QXAjmQAfaCk+wHHFewP8N3qMohGv5GS9h3rJvIcao3hgHG4vBk4VdIfqutbAS8qLGMjSY+NiJ8BSNoZ2Ki6re4X8CHk0MdvRMQvlEOPzi6sx6HA+ZJ+RrYuAxARB9fc/9PkD8DlwLnKeUw3F9bhDkkbUp1gSdqmuy413Qf4laSLqus7ARd0hu1ERJ1A5TuSnhUR3yt87G5fkfQZ4F7KYWqvBD5bWMbAr0cVmB1ItlieBOwcETco59r+CqhzUni+pB0i4sqi2qf1qx/RuwEi4ghJvyOHUW80/q6rOUfSO4ENJT0VOAg4rbCMq5RDY9eRtC1wMNmjPK6I+BbwLUmPj4gLCh+zVxvPo43PyvuAM4DzIuLi6nvj14VlvAh4Kdm7+Cfl3J3/LikgIpZL2hXYNiJOkLQF5cfGaZKuJhvsDqrKuG2CfXpdKulxEXEhgKTHkideJdp4b9t4LmdLegdwCnmMvAj4bufkssZJ5HGS3kL2uATwE+DTEVFSj4uq78AvddXhx6rmqnUaWidwO/ALST+syngqcJ6kT1RljPn71HUifZqkg4BvMPq3reRE+kByqsMREXGdct5y0RQD2jm+Gn1/9fgMq/9W/6OwjL9U3zmd758XAH8sLKPxe9vlVuXUnU49HkfZc2njGP27pI3I37Qlkm6gPHj+haTvkT1rAewHXNwJXiLi6+Pse0m1j7r+7lVdAphwKHpHRLQx3/qfEXG3pDuV82NvKKlDVY/PV79vcyLimob1aPob+exxbvtOw7pMC1XdojYkqpa6h5If0qsj4l+F++8EfI6RE6QVZCvRL4C9IuIrNcrYLyJOnWjbBGVcBJxHDge7u7M9Ij5fY99ZwAu661q15KwTEbW/OKsTrHcBDwd+AOwCHBARPy4oY7fxbo+Ic8bZdwUjX7j3JL9c/kWzVrbO83latf8ZEfHDwv2fRvb8dL8eB0ZE7cYASV8AjouIc/vc9uSImDCRhaRfAv/GyFC1zusxYZIUSR8GfhARZ/ZsfwZwdERsW++ZrDrOXkXXa0o+t9pfilWgvKinjPfXPRGuns8HyJP508mW1DdHRO2Tx5aeRxuflV0i4qcTbZugjA/19sb32zZBGYcB88kemIdIuj85VG+XCXbtLefewM0RcZeyR3+jiPhzwf6/Ir/Lr682zSEbVe6m/vG+2nsbEaUNRf2ey8YR8aeC/a8b5+aIiHFP4CR9hfwt6hzXLwHuHRH7FdRhvO+piIg9a5TxivFuH+/3qXoNOt/n/R6/1kmsstf88xFRNI+0TzltHF/d31+Q3x0fKAnkJW0dEdd1XRc5HLJ2Y1HVuLQYeAJwE/nb8LKIWFZQRuP3tquMR5ONntuTOQu2IM9Fao0qaukYvSf5ezCLHOW1KXBySYOEpBMmqMcr65Y1CEm7kMM2b1WOcHs0ObT1+gl27S7jGOCdZP6E/wRuqco8sKCMZwMfAdaLiK0lPRI4vGaDf6eMgX8j+5T5/Ijol8dgKDlgHCLVl/dbgLkR8Zqqxe+hEVHcCqGc4KuI+HuDfX8eEY+eaNsEZZwfEY0zZEk6NyKe1HT/rnLuAzyO/JG/MCL+0qCM+5E9iwAXRUStoR1tqn5EbqtO+B5Knih8v0GDwkCvR0sn9HP7bY+I5f22T5bu17S6vg45H3KQodSldbgsIh6pzL67D/AfwNkxeqjZRGW08jxaODba+N7oV8YVdU5+u+5/GfAocp7YoxqW8bnuk6qqxf9bEfHkgjL6HucddY53SYdEDuscd9sEZXR+V+ZExMJBfleaknR57zHdb9sU1GPaP/PV454BPDsi7higjIGPrzaM8Zm9JCKKkr1U+90TmBURpcM4O/uvBzykunpNye9jdSwcTAaMnUb7ojLa0MZvbIt1eQIwj67RiBFROwmZpCvIRtBHkCOSjgf2jYhxG+K79hc5heX/quvzgE3qBvBd5VwC7An8uOs34cqI2KGwnIHPJ3vKuz4i1pjEN86SOlxOAO4AHl9d/x3Z+1CbqixfwCkR8XcVZPmS9ExJRwMPkPSJrsuJlA+JOFvSQklbqdmyGj+U9FZJD2q4P9VJ+J0R8d3q5OhOSfsUlvFC4CJySMcLgZ8ph8sU1UNdGbok3au0HuTwlPWVmWvPpFnm2rMi4q+d1yMi/qLy1PZP7bOtaM5YdSJzL3KoxrOBe5We3GiATKtdzmL0HIINqZmVWJkx8ttjXQrqsNr8soJ9OwZ5Ho/uXIC55DCwPwBzVDMtvaTHS/pPYAtl1sbO5b3AOjXLeL0yu+BDNTrD83XkKIUSd1S9q4PM9/29pGOr/e9NtigXDRmMiOXVcf3Pqi6Rm1dtr6Nfr8kBJfVg5Hel04DX5HflHsrlCr5aXd6osqWWLlUO7+uUVzx8UtL/U9fSE8qsq0XPgwE+K12P+4Y+9TiosB7LgJ8qsy6u+syUFDDW92jJ8SXph32eyxk1991O0vOBTZVLT3UuB5BzCWuTdIhyuOFK4OOSfq4cEVNSxu7kEPhPAccA/yupdqNz1Yjw3Ii4MyJ+ERFXNWiQ3VS5FNDS6vJRlWfnHPg3VtIDJX1DmdH4z8osug8sLOMkslduV7LBfCdy5EaJO6vv4ucCR1UNXbWHqVb7frPr+rLSYLGrHr1Di5v0lj2A/E1bj5xjP9b8xLoGmjw81TyHcbi0kXjiRPIEoZN04n/J7E7H19j3D+TSF88hx7F3rCB7Pkp0ljw4tGtbyfj3Tuv+GxruD3BYRHxj1c4ZQB9GWVr6RcBOnV5F5fyfMylb+qCNeigiVlbB/9ER8WFJl9baMVOtz6ZKbc/Il9Qm1ExtL+n15PypbZSthh0bU37idwiZ2KUzj+JkSYujLCnGt8i5JZdQPteuY4OIuKVzJSJuUf11Tz/S8DF7tTG/bJDnMV7a8yBbZSeyHjkEfl1GnwzcTCYsqOOLZIbCI4F3dG1f0SCI7jfftyhJQkS8W9KHJH2azIL5wdKhQ8r5vh8lP2M3kAH5r4B/r7HvS8jv0K17GiA2Bv5aUg/a+V05lmzc6Cxds3+17dU1938s8HJJo4ZPVo0EUbP395kR8c7OlYi4SdKzyGFidQ3yWel4TUSsWlqpqsdrGHlt6vhDdZlFwQl0t5a+RzfvHoVUPZf71ty3zcRdr4yIoyQ9Hbgv2SB6AtlQU9dHgadFNUdN0kPIuYQlPZ0/lfRJ8pzp1s7GqDf3EHI60FVk4zLk5+QEMgP2uLp+Yx/c9Rsr8ru1dG7qCeR3amfI98uqbf2C0bHMBx5eBW1NtZHE7EJJO0XExQPUY+C5usql0B5BTu/qTLMKRj5/TaxRQzwdMA6XNhJPNM7yFRGXA5dL+uKgwzAiYqBF5Qfdv9KvB730mJ8Vo4eg/nWMcie7HlLzzLWvJRMq3Z8MsDonizeTrbF1tHlC/yrgsRFxK+RwG3J5jpITnUEyrXY0zkoc48xdLRER76ief2d+2a1ka2yJQZ7HHoWP1a+Mc8jkLCc2HQZXtf7+A3hJdVJxP/L43kjSRlEw5yUiPqKcb3IzeVL7nqg537enxfgi4N3V35C0b4yfLKLX+8nhS2dGxKMk7UHO3avjfLK3d3NGB/UrKM/S3Mbvyk49w0d/pLKMnIN+ViFP9taPiNsBque0fmEZbWQinyVJnRPp6ngtWhg9It5X+Jj9tPE9erekOZ3Pl3KYa62T2Gg3cVfnN+lZwAkRcXmDRo17RFdCk4j4X5X1gsNIL/zhXdvqNpzB6CzeAO9TDpGvo83f2C0ionse44mS3lxYxlXAlpQnH+o2cBIzYA9y/evlZBBfO+dBlzeRjf+3k6/zGeT3c4nHRcTDC/eh0yjW7ybyd26N4YBxuBxGJr54kKQlVJNqC8sYNMsXwM7K4WRzyWOk8wGts1DznhHxo7G66uuecKmdeTdLlQuHf4p8Pd7E6J7TOk5XDtH5UnX9RUBpttM26vFmGmaujXZS20dELJP0ht4bVJ5qW+Q6eR13UT40Y5BMqx1vpmFWYklfiYgXjvVjUPhj9jBgnnLJhI6SxerfzIDZlate6IMYLIvl+pIWs/qcl7onWyiXangvueZWdytuyfzDznyfH/bZNpHejHaXki3iz6a8Nblxevwq8F7OyPSEQbTxu3KXpG0i4rcA1fdP7eUGIjPX7gg8sdr0k6qBssTJwFnKhB5B9hxPmMikx5sZPBP5GWQv9qereryOauH7uqqRBG8ne5tXDd8s+azQzvfoIjKTaKcB7Enkurol/izpNLJxJMig9T8i4tqCMi6R9ANga+BQSRvTlSyvoIzjyblykI2rtX5nNTIv+N0RcV7h43b7p6RdO2Uok77UbbzrbjR7NCPfxT8FSgPGvyiTzHTOW15C+ciEzYFfKhMYdmcDrp0oJjKx1se6rl9P2W8btLNM0l4RsYiu5Z4k7QfUTuRIZsd/eET8svCx9+6zTcADyWQ+awwnvRkyGjzxxEBZvqoyriaHoF5C1w9SREz4hSPpfRFxmPpn6YqomZ1L0perx395RGxftSZfEBGPrLN/VcY9yR6Cp5Cv5w/IDHC3jrvj6uXsS355Czi3e3jpVNajDZK2J7N8dZ+kTPgFLuk7EbG3+mcKrNWY0FXWW8i5WZ3XcR/gxIj4n4IyGmda7SmnUVZiSfePiD9owAQ+ynki25ALtHc+axH1l5/plDNoduU2slheTi6H0/u9UbtxRNJvyF6T0pOb7jIGTpzTBklnksf2keTJ1w1kT13tZGBVg9/RZKPCeuT8mVujPMPyoL8re5LTHa6typhLQYZlrT588nnkYuRFDVjKbMirvkcjotZ8u54yBv2szCKDqu7v8+OiSqRTs4wfkMMe30oGnK8AbqzZqNEp4z/IwL/x92hVzuaMHBsXNDg2LiQbQzvByYuBN0XEYwvKmAU8Erg2csrGfYAHFJ63rE9OYVn1Ww0c0+mRnmDfTvKxoiRdfcrZkQyIOvMWbwJeUfg83k0Oae18VvYhszzXnq9b9eR9kmxwCnLEwiElI0A0Rob4OqNrNJIhfrWbKMwQX42I+F1E3K6cp/oI4AtRkNBxjN+E0oRsTyKXNPoTDc85lNlZX0q+v9cBX4uIT9bdf7o5YBwCmiC5RNQcP6+WsnxJ+lnJl/1kkLQ0IuZLujRGslpNeVa96nG3JOfg3A1cHAXp6Ft47NMYZ4hQSWufct7k7mTA+D2y5e68iChK4tOGrhbUThBeaz5m1/6tZFpVwyxwnR8bSSdFxP4lj9lTzq8YfJ5I4+fRtf/AWSzVMDNiTxlnA0+NguVzuvZdNQeI0Qt2bwz8NAqWMZD0efIE6+/V9XsDH63b4FXt0y89/pKSYFjSUvIE/FRyTtHLySULFo274+rldBq9gvzM12706vpdOYbRgVbtYa3KOVmPj5Hhk/ckg5OSk62tgT92er2rRsT7RdnSC28g34O/V9fvDbwkIkrmH3aXt2p4a+F+l0TEY7obMiSdE/WzR84ig7zbaPA92tY5R1XWaucLki6MiMeNtU/b9ahejysiYvs69++z/5fI4GoLRn93lCz5tA451/ltygQ+RETp2tGd34RH9RznP4+Ih9Xcv5VlW4aFckjvfPL37Qzg2+Ros2fV2PeZ5DDnF5INNB2bkL+7OxfU4zfkqLfepeLGPedQzqV9MSO9vF8G3hoR42Y5HkYekjocOnNUNiA/GJeTX1SPAH5G/iBMKHIO1HMj4uPkxNymzpb032QLV/dQhAm/vDVBpreI+Nh4t3dpPO+m5SDr1cB7gB+R78nRkg6PiM8VlPEQsiV5HuVD9TrJVfYl5xN09wAtq1uHygvIFNeXRsSByuVCaiUDaeOHXdImEXGzMtvtMrrqr8JhrdHCELexeveoN2RmPeW6X09Qn+HXUX+u28DzRAZ8Hh1tLALexoLm15ILXX+3p4w63xttzgF6RKyeDORRdXeuTtq+FRFPIU8uSodOrhIRv5G0TtWDdYKk0mQNx5C98Z0eoNdKekpErDa8fIzHv0vSc6rflSYZCoFWhk+eysgcs04ZpzKy5FEdbSSs6XYcubZcqU4j7h8l7UUmwKmdxTJyIfOPRsTjgeKAlZbOOSpnS3oHcAqsWqz+u9X3/ESf/+56PIY8vpqc+9wt6XJ1zccsEREvqRqGzyCT/hWrPiePqf4vDhS7LCNfj850gPUZHcTWqccWktaLBsu2SDovInbt00s4Lb2DwN2RuTj2JddwPFo1E/7RbiLH6yOiJAN6x9XkFI9nR8RvYNXogDWOA8YhEFXiCUmnAAujmpelHD741sLiBs3yBdmbBqNTKNed+N0o41sf72X1eTcH1ty3zSDrbWRr319h1dCu88lsaHWdSg7VO46CeT8wMvxD0vtj9LqUp0k6t6Qs4J/VD+udVQvoDdTPOttGNs0vkuP5L6HPD1FBXfoNcWuSIXCQLHCvI3uN7sXq895K5roNPE+EAZ6HRuZg3oORLJZBDjksnavRWQLibV3bSjMbX19d1qM8kUhriXPIxCb3joibIBs0KPi9rE7aVkraNFZP515ipXJtucskfZhsWChdJmQ3YPvO8VH1npbO/T1/wN+VE8glibqHT9bJ3N1t3e4T4Ii4o3ptSgycsKZH07T4H1Aut/Cf5IigTSg/gf2BclmLr5d+9ls+5+jMAX1tz/ZXMsHnv+V6bAX8ovou7T5Ga32XRo4cWjWiomHv8aXKrMan9tShZO7z7eTz+CH5+j2VnGf6iaqsOtMVlpHngt/uqceEDW8RsWv1t41zua8B8yX9G/l5/zZ5HjBh72CXfykzPL+ckd/aWsmMok8ix6ajAoCrJX2RHJba/Vs90Xv7fLKH8WxJp5MNK2vUchodDhiHy3bRlcQjIq5SjnkuMWiWr4EyJ0Y72d+IiB8oF1vtzK04JGrOrWg5yPod2RrVsQL4v8Iy7oyIYwv36bWFpAdHlUigGp61RWEZS5Vrbn2WDNpuITNATmiQY6KrjL2rv21kwG0jQ2Dj3r3IpAbnKYdOl574dnvvAPt2DNJL2W9CfiNtvK9tfH+ohcQ5ZAPJ+ZI6y+fsBxxRWJXbgCurE7/uk7aS+an7k0Na30gGFA8iT0BKXEMuY9EZOvUgynsKB/pdiYiPSfoxI8MnD4zCYejAjVVP57cBJD0XKF04e+CENT2aHq8/62rgaPrd+hay8eAuSZ3eqKIeIFo452jp+7yNc59Wzj26NOk93owcdtj9uShNlvUNRualAvy4sA7QzrItbfYOPo/y3sGOA8nP6RERcV117lO6Jm73tKymowI2JAPF7vVBJ3xvI4f/f0M5DH8f8nv8fsp1fr8RESVLx0wrz2EcIspx9LeSH4Yg167ZKCLqpmJvqx73A/4fcP+IeKakh5PzT2qfGFfDMI8l55hsL+kRwHOi5sRt5SLzT55o2wRl/IrMjtUdZH0vas4FqPb5ArADue5fkEseXESub1mrxU6ZcfYGBhiqp0z2sJgcsgc5vHVh0y8bSfOATaLmZHy1lP22KmsX4LKIuFWZye3R5I9J7R6gqmdspxiZ57EBOb90h4IyziYTLTTu3at6OF5HZhcEOIfMLlp73nD1eesMq7soRi/jUmf/gZ9HV1n3ZXRCpKLhXWqYVKlr/4GzR6qFxDlVOQ9n5MTvR1GYHU85ZHk1EVFreKpamoukzIC5EyONQzuRjSsrq/o0GoJX87G7h6GvpvA7cBtgCbk8kMiGu/2jytxas4w2EtaIHF3w4Ig4XJlgZMuIqNX4VpXxazLpxZfJHsKb6u7bpjbOOZRJhF7PyHfgj4HPFH4HtnLuUw0r3bkqY6B8A+rKnzBdBugN6+y/CdmIsGLCO6++72U0nDvYVcbPgP8hs5M+uwr4rormc00Hej2qMobhfd2MbIR8Uclv23RzwDhEqpPe7i/ec4Fjoyy1fXd53+n06hTu931yCNGiiNhRme7/0sKT8XPIoWmfiZGkNRN+UWhkkfmzyQQtna77TYDvFwZ7AwdZykQxY6rTI6LMLNpn11rLlOwXEadWwe4fgO2qm4qSTlRl9WtV+wewPCZIMqKWst9WZV1BDv15BJkC/Xhg36iZ8KEqo41Mq42zwHWVcRw5PKYTBOwP3BURtRY0l/RCcl2qH5PH+hOBt0XEV8fbr6eMNp7Hc+izyHxETLjIfFcZAydVUjvZIxsnzukpZ0fyuzhoNkd2TzIj6coB6nAGeaJVPBepq4xxP1d1jhPlUPzD6EqcAxw+UVCu1bMrr7qJmt+BfcrciDx3KT4J7imnacKaY8me6z0j4mHKxDk/iIiSuZRI2pkcqrYPOfz7lIgo6jnR6GRGP4mIbxbuP/A5x6DfgS3WozffwG7kMVoyfaS7vH0avJ4PBo5i9BIjb46IfucAdcprlLVV0nzyHK7Tu/gP4JVRlrG6k9jtbcBtnd7BkmCranR7HZng6kvVecyLIuKD9Z/N6nVqsm9XGUXvq6S3R8SHJR1Nn9wYUZjRfI0WEb4M4QV4dAtlXNpwv4t79yd7hCa9DOAQRpZKuLb6/zpyUv4baz72ftXfrckJ4ztWl/UHfD23nIbj4Ofdfwcs60LgDnIS+CXVa3xx9To/bRqe03vIBX0bPT+yZ/Lg6ph5VMO63I8clrk3cN8G+19eZ9t4+3c/LjnMuPb+XfvNBZ5S/T8b2Lj0eQD36XxeyWFyiwvLuJIcAnV512t7WmEZl1R/r+jadk5hGceTAc2h5LC9twBvKSzjEHKo7/vIYZhXkksFlJTxBXIkwgXAh8n5N/cuLOMz1Wf03QM8lzeWPm6fMn5Y1WHr6vIu4MxByhywPt9poYxG36ld31+Xdm0r/sx27bt5dazcVbjfMWQP6YHV5XTgUwPUo9E5x6DfgS3W4xrgPl3X70NmiS8pQ2Tv5nuq63OAnQv2v5AMmNetLi8jhx83fS0ubbjfFcATu67v2v2dWrOMn5F5H64Ctq62XTXV72tLr0fj95VssINsvFztMuhzWpMunsM4vJqOs+5WOla849aqRTk/abkWWGnihr9UQ4g6ZbyAGnOsop1F5g8lJ51/LbI1qqhnYBzfo+F7MsBQvb9WPSZbKyewjxJlw8mWkQHaL6o6PZzsBX4/OQ5/wp7Xpj0NPVZIOpT8An9SNfSu1iR2tZhptU/v3tGSinr3GHBBc2BWjB6C+lcy6KpNmeVxITl/ZhvgAWSSpdrDtxlgkfkugyRVWlWP6m+j7JGVxolzugw8RzYiXl7te38yQ/GnyB7ckt/dgecikfNbL5b0czJZ1xlRnQEV2Cwi3t91/QOS9ikpQNIDyIaN7kzRpXPKOx7QcL9RVWq437+q76zOb9sWFC4yX30+nkf2MG5DjpSoneK/shuDJzPq1vScY9DvwLbq0Ua+gWOoeo/JhqIVZOKWur3HioiTuq6frJxT3VTTeZkrIuInnSsRcZ4y62mJgecO9mjjnLbp69H4fY2I06p/V0bEqd23Saq9TvFM4IBxeDX6MZN0SBV0EdUwwe5tNb2FHK++jaSfkr0epWv1vYEcDrqdpN+TvYQLCvb/k6SNI2KFpHeRXzQfiHpDiNoMsro1fU/6DtWj3rIHe5HP/SRGMpXenzyJLLVdJ1gEiIhfSnpURFyb03JqOYUcLtRJvLGAHEL4lIJ6vIhcvPZVEfGnag7Qf9fct7VMq+S8ip06AVt14ncmUBIwvpXMfjZqQfOC/U+vhh12ljx4Ebk0RIk3kCebPwOIiF8r5yKW+Hs11O9cYImkG4DSIZ2Nkyp1GTh7ZLSTeGvgZSCU83OfSM6B/gu5kPZPxt2pRxvPJSLepVwM/GnksflJSV8Bjo/68//OlvRi4CvV9RcA361bhyrgfhE59LJ76ZemAWPTxtBuTV/bT5AB3v0kHUG+Fu8qLONy4JtkY9sFDevRRjKjbk0D6Lcx2HdgW/X4PZmJd1S+gWr6AlFvaZ7HRg7DvLTa5yaVZeIdZIkRoJ05suTz/gz5u9Kpx48701LqnEdFztk+uKpTZ/h2o6GklabnT228HoO+rzDSETHRthnLcxiHVJPx89V+q43xLh13Xu2zLiOLNF8TBRPYe8q5J9mLUtS6pWpBY0m7kuuqfQR4Z/QsEDzGvusxEmR15lGsCrKi5twudS3EW10/KBos8KxM0LIjOZxiR1XrH0ZE73IM45WxRUTcWP3fdF7Dl4G/kT9mkD8im5NDaM6LGnNw1GdxdmWm0Plj7dNz33XIHo6SAHNSSLoyuublKhNiXB415+qqhQXNq3I685BELr79jcL9fxYRj+18zqvP7s+jbFH0gReZ7ylvHgVJldog6X8i4s0aYx3WkoYitTNH9i/k+mmfBs6OggXmu8oYOAlQV1k7kifyzyDniD8O+GFEvL3GviuoMnJWm9ZhJPNrxASZOSVdQ65tWfTZ6CljtYbP0sbQlk4+kbQd2YMv4KyI+FXh/t1Le+wdEd8p2b/ar9VkRk3POap912eA78A26qF28g38jMwIfHEVYGxBzk+tdf6k/vkKuqpQK2/BwHNkqwbz8epR9P3R9Jyjp4ym72sbr0fj91XSM8llQF5INo53bEIuZ1U6MmCN5R7GIaJMPfyjiPhHRHyzaq3fvc6HTLlOzUtZvVdtY3KYW0k91iE/IPPIY+Rpkuq20I0SmQnzO5Sn7++cmOxFTn7/ljLbaJ3HvAO4UNITBgmyolqIt/Pj3iRYrAw8VK/zPCpNW2APAA4C3lyVcR7ZQ/YvqJ3afaCehmhpfTq1kGmV/r1736u7c7SwoLlGMvd+vbq+oaR5hcHFOZLeCWwo6anke3zaBPv0FZkC/QIyudLNJfuqK4txp/6qmdlY7SQW6AwF+8i496ohWlgGIiI2l/TvZCKPIyRtSza+7V9QzBLyJGVvupIAldRD0sHVfn8hh4W9LSL+VTWQ/JoMSCd6LqsNh+0Oemq4lhx23jiQIJ9Db3B4QJ9t4xl0yGHH5uQQtROUi6RvHQWJTXpet8OB4oCRnAM+kLYC6CpAvELSeyPivdNUj5Oiyog+gIF6j6OdJUYG7g2LFpbB6rGm9w4O8r7+gcz78Bxy5EzHCsrXTl2jOWAcLod19y5ExN+rVrNv1tj3fHKO4OaMXmR9BeUns6dRrSFG4dyMMTSZb/J75ZCKpwAfqlowi+Z2tRRkXQp8S9IgC/G2MVSv22eb7BQR/ySPjY/2ufmW8fatehiCfB3fwshchlnVvuO27vZoY326Y4Edq16Tt5OJTk4i5/XUEhFv6+ndW1zau8fgC5qfysgad5ANJadSdgL7X2RP+pXk4tnfIwODEucCT6xab88ifyBfRI1h5BrJbLx5tX93ZuP713z8Tg/N0pJKd4sqA2BEnFOdUDykuqn2CAmNXv5hGYPNkd2EHDI4l2x825Ty79P7RMTxVU/aOWTjQO3st5XNySzEy7s3Vo1YtRryJB0eEe/puj6L/LyNe3x0NQCsBC6TdBajl36Z8DPfZmMoLZx8Vr/J88ketRPIQPhkYJfCuqwqsslO0TVSpmkvJe0F0B3Podnasm3U40TlPNmLye+zn0TX2o51RMQS5frPnd7jfer0HqvFZadoZ47s/wM+HNWaidX38n9GROnQ6Y4pnzvYZeDXo+n7Wu17OXC5pC92fkfUwvIeayIHjMOlX0BU6z2qTgaWA49voR4PjILhbDU0mW/yQnLo1EeqwHkrcq5EU42CLAZciLdqYTuy+uL+tKTTGXCoXtOezqqH40hWT74zYW9nvx6GAXyXgl7JMdwZEaFcvPuo6qT6FaWFVD/kXx/gB2CgBc2BdaNryYSIuKPkBLY6cb8icrmapsc45PSElZJeBRxd9fbV/dy+luy1vj/ZINI5Ab6ZTPQyoYg4rTop2D6qIeBNSdqdTPG/rKrLgyS9IuolWOnMje13El86R/a8rssnI+J3Bft2tJEEaOveYFHSSRGxf92TJmCOpEMj4siq8e5UoM7npdMAcAk5L76JNhtDBz75JJPVPIrq+UfEHyQN8v342gH27WjaSzlQAF39vj0wIjrJZZo2zLbRq/akap+dyJwB35W0UUT0XQN0HE16j3cjl/PoN82k9vlCpY05ss+MiHeuqkC+ns8qKWeG9A52G3RUQHejYxsJfNY4DhiHy1JJHyNPsgJ4E6O7wCdUtXB9CLgv+eXdWe9q3DkmPb4v6WnRcFH4rrpsCMyJsjX6NomIm8mA5sfVts3IVulBeh8aBVkRMcjkfaqg5pvAY6rrywYpb0AnkD2BHyeHoB5Igx/4qrVyW0YHnbWTV0TE57uOjWtKH7/SONPqGBr9ALQw9OdG5bDWbwNUAfBfCh7/bkmXS5oTZcNxe0nS48kThFdV2+o2VrWR2XjVEPCm+3f5KLlMzDUAkh5CDjuesOyWhpR1ylrV6KZcULyJgZMAkfMfV6k+K6Wv84FkMqRDye+O70cOxR5XRHy+63HXI4c6B9nrW2ttyZYbQ9s4+byj+l7vBJ33LK2EpNnkezonIl5TNeY9tGEvITQP1AYKoHt/3yg/rlqpR7XPrmSSqScC9yID6KIkU017jyPisOrvQOcLVRmNe8O6rCNp/ajmkla/t+sXlrHG9w52DMuogDVeDMHaHr7khUwq8EFG1sk7ErhnYRm/AR42YD2eRw6v+yfZS7ACuLmwjGeTWdyuq64/Evh2jf2+U/29jtHrMF4HXDsN78lDyCF6V1XXHwG8q7CMT5HZOKf7+OqscXdl17afFJbRGfp4E5k445/kvNtJPzZ6ytiSHBr7xOr6HODlA7w2lzbc7z7kSejPq8/sUXStBVZj/23ItbuuJ1PAnw9sU1iHH1Wf0bPIXpxvN3g9d6v2+6/q+oOBTxSWsR/V+o/kSfjXKVx7iwz2vk0mYtq3cyksY7X1xvptq1HOvsDHqjrt0/TYqsoaeB3VBo95aHVc3Fl9j3e+y/9KjnqoU8ajuy6PBS6rvs8eXfLeknPi/49sBDynOt6fWXPf86q/K7qeR6Pfpaqc7cjMwm+kwW8lOe/7M+Tv02vIRDOla3R+mRxK3/ld2ZDytY7X6fq/9lqBPWUsqD5vvweOIL+X9yssY+Dft5bqcReZKXofYL2G9biMDAYu7dpW+7uDDMpeCryTnGP6Hqq1/wrrsSs5bxoyS/3Whfu/nRzZ8CrgldX/by8sY+D1Rtt4X1t6PQZ6X/uUt0/Tfdfki7OkzjCSfhoRTVtNOmVcS37pXhkND5CqRWhP4MdRZaJSlfl0kLpNtWq+0NuAz3Q9j6sihwDWLeOXZOC5nAzEO72+U/paKJdIeSK5bMSPyC/xD0bEQwvKuJJsYbwwIh6pzBb4voh4UUEZ/Y6NURlLJ9i/9Uyrap7B7YfkfJnOnM4FZKKqoropl7RQFGYTrvbtO28zamYD7lPeLGCjyJ7+kv0aZzbuKuOEPpsjykYpfI5s0e4kwVlADv2t3fov6Rjg3xidEOm3EfGGumX0lHdpFGaqrvZ7MNkI8XiyZf4C4D+iILmHpCMj4tDSx672PXucmyNqZluUdDWwd0T8prq+DfDdiNiuSb0GUR2f20Y1NI081msNTesMwSSDzqeR3+VnRMQPC+uwNCLmdx8Xki6PiB0LyriO/C4/IXIJhEY0eMbXVn7fWqjHvcgeoyeRv1F3AxdExLsLyrgoInZWlSSv6j2+oO5zUU45+QfZeLhqWZ6I6Jc3YKwyVvWGRcRDlOu4nlp6XifpGWQOCJEZQc8o3H+gjLFd5Qz6vg78egz6vnaVM9DoqjWdh6QOkWro1FsZyU4KFKdQX6pcPuGbjE4uUDKG/tdky+cgrQl3RsQ/VH99v1FUrRfU4x/A8ogoXR9uELMj4qKe51H6+M9ssT6DeDOZnORg4P1k0FY67++2iLhNEtWQl6sl1Q44K/2OjdrHWgyYaXWMY+t6FaxR1WXgBc2rx7xFzbIJE5nkZS55EnxmNdxtnZIyJH2RzMJ5F3mys6mkj0VE3fUxYYDMxh0lQd04Xk/2IB1MnqScSw6vKrEb7S6K3nR+6RfJHpznVddfTAaxtYPw7mBRhVkso71sizd0gsXKtWS26CLVZ3RX8vvivCjMXDvo0LSIHIIZubRQUZDY445qmGDn+NqG8gyyjyCPh+OqRp7PAaeUNvQw4Nwu2vt9G3SO2d+rxu4HkUH9EyifpvAVZbK9e0l6Ddk7V/LZfWBEPKPwMXu1Mkc2Ik4nM4HvXRosVoZi7iDtvB6Dvq9IejVwCHlsXUYuS3QB9fMVrPEcMA6XU8k1u45j9KLRJTYhM9I9rWtb6aTrP5KLvH6f0UFnybIaV0l6KTmWflvy5O38gv2PIYc9XUGe9O1ALnZ8H0mviwHnVxb4S/Vj3vlhfwH5+tQWEct7TnR+WhiUtCIiLoZVPUgHN+nNAn5XteR+E/ihpJuo1rcsMOixAYNlWu209m5AnjxeTh5jjyCHNO1aUI+Blhnp0SSbMNUP4EIyQdM2VTmfJlt163p4RNwsaQGZZfW/yMCxJGAcOLOxMuPqq1h93cHaPYwRcbsyc+1ZZC9D7flyXQZeFF3SqyLi+KpOx1TbPhgR7ygpJiJO6rp+sqQ3ltSjR6Mslho86+IvJH2P/JwEOXz5YlVZJes0aEp6T7Vf574nSjo1Ij5Q8FTaOPm8UNJOne/Thg4DTicTMi0hA9YDSgqovr8/C3xW0pPIhoSPS/oq8P6eAL2vQQPoqh7Lldmqn1ht+klkZsna2qiHpN+Sn9ufkN9/B5Z87qve4y8zsqTQQ8nhpCUNA+dL2iEKs7P2GHiObI9GCZFieOYODvR6tPS+QgaLndFVe1Q9p02zx66RHDAOlzsj4thBCmiphb4zZ3C96gIFPUCVNwGLyIDzi8AZQMkP+zLgVRHxCwBJDyeHhr6fPGGYqoDxDcBiYDtJvydflwmXGujW50TnhAYnOgOTNJ/80t64uv4P4JVRLUdQR0R0ejreqxyutil54lNi0GMDBsi02uk1kXQKsLDz4y5pe7KHv8RrybmUJ5E/qrOAW5ULv0eUJZsq6i3p8gZgZzLYJSJ+Lem+hWXcQ9I9yKHon4xcp6/0M99GZuOTgKuBp5MnOgsYWXKjFmU20U8DvyXfk60lvTYivl9j39PI77pNgV9J6mQE3JnyRo0XSLotIpZUZR9DeeKJsyW9AzilqteLyOyPmwFEwTIflabJGgbNurgB8GdGlr25kWzgeDb1GzRfAjwqIm6DDL7JwK/ku6ONk/E9gNdKajwEMyJ+KOnnZC+FgEMionayK1g1NH8vMiHRPLIhbAkZuH2PkWVlxjNwAC3pEHIuZ+c9PFnS4ihLgDVQParX4lOFjdqjDNJ7rJyqEeQ59YFVT+ftNBueO3BvWG/1Bth3je8dbHFUQBujq9ZoDhiHy2mSDiKHAXT37JWs/XUCfYK7khZ64JcRcWpPufsV1GEdMunGU8jAoIntOsEiQET8UtKjIuJaNRzmWkK57tlRwFYR8ZTqxGJWw165Nk502vA54KCI+ElVj13JALJ0HH9vb2lp781DI2IRzY8Nop1Mq9t1twRHxFWSHllYj4GXG1GDbMI9bo9cjqNT3rqUN/B8hmykuRw4VznEtWhoW+SyHN8ihzDNqTZfXViPf4uI/SQ9t3qPOw0KJT4K7BE98+WACQNGct5lW/YFvi3pbnLY3t8i4qDCMjpzg3uXXngl5ct8QPMslgNlXWypIXMZGXjeVl1fn2wUKNHGyfjAQzAlPY9MFvbd6vq9VD6P+tdk4rH/jojuxoyvVj2OdbQRQL+KXD7h1qqMD5FD9UoCxoHqETlN4dlkkqpBNO09Lp5K0E9bvWGStoiRdagbLdsyw3oH2xgV0MboqjWaA8bh0plP1t0qX3pS0D30YAOyhaf0oD6UHB470ba+YsA5ZpVrJB1LtqxDnjj9r3KYW61FuAd0IJls4mgyG+CtE9x/PMsY/ESnDSs6wSJARJwnqSgAbqm39GNV79Op5JybX0y0Q596PJs8uV+P7EF6JHB4RDynoJhfSTqO/BEMcomO0vTl3XUqmh9W7dPG8zhH0juBDSU9FTgIOK2kHhHxCXLOSsdySUXz1yS9iRxq92dGUqcHZQ0Snc/236se3z+RvSclGs+Xiz6JglS4KHqn96/yavIE46fA4ZI2K2kAjBaW+VDOjT8WuF9EbC/pEcBzCj+zJwNndTVIvpJc67JJfX4eEbWXsJF0dPWYt5NDW39YXX8qmf2xbjltnXx+ICL27yn7JDKzb12HRcQ3OleqHvnDyGOlrkdExC39boh6Q/OhnQBajJ5CcxflvVpt1ON85VD0LzN6mkLJ9I9GvcfRtc5pnwbV2o/fYm/Y+cqkSF+mbDpSt5nUO9jGqIA2Rlet0ZwldYZTzlc7M2okzpH0TDL9+QvJL5qOTcg5TjsXPO5XyOE2TeaYdVqwDyK/eEWeGBxDBl2zx/qhbIukL5GZCbdgdHBX+4um60RnDjn2fdSJTkS8uO16T1Cfj5NJb77EyPC2m8i1lWr9sEr6FaN7Szck028/rLAuW5LH2YvI4+vLJSewGjDTanX/DcgEKZ3W+HPJZC23jb3XuOUVnQhX+wycTbj6jL+KrqyNwHFR8OUu6X7A/wPuHxHPVA4Bf3xUc/BqlvEbsqfhr3X36VPGq8nj8RFkq/ZGwLsj4jMFZRwLzGX0fLlryKCtNAFYkwDnuupx1fW3IyKidgOgMoHRW8ge6IVqsF6fWsj0XO3zTEbmMxVnXewq59IoyLQoadzEXNG11mONsi6pTj4b6z0elCNqroyIhxeUsdpnvMH310AZdKsAuo2Mr28hG7s7AfA+wOejxjqdLdejX0bfqHPu01XG3H7buwPCCfbvbVDdh8zoWfLb9ingxAF7w5C0M5kUaR/gl2Tj7Mnj7jR6/0Ezxrb1vg78egz6vvYpb2FELG5anzWVA8YhIGnPiPiRqgQAvUpPcHrKfiiZvvzfatx3R3JNvMPJ9YM6VgBnR8RNBY/b90e+8Md90CGHA6mCmjPIRBGj1PmiafNEpw1j/KB21PphVSZCekmMJL+4F3ByRDQakiNpB3LNqBdFxHoT3b9rv59FxGM1Oi198bItbR5jpSfC1T6Nn4eksyLiyZI+FBH/1bTeVVnfJwO0RRGxo3JY66WFJ7BnA0+NAbIYS1onIpom/OqU0W9pjo6IwqG/Td7XtigzXl9CrjG6fXW8XhARjywo4+KI2KnnGLuspIw2SfpA1E+WM1YZjy7sOers1/jkU9Kh5Pp6G5KJ5SBPgu8AFkfB0iXKpV/+TmbADXJe970j4oCCMi6s9u8s/fJicj3IkmVsBg6gq3I6vWoCzo3y7LWt1GNQkk6KPr3HvdvG2X/gBlW1vAyXpM3JoboLIqJ29mxJbyWXkHgquUzSK4EvRsHc1JYaaAZ+PQZ9X/uUV9w4PBN4SOpw2I1cF+/ZfW4rynCqHGLY3br9JzLj4YQiM5tdLumLEfGvqrx7Aw8qCRarsgYKhiQ9h8zQOMhQvYFExJ+AHZsGFf1eg6YnOm2IAVLkq6VhYVVZDyN7Fl9ALiJ+CvCfhVUaONPqJBxjTX4YB3keWynXYHyOMoHP6HVKyo6zzSPiK9VJMRFxp6TSwO1aMrvyd2meXfk65VpmXybneBW3aMaA8+W0+jqfjeYAVWU9gdWXSfpCQRHbRMSLJL2k2vefVct9iYEzPUt6HDk8/2Hk52Ud4NYoS+oEwKDBYuU4Mot2qUGGpv0mIjaW9JWIeGGDx+72JuDd5HEuMolb6RqfbWTQHXhuV9eJ98/7bJvKemxKDonvjBg5h/w+L5kW8+89Za5D2ff6MgafftLGHNlNyCGlLyYzZ3+DTNxVd/9hmjvYxrItg76vvSY/kcYQcsA4BCLisOrvwIkBooUkHOSE3ueQx8dlwI2SzomIt9QtoDr5PRJ4OKPT49cdjnUY+QX342q/yyTNq/v4bVE7c8y6NT3RGdiAP6hLq7+XMDL0CKr3p9AJZKv40yKi6aTxNjKtDnyMqWcZiM65fEEv1iDP4z3AO8hhP71BWVC2PtStku7DSFDxOHLd0xLXV5fu7MqlHko2nL0B+Jwya+kpEVHUKNHRpCU4euZgR8RFE+/V97FPIk/WLmNkjlcAJQFjG+v19cv0/LLCMj5JnnyeSibCeDkw4aiVjjYDzk6RDfcb5OSzM4+/9vMeS+Sc+HfAqpPXe0b5PPk2MugOPLeLdk7G26jH54CryKkOkHNKTyCTT42ru/dYUifZ16re44I69G1QlfQJqD0lp405speT82EPj4gLCvYDhmvuIAO8Hi2+r2h0hthn99k24zlgHFKSvjPAML/nMBIU/DgK5rtUNo1ck+3VwAkRcZikojXIyC/qw4CPk18aB1L2I99vcffp8F7aDVyn8wk1/kHt7i2VtB4jKduv6fRG1xURjyu5/xgGzrRKO8dY42UgNGA24Yj4KpkR8d0R8f7S/Xu8Bfg2sI2kn5Jzd19QWJ/3ASgTI0Q0mGccEf8k5x5+pRrdcBTZsFF7KFWPpm/uIOt8dswn534PMu+jjfX6rgUGzfRMRPxGI0OGT5BU0qM/UMDZx/sa7jfIyfhflcOut5b07d4bSxoRldl/X0c2JFwCbCrpYxFRsu5pGxl0GwfQfU7GO5+14pPxQerRZZuIeH7X9fdJuqzmvm31Hn+DwRtU2wjAH1wFfYOs4TgTegfbHBXwNarG/oj4XbXtqwV1WeM5YBxeTRfx/iCZYGVJtekQSbtEwfwKYF1lFssX0vyEfMOIOEuSIuf7vVfST8gToDraWNy9DW0Hrk1PdNowyA8qAJJ2J7MjLiNPEB4k6RURcW5BGbuQgfhc8juo0+pYkg144EyrtHOMNV4Gorcnq/Bxux0h6WXkScLhyiUttqzbM1b9AO9WXR5Kvh/FDQHKrKYnkevrIekv5Ny7ovdGOcz2ReTJxsWMNHA00WitTgZY57PLVcCWFA7/7BYDrNenTEbSb3un7JKhwiurhqLLJH2YfE6lSx8MEnB2hsktoOFxXhnk5HMv8oTxJHLpFoD70yy1/sOrRtkF5JqJ/0UGjrUDxmghgy4DBNARcSRwpKQjC88vWq1Hl39K2rUzGqH6nflnzX1b6T3uaVgtmn7SZm8Y8DhJx5NJw+Yo81O8NsqW9ZkJvYMDv6+StiO/NzbV6Dwjm9A1em5t4IBxeDVdxPtZwCMj4m4ASZ+vyir5Qj+cPOk9LyIuVmZj+3VhPW5TZm/8tXJexe+BksXE2xhy2IbGQYUyEUCv6zvbS35MWjLID2rHR8mhpNdUZTyEHF5a0sp2PPAf5AlSowQnEbGHRjKtLlbO2SjKtMroY+xL5DFW2lM36DIQbfRkfYrMkrgn+dldQbaG7lRn5ypwfW5kVsMmgXfHYuAtEXE2rGpc+CzwhLoFKDOMXkb2Mr6twTC9TjlzgW0j4l3KIZ3rlvSsRTvrfG4O/FLSRYye01nSE7ULcFlEfLdqFHinpKOiXna/zvSEh5LHQqdX7NlkRuAS+wOzgDeSn90HAc8fd4/RBg44ySzZjY7zNk4+I9ebvVDSE6Ja407Nk1/cQ9I9yAyWn4yIf6laq66uav/uLM8/JjPhljT0DNybFRGHVqMBtmX09JOSY6yNXrXXAV9QTr2AzAA+buK5Lq31HncpnX7SZm/Y/5CjXr4NmZ9C9dfm7JgJvYNtvK8PJdfZvBej84ysAF7TsF5rpojwZcgu5A/9Rg33vQLYrOv6ZsAV0/AcdiJbtx5IDnv8OvC4mvuuQy4FMgzvxWzgCLKnY2n1/wY19z27ulxABhZLySDpX2QwPtXPZUdybsOy6nIpuZZX0fFVZ9sEZfys5ee1A9nqf8c0vKavBu5N9s511vt7bcH+r+h3KazDz6u/l3Ztu7ywjCPIYYNPJE9yHk2uP1pSxmqP2aAem7Twnrym+rz+trq+LXBWYRnPJpfiuK66/khy+HBJGbv1uxSWcQUZ2HQ+u4cA5xSW8QNg467rGwOnN3hd1yOXO9kBWK9w37lkMLEJOcrkY2Tv/JQc58B+1d+vDHp89ZR7acP9DiYbUb9Xvb9zgZ8UlnEcOdpjz+pyArmcTp19DyVPeO8kk5rcXF3/K3BkYT1eDVxJBmhnk42QP5qqepC97gC7VH83Kf0eqY7tx5EN453P6kuafGabHhtdx/fPWzguf9ZbhwbfxSfV2TaJ7+vAr0eb7yu5zNRA78uafnEP4xBRLjHwBUYP6XpFRFxVUMyRwKVVq4rI1sei4SIaWZx5lChIRx/VuPeql/HgKGvdb2uo3sAiYiXZC9VkjtkeAMoMlgsj4srq+vbAW9us50Sqlr2XRS6ZsElVv5sn2K2fS6qhLp3sfAvIILjE2ZL+m2xE6O55KRm+0zjTqjKRypit+VHQmhwRx1X/nkO9OUO9+7extMq/qve3kxhlC7InpkSnF/Dw7upRljjnWknvZuTYeBmZYKXE+pLeyeqZRUuWwngDOe/4Z9W+v5ZUMroB+s9dLhoCGBHnFD5mP3dGREh6LvCJiDheEyzX08ccsiet4w7KesGRtBfwaTLjo8gW+9dGxPfr7B8jPaK3KROAPCgiflNSBwY7zltLWNOjdHF5ACLiE8AnujYtl1SaxXqniNix6/qPJF1ec982e7MOIRuIL4wc+bEd9adetFGPA8m5zkeTjVzFv2vRbu9xR+n0kzZ7Of9PmaE5qp79g6k5t77LGt872PL7eqmkN1AluOt6jKJlmtZkDhiHy2dYfUjXYgqGdEXElyT9mPwCF/BfkctDlOhOkrMBmZ65aJ6GpPlki+fG1fV/AK+MiLrBRRtD9RprM6gAtusEi9W+VymzrU6ZKgh/TPV/k0Cx43XkCfnB5PF1LjlUrERnnbD53VWkLDg5geaZVj9SeP8xKTOLvpdMRhLAT4D3R83F6zWyyPsoUTaf8xNkooX7SjqCDKKLli6IAZZc6fJK8iSpswzQueTJXIlvka/hmTQcrgzcHhF3qJqrp1xTsmi4H/3nLtcqQ9J5EbGrRpY4WnUTOQeoJDPoimo45cuAJ1Unbfco2B8ygL9I0jeq+jyPskytkEPR9+gEecpsrd8FagWM1W/SQJm3GTnO79fgOJ+MIYdEROl3HwCS7gf8P+D+EfFMSQ8HHk8O16/rLknbRMRvqzIfTP3PTJsB9G0RcZskJK0fEVcr13+eqnr8StIyYAuNTs5XPOeuE1R07V9EGmiebZtzZF9HBtEPAH5HwbItbQzfpp33tbXXY9D3tdI4wd1MoYjS31GbLJIu72kx7LttgjKeRw4H+Ud1/V7A7hHxzQHqNYscIlr7hL764n5DRPykur4rcEzdL++xWtFb6pGp8/i7Vf/uSyauOLm6/hJgWUS8s6CsL5FB78nkCdvLyCHHL2mvxrXq8VFyeN6pjA7Ca63zWR0HV0TE9pNTwzVP1aBxLiPHxwLy8/aUsfcatf99uq5uAOxHDil/T839Z5FDbv4GPJn8MTwrIupmah33hD3KEqMMTC0sKK+cI/d3MhPnm4CDgF9GZtWtW8bxwFnk0gfPJxtI7hERrxukbqWU83RfClwcET+pTkB3j7K1HDvzqZ9YXW2ysPq5EfGkrusih8bWmhcl6dKIeJQy8/aDosq8XXIyX5WzHc2O8/UYOfl8dbV51clnS73BtUn6Ptnotaga9bEuOXxwh4IynlyVcS0jw1oP7DQ4T7DvD8ng/ZFkA80oJQF01RBxIPBmstHvJvKz8qypqkf1OTmDbJToLaPOfN9+ZR5U2iAg6ViqebYR8TDl3M4fRESt+eRVGVu02MtZTNJ+EXHqIL2DLR9frb4eTd7Xar/Od9gVEfEI5RziM0rOi9d0DhiHSPXF+3NGD+maHxH7FJSx2glX50AfoF4PBb4bESXrbv00InaZaFvNsqZtsfveE6Wxtk1QxgaMTk5wLnBsRNw29l7tUw417hUlQyqUqf0PjYjrB6jHpgy4wLIGyLQq6UrG7z2ufRIr6ZLItaq6ty2NiPlj7VOjzPMiYteC+18QEY9v+FiHVf/2TYwSEa/uu2P/sn5IzhX7e3X93mQG26cXlPEB4PyI+F7dffqUMYtcG/Np5HFxBjm3q/aPnaTZ5DD07jLeX/czOxmNK5L2joIlkiRtEpmJc7N+t0eNdfo0khXwqeRn7SvkZ2c/MpNu3WHgV5Kv5efJIOnihgHjrmQyoxOUQ1I3ioJ10Kb7ZLyrHhdHxE7dv81NGkskrc9IZuOrI6LWGp2TFUBXDa2bknNk76hx/8mqx7ScM3SOqZ73tajRv6e8RuduymSHh/R8F3+0zm9913No/PmYxPd1oHPZQUi6KCJ2lnQu2Qj5J+CiOuccM4WHpA6XfkO6DigsY1afbUXvs0aGUqn6+ycy7XeJiyR9hhw2GOR8sx+rWYbQaVvsnhzm8uDItcxQzmPaoqSAyOE6nwa+F80zLg4sIkqHB/azFbkw8UWM7qUsGdLVeD3ILoNkWm20vukYzpb0YvJEGnKYXO3lGDQ6k+4scpjuxmPcfSw/kPR84OslQRGMWjvxB+T8nxXV9feSPdElNu+coFRl36TyuYOHkJlAbyeTQxUP44zMEP1ZGs4vq8poPHe5UwdJl0uaM0jjSo/DGT1dYCJfJI/1S+gzNJZ6c267swL+mUwWAXAjmeyproEzb1eNG/PJAOkEcmjuyeRw8FqinaFpbbi1Gl3QmY/5OKBovr5yPtWSiLiiun5vSa+q03sSLc/ZUw6Vvh8jc5a3BCY87tuuR5fpOmdoYz55t6bfYY/o811cN9AatrmD3Rp/p7dgcRV4v4tsWN0IePc01mfKuYdxiHSGAky0bYIyPkcOx/oU+aX1JuDeEXFAi1WtU4/xhsVESTf+NLcqPYMct39ttWkemcDmBwVlPIdcX2u9iNhaOX/x8MIga2DVSdpR5BDGILO3vrmwhX63fttLWgzH6AUval2X9LOIeOzE95xcVePKPcmgVWTQ1wmkJwx0ej4nd5LZaz9S0rDQVYc7ybm/xUGWpKuBHTs9FFXPxeURsV1BGZcAz+sESMqlLb4x1b04kvYml0fp7X2e8PVQi3OXJf2I7LUdpHGlu7xp+x4cBso1Yx9FZk3s9N4U91J2lddoaFobqoaio4HtycazLYAXdIK/mmW0OppogN6sN5EjRv7MSHAUA7wvAx/n0/VZUa6r+SIyOcyJVPNsS87hWqrH5eTQ9Zuq65uRQ8gnHPI8E3sHrR3uYRwunYnCE20bz5vIVo8vV9d/QM3EAJK2i5yw3u8EL4C/Rc35ANFOEo2OKV/svitQv4ac99c5ca497KfLYayecXFeS1Ut8UWyIeF51fUXk9lFawdeEXGOcr7IzuQxcXGUJ1VqYz3INjKtPo48aXsYmX57HeDWwt6s0t7A3v0H/pwMWodKG4lRFgHnSeqcUDwJWFhnxwm+e0pHJPwP2Vt9ZWmPKyMJkfrOXS4sq+3vrdc22UnSF8h5RD+JiKsHrUSTngLlvNIPkJ/z08llQt4cESePu+Nod0REqFqvUFLpOo6jTFewWD32z6vGt85w0muibP1EgFmS1DnGq56t9QaoVtPem0OAh0bNRF+TWI9uU37OABARS6qGs848232i5jzbln0UOF/SV6vr+5FLJ01ohvYOtkrSdyKizZFKawT3MA4BSc8EnkUO0fty102bAA+PiJ0blrtVRPyx4P6fjYjXjNM7eB+y12H/GmXdi0w6MY/R6fFrZzlVzp/ZlTyBPS8ivlF330G1MY6/q6yfRcRje+Y1NG4ZH7QePdsujIjHFZTxauA9wI/IH8TdyN7SzxWU8UhyLtOm1aabgAMiom5K+LF6sEt7rpeSQfOp5FC3l5Nrw004DLGtAKcalnYYXcc5+Xo2OvmS9N6IeG/DfQdKjFKVsTnZgy3ggoj4S839FkfEwpbe17OBJ0cOTW1ELcxdboNy/vNBjD4+iuY/S9qz2v+J5DDUy8j396iGdSruKej0himTsu1DDic/O8oSur2VbLx7Krl81CuBL0bE0SV1mU4amRPaV9RMQFaV9d/k7+unyWPjdcD/Rc15pW2pPm9PjYg7p/Jx+9RjkAylbdZjoHm2Ldbj4WQSok6CqF8OUJZ7B7usra+HA8YhIGlHMpvU4eTJeMcK8kf1pobltj6pX9IPIuJpNe53PnAhuaDvqhO3qJnlVNIxZErmL1WbXkQuxF0rNfSg1G6Wr2HJuPhBcrjyKYzMK12f7HWsmwTjGuAJnYCmCnjOj4i6adS7yxpkPciBqUpO0x28Szo/IiZcxqatAEcDZlntU17RZ15jJETpqHNMjFFu48B1UJJ2IoeknsPo3ufaGV8l/QrYK0bPXf5eRDysoIx9gQ8B9yVP2poMFf4K+TvQ3dN574jYr24ZVTnrkMNj9yADi39GwXDjnrI+EBFFy7ZI+kVE/LukzwJfi4jTVZAMpAoGHkiO9FiViCgiflha/+mk/onHOiLKEpDNInvwn0K+Hj8gkzs1XY6mker37aHk3O1Gn7eW6jFwhtIW6rBqnm1EPETS/YFTo0GyvwHrsQ3wu4i4Xbk82yOAL0TXvMbC8qZt+PYwkvS5ks/qTOGAcYhIWrfNVrrSVpCWWz8HClYl/QLYvmu4zSxyiNm/j79nO9ocx6/RGRchkz98oKSXoA3KNf/GElEvw+hZwDOrYSud1+l7JQGOpP8HfDhGZ3D7z5KTULWTafVc8mTrODKx0x/Jns4JT2I1knp8VUKkJtRyltUGn/nOOpAiF3i/qfr/XsD1EbF1w3q00TO/OCJqDWnt2e8HwC2s3lhVe5iapKeTQ6gGmbv8G+DZMcCQtH5BVUmgVd3/LHKO6wVk49d5EXFD0zo1UTVW7UMOSd2ZPL6+0zviYYIyVvusWNL0ZhI/rN/2ks9bS/VoNUNpwzpcRovzbAesx3zye+t04DQyiJ1wqRPrT9IhvaMy+m2byTyHcbj8WtX8jG51TuTHUDpmvJMR777AE8hhh5Ct0j9mJHtrHSdJeg2Z1a+71bFuj8U15AlsZ87kg4DaCQEGFe2O439w5DDHRhkX29L05L/H74GfSfoWGWg8l5z79pbqMeq0Kj8zutaxjMzg9izKFptvI9Pq/mSSmjeSQ+QeRPYA19GZW/xVBsvGN1CW1T6KTqg7x4Qyi++3o1rOQjlMvlEvZ6WNDJRNlybZrM4oiLFUjVObMvjc5T8PEixWLpX0uIi4sKrbY4GfFpZxBXlcbE9m4vy7cimW2vOG1XC+r0bmgn+G7G29OSLukrSS/O4ocaGknSLi4sL9hpKkvYB/J9dfBSAiDm9Y3LRlEp/qwHAcbWcobaLVebYDuDsi7qw6AY6KiKMlFU8xsFFeQSYN7HZAn20zlnsYh4gGXMS7q5xOiuvuuYO1U7tL+g7wmqjmP0raCvhURNQ+GVem/D6CHALZOchq9WJV+5/DSIZBqv8vAFZWBU1phtGqTkW9N137nUeeZJ1Izrn5e8tVKzZA703f1uSOOicPkq4AdoqRjJwbAktLeo/VTqbVe5JD8+6urq8DrB+5pMJE+7a14PRAWVarMjYg1x3sPfksGd7Wdk/nrBhgDmFVxukR8YwG+30Q+FFJb2CfMhrPV+waqbEbmTjnm4xuNCsZqfErcrhf5/t7DvAr8kQ4SnouJG1ELrD+VnJu1/oF+zaa76t254L/EngI2Yh4KyNDfKe096YNVQPNbLIx9jiyoeiiiHhVw/Ia/TYNQtL/RMSbNUZm4an+jdYQZCjVkMyzlfQzMvnXInKUw3WSrooW14VdW0h6CfBSch5492/9xsBdJaOr1nTuYRwisXqii/+pgo3aAaNGp7junIQGOYa9rnkxOlnOn8kf6hJvIU8oaiW96KMoSJ4ijbJ8RcSukh5CnqwtVa5heEJM7/ybRoFAd0Aoacsoz5AKOR/rrGo+T5A/qrXmtnZpI9PqWWQv2i3V9Q3JeUATzmEE9mJkyPJHq22rhizXFe1lOL0aeDo5D3oBGVSU+Iukd5HvTQAvA4oS71TH+LHA/SJie0mPAJ4TER8orEtnfmvRPL0ubwDergHWcgR+WJ38fZnRS2LUGSHRvXbhSkaGokO+tiUjNYoD5l6S3kgmvHkMGWx9jj6NHBOJiN9IWidyjtwJynnqExl4Tbcuzyy477B7QkQ8ohqu+D5JH6XsuOg1Hb18J1V/PzLuvaZITHOGUkkivy+2A24mG3reM02/8weSc5WPqILFrRmZB21lzienq2zOyG895NzyKRv1NgzcwzhE1H8R79cXzlf5DfDYPsFnST0+SbaSfYk8wXkx8JuIeFNBGd8GXlynt2acMu5H9ixCtr5O6bybtlU9WPsAnyB/UAS8s6THocW6NOq96SljkIWen0FXsoaIOKNw/0cyeKbVNnopt2hhyHKnrEaJYjq9C525MpLuQSYEKcksuhmj54SeC7yvYAh5Z1TA24DPdM3fKWrVljSfHFrcCaT/AbwyIi6pW0Yb1H++b+0REm2TdF9G9x6XjBh5G/l+XhIN58ir4XxftTsX/KToydDdb9uaQCOZsy8kh9H/FbgqIrYtKGMosoIOE01zhtJ+IzWmm6ZxfqvNLO5hHC7drRedRbxf2P+uY/o/8iSrsYh4YzWsqpNif3GUL2lxF3BZ1brcPRyr1rIakl5ILnb/YzKoOFrS2yLiq+PuOISqnpYDyV6pH5JDRH6uzKB2AYO1LDcyaLBYaTxPLSJOB06XtHdpsFjtfxmwowbLtHpr94+ppMdQ2EvZCRYrg87bew7w3gb7ddZv+7uk7ckT+nklBVSB4SENHrvb7Ii4KM9jVykNUD4HHBQRP4FVJ4AnUDZCopNIaVtGB1nn1t0/WpjvqxbWHpT0HPJ34f7ADcBcsve49vDtiPjvrvIWRsTiuvt2aTTfN9qdCz7qOVcNcEN1cl7gO8qlp/4b+DnZMFs6guUYqqyg5MiCFcDXGGlknRKS9iazEs8lzymb9Oi3UY9VGUrJ74x7kL1qU5mhdBjn2U7b/NaZQNJ51SixFYweej0tx/l0csA4RGKARbxVJR0hs/r9WNJAKa6rXq9BAplvVpemFpHz3G6AVRPYzySTjKxpPkmeDLwzuhJNRMQfqmGAk2qsOSZd9Wg616SNhXgPJxMjFVELmVaBNwOnSuoMI92KnAPT1KCvR9OAc3H1/N8NfBvYqPq//gPn5+vtrD4PsnYvJTmsdRtGkk68gOyJKrGiEyxWj39e9UNdm3Kt0EPIZRguI9eFvIA8sa5bxj2A1zPS4/pjsue0ZHH1p0XE25VrD/6OHGJ7NmVDw95P1v/Mqhd5D3JpjaZeBxQHjBHRST52m6RPAA+KiN8U7N+4YUXSocA7gQ0ldRqGBNxBg+cyDCLi/dW/X1PmDNggCjI8Vx5bzQ+9tCrzpqpHd6r9D9lLemVM75C151FlKIVVv69tDPkvsQfwWknDNM+2jQRka62I2LX6O9XH0tBxwDhk1DxzWudgvr66rFddmtShUUa8bhHx+erHqzP38ZrCk61ZPUNQ/0q2cK9xYpzkGRFx0li3tagzx2RfMglH95puy0oL00hSpe9Uw6CKhsj1Ftdwv4EzrUbExZK2I1ukRWbCLDlGe8sbdJ2qRr0lEXFc9e855MLsTSwh59/sTQYVrwBuHHeP1b2BPIHfTtLvgevIuZAlLpL0GUaGw7+IbAB7NEDNoVWHkL0sF0bEHtV7XDrH61iyh6Lznu5fbXv1mHus7h7V32cBX4qIv/X0vtbxr4j4q6RZykRCZ0v6UGkhXRp93iT9mOwBX5cMwm+UdE5EvGW8/cZQ2rDym4jYWNJXIqJ0xM1Q6tcgIam0QWIYsoJCjmq6apqDRRiODKXDOM92WLLYrvE0YELJNZ0DxiGiMTKn1dk32k1t/Un6ZMQrKUC5WOznyYBEwIMkvaJgWNjpks4gTxwhTxy/V1KHYSFpWzJj2sMZ3RAwJfOhOvOEJL2/J3g9rZqbVJsGSKok6ayIeLKkD0XEf1WbX1vy+F3WkbR+jM60WjvrY0d1gnaVGmaNHZR6Mpx2Aoooy3B6H3Io6y7ke/ET4P1RNo/5PhFxvHJdqXOAc6o5ibVFrkf5lOpEbVZEFPUMVh5Z/e3NxvsE8rnV6SW8LSJuk0R1jFwt6aGF9dipZ37ejyTVnh9bOU3S1eSQ1IOqE/rStVf/rsxuei6wRNINFA7zlbR11zyuZ/fZVsemEXFz1Xt7QkQcpsx2XKxBw0pnCZui36Ah10aDxCeAbwD3k3QEVVbQNitZ09uB71XfF41HNbXgK1Vj072US3q9knZGwZT4QL95tuT7O2U8v7V9Pec+nYaZ0oSSazQHjMNl4MxpynT/+/UM1TslIp5eUk40y4jX7aPkkKxrqno8hAz+JuxFqb7sPkH2EuxKBiVN5lEOixPIL5qPk40BBzI9w0S2UNdC88rMaVsUlnEIuQBwk6RKW0naDXiOpFPI1+DOwt6jjjYyrXZruubfoNrIcHoKGVB05pQtIHsLS9J9d3o2/liNcvgDOaSztq5h8Z3rkPOpL6nmnE5okGH5XX5XzQ/7Jpnt9CYKs9cCd0naJiJ+CyDpwWQDyYTU7tqDzyUDzv8g39dNyeOkxNeo5jBFxO+qbV+lrEd7XeXySi9k6teTbTPT6rAYuEEipjkraJcjyEzTG9BwVNOgqnOGYchQOizzbIdifusMM8i5z4zggHG4dFqfVyoTovwVKE2+sEV0rfNXDdW7b2EZK6vhpJcpEzf8kVwrrsQ9OsFiVY//rYbhTKgaVvLNyGxjU54QZhJsGBFnSVI1F+i9kn7C6r0ok+3N5NCna6vr84DSXrVBkiq9B3gHGYj0tj7X7T3KO0d8uOrh6GRafX80SJ7TZboy8P5bROwn6bnVMO4vAqXPY7OuOVEAH5C0T2EZH5C0KfCf5HD0TcggpcT86nJadX0v4GLgdZJOjYgPT1RAVYfubK3nAIeXzO+KiOdV/763CjQ2JZPOlHgbcHb1WRGZ0OPAmvt2esS+Fl3JXSLiVrqW6JhIdbL5rch1vu6msEGkGor778CmGlkbEvK93aD/XmM6nDwuz6uGcj8Y+HVhGU21soTNkGncINFjc2BlVFlBG/Qct2GziHjaxHebPD3nDFO+jIWGb57tsMxvnUkGTii5pnPAOFxO0+CZ0+6SNKczrlrSXMZJeDKGRhnxeiyVdDwjazUtAEpS4w9jtrGmbpM0C/i1ck203wOlQfxAqsfflMwcuV21+erOkM4a+w+cVCkyw+1XJb27J8BpJAbMtNrjWZI2iWbZVgcxcIZTMrB5MfCV6voLgO+WFBARncRD/yB7wZu4D/DoiLgFVmUt/CoZ/F0CTBgwkllSr2IkO/T+ZA/9vmPu0aU6zq+IaimPKFi2oVvVwLMto+e31vqs0FKPWKdXUtKmJQFzl4eSc1Lvxei1IVcArykpqOoxPbXr+rWU/yY0Eu1mWh0WgzRIAEOTFRTgTElPi4gfTPHj9prOc4Zhm2c7LPNbZ5JWEkquybwO4xDoDGHqbh2UtD4NMqcp17dbTLbMQ56sLWx6Qq2Ga/hU9X8DI0NKzwWOKQhQfkn+EC5jeLKNNSJpJ3KY4b3IrIebkhk+L5ziepwb4yTgmWDfcXtD68yhlf5/e/cdZltZ3n38+zt0EYKFRGOCFEUUpASxUJRiQzGvGgwisdARoyiiQkRFNOqroleCBSzB3ghiLDRFqjQ50izwRhCNJsbXKIKC1F/+eNY+s2dmzzm7rNlr7T2/z3Wda9hrZq2555zFnvU8z/3ct7ao9pP1fNAb5j6rrjvUw2O1mncYZWZ/OeXf5X3uakOw2Ko9YadR9kGcQlXh1PbJA1zjNkoGQGdP6TJmVrLsAct+j/D3+SNgm+oBv/MecLXtR6vqFdnHNerojflZ4BiPUIxA0v2AI4GH2z64M3jsGliv7Nw6ew9+iVIl9Zt0rU66z/ZE1TWeZPvSfr9+gWuM3CKkTv3eT21W/f8xzIRE5/yrqaqCeqbv6bXj/h3Z9f5zFzMTYAO/79QQxw8pRfbGXqG0857ZlokMSftR6j5sD3yCan9rNfETQ1joGaifZ59pkQFjC9T9ZiPpwZSHDAGX2v71qLENcd66lOIT91avVwPWsn17n+c/vNdxz5R3jwFJehPlge+LzH747Ls5+4jf/yO2D6lWX+ayB2vh0H3doR4eOwOR6pfr9sAbKPvtJm5Sok4j/H2+iVLa/t+qQ8+htPk4gbIHeb8+rnEp8DrbF1evdwLea/tJA8TxbcpenSuYfZ/3vddN0hcpkwgvsb2VSlGlSwccuG446oqYpJf2Om57lempkl5fpW6fSI8skwEHnZ3/V54HPJeSeXKeZ+/DGxtJh3v0qsSNkfQK4LOeXWtg30F+JklX2H581/PDupR7dEm+fzX5zKBSO2J1StGui+Z+fpD3nhpj2oKZ/a3nupn9rTFFkpLaDnVv6l8L+A3l3/cxkgZqWj3HsMVZzqXsL/t99Xod4BxKtcNVsv3TaiVqZ8rDzneGXYFqihav/+GwOpU3X9EdBgO0YtBoRZU6e0sOrFLaBqZ6K62uobKv9rnAB2zfraok+7hohAqni7Viy4DprFUsosxkn8FMVsFhtq+svmSVg8XKy4FPquxlFOV9rOegqUcMnaq5dcz4bmZ7H0n7Ati+o/oZ++YReg92+Q9Ke5C+Jtrm6DwgXrnSr+pPHS1CajPJg8XKwbY/2HnhssfsYGaqpvajDVVBAZD013S1COlnJX4RNFmhtI37bNuwv3VqVM/ovSbehpronkQZMLZDbW82Kj269gF+wOzSv8MOGId9+Frb1V4mANu/r9K8+iLpzZRG152iN6eoFM54+5DxNOG9q/6S8bE9aAGlXkYpqtQpBvKvVFUbh1BnpdWTKSnP1wAXVjPU497DOEqF0yMpRYtO6PG5gYoIwYoZ+kfaPrZaUVvdfbbGsGcVnRhkr/Lc61wNbCNp/er1IP8el1Luq4PmPjgO4a7q76CzB2gzuvatDGHYB/mXASdJ+h/KZMJFlMIzv13Viba/Vn0cpXpwRx0tQmLGMklyleJVZeD0XZSkmrxoQ1VQJL2LsqL/2erQEZJ2tn30mENprEKpW7bPVu3Z3zpNjur677Upv7MHanE06ZKS2iI1pTDdAGw96H6IOdc43vabu16vBnyqn5SyrnO+A7yy8wAvaXvKKk5fqWXVfqjtbP+xer0OZa/Gowf4UVqjin8jd1WObSiOrZjfD/JTA5y/HHieZxdVOr2fe7WOtB1Je1P6Fu7M/JWTodNau66/uu2x/RKQtLwaZHUfu9L2Ktt8aGbv84pWKSPEcTBl8PlA25up7Nk7yfYeA1zjg8AnPELRCY1QJVXS9ykFw95MKSoyi+2+Ky5Lehqlp91jKJkROwEvs31+v9eok0rV7L0pDy1/bnuVk711ZDh03WObALcw0yJkXWA927/s92eIGZLeQyludRLl3+gw4D9sv3aAa8x772iCSrXqbW3fV71eDbhqXKmx6qpQCnRW4ldUKLV9zDji6BHXUKn9NX3vq2nB/tZpJ+kC209pOo5xyQpji9SUwnQTZTZplNnwjSQdY/udKhvzT6VUbR3Eq4FTJXVWSR9KWfns182UQU1nFnst4MYBY2gFSc+hrDauSUk73pbyEDzWlNRq1nFXykPwGcCewMVA3wNGSg+2izXT1P3J9N+aY+SVdNdYabW6t/+G8uDW/V44aJ+7UYxS4bSOFduOVwCPBy4HsP3vA6wcd+xGaaFxM8MXnRilSuphlBXaDZhdFRTKQ3lfA0aVSqsPqL5nZy/4ER5hL/iwJP0dsAvwWODXwAfoMdmygDoyHGppERLzvIHyvvlyyv11DvCxAa/RpkriG1DSx6EUDxuntlUo7WgkPbhyV5X10VnBHrQtWswh6YFdL5dRVq8f0lA4jcgKY0tpyE39kk6jVLA7l9mlfwcpcCBKesl1lIfAM22/v89zu2ekf87sKnB3r/zsWdf5CiXN5ZuUh72nUQY3vxr052latSq3O2VvR5PV7K6j3BtX2d5G0p8BH7M99+F6VdcZqajSKCvpde7bk3QWVWN5unqg2e6V4rkoNEKF0zpWbLuudbntJ3RmxSWtTpmd7vseVQ1FJ1RPldQDbX+8369f4BpDVxSuk6RfUybKTqIUmbl5yOusSUlfNHBDlULXz3mtK+YxbTR8JfLGqoLOiWNf4F3AeVUMT6ZUKf7CmL5/qyqUtoGkoygttJ4GvJOyv/Vztk9sNLAJJuknlPdPUVJRf0KZ+L+40cDGKAPGKaPRqup1v9muQdnj9R3g49U1VvlLra4374V+jo6a9uWMxdyH8epYEwPGTlW95ZSJgNuA79vechWnzr3Owyh9w1asynnIokqDpu2oxkqrkr7vql/fJFK97RveTUk5fAnwSuBw4Ie23zhgTDtT9kGeUu1zu78HKLSgGqqkzrneR2z3uwLefV6jFYXnxLIl5SF8Z8pD4A0eYI+mpGdTBpw3Uh52NgEOtX1mH+fWdo9FbyNsP2lNJXFJD6VM8Aq4fJypypnUmK2a8P8LygTR0yn/Jme7gf2t06DOrR+TLgPGWGGBh/COvh7G63rz1ohtOdpE0scpK75HU1IgXwWsYfuwMcfxIcpejxcCr6VUsL3adt8No7VAUaVhfykPupJe8769jwAn2r5ulOsM+b3rXCmtY+/zMsre0BUPGJTV575/Qair0ILtzat9d6fa7rvQQpWu/UlKWlunSurLbF/T7zXmXG/Yv49eg1zb7ruicB1Uiv/sBDyFkpr6YErV1L4qx1bXuB7Yy/aPq9ebAd+wvcUA1xj5Hoveht3rJunTcycOeh1bLAu9d3UMs2o6ZByZ1JhDLdnfOg2ygj0jA8Ypo1Ks4p3ML2wylgedut68JV0GPNVVpVVJ9wfOsd1XW442UakO+0ZmP4y/zVVBn4Zi2hhY3/a1A543clGlUdT55l2ldD2CklpyJ2NM6apzpXTOdYd9+Bx5gkY1FlrQcFVSe13nLNvPHODrWzWbrFJQ5OLqz4W2fz7ENWal11YrEBcMm3I77D0WvUl6ru2vDHHerPfA6v/Z62w/ps74VvL9O+9da1Mmiq6hvIduTVll3HkccXTFk0mNimooQBZFVrBnpOjN9DmFUmXw/ZS0w/1hsAI6kt4BvNuze+291vaxqzrX9ZWXHqktR5tUD91vrP40RtKnqErz275+yMvUUVRpFHX2LN2zvrAGNnJPygUMW2hhpL6plaELLUg6coHjANh+3wDXeoHtU6vznjn32CrUWUhoZN2DbUnDFlj4gaQzKIWVTGlX9F1Jz6++R9/VYytNFvOYCtWgfT9gU9vHS9oIeIjtK/o4d0VVUEmdCZUVVUEXK+a5bO9WxfMF4JBOpoZKJe6jVnbuIsVTR9HAabEbcKikRve3Tok29thsRFYYp0wnFUHSdbYfWx27yPYuA1xj3gzyKDN2w8xIa8S2HG2gGsra10nS7pR9ULsAmwJXU1Yt/mmAa4xcVGkUdacfSdqG8vcBZSA9VOrjoNqW5qJ6is0MXWihSmddkO2++8H2+jvt9++5zbPJI6TXnrKST9v2ASOEFUOQ9GFKSv/uth9dTcqeY3uHPs7trIK3oipoHe8ddRt0q8O0UYv2t06LrGBnhXEa/bHaj/Tvkv4e+AUwaHn81SSt1Uk7VOkhuNYIMQ0zI/1qRmvL0QadsvbPp5Rf/kz1el9K25Cxsv1tlXYYO1BmIA+jNDvue8AIfLX604gaV7CRdARwMDPtFj5TpYqOo5JcnSuldfiDuqo1VhM0dwxyAdvvVelfOHAj8UEGhAuRtCfwLOBhkv6561Pr03+D5TbPJg+1auIB9ijH2DyhmjC6CsD2b6vJsH50VsEfsWjRDeZHkj5G+f1m4O+AHzUZ0FIeLFbe3mt/K6VNUQwhK9hZYZw6knagvFlvALyN8rD0HtuXDXCN1wN/TUlvNWWl4Ku23117wPO/dy1tOdpk7h6ihY6NIY5zKS0cLqWsnlxs+1fjjGExjLBv71rgSS495ToplJeOaQ9jqwo1VO8bX2BmYPRQYB/by4e41vrMrqA7VGXRQScCqtXibSl9NN/c9anbKC0pfjvAtVo3mzzsqolKBdy3UyYAzqJkCLza9mdWemIsGkmXU9K9v1sNHDekrDCu8n2sbavgktam9JPs/D67EPiwG9yjv9Q1vb912i3VFewMGKdI9abwLtuvq+FaewJ7UAZr59g+e9Rr9vl9W5WqVwdJPwKe3dmrVg2Gz7D96DHH8X5Ks9k7Ke1SLqQMkPpeSVLDRZUWiGnYB+nrgB06DzbVg893O6nc49CmgYmkNRhhgkbSoZTB2h2UdLvOvpmh7o0RJgJWt93viuKixVHT957XU1LSu2wfPcA1rra9raTnAc8FXkMZQG9Tb7TRL0n7UTJmtgc+AewNHNvPPtu2TTZ105A9JaMe3ftbgU7BshX7W20f01RsMfmSkjpFbN8raXtJ8ogzAS49ulbZp2sRtC1Vrw6vAc6X1ClusjEwcG+4Udl+DYBKxdn9KSvID2GwdOORiyrVbYSZvlOAyyWdXr1+LlXP0XFpWZrLDpR7c3VgO0nY/tQA5x8FbGn71zXF841BvrhrT9dVqgrvdBth5bjJIi97S/qj7c8CqLTGGXR7wBrVx2cBn7f9G6npW21ps/1ZlX64nUnZ59ruK42zzrT8RfAxWlAsagn7se312rK/NaZLBozT5yrg3ySdyuyG031XwpP0ROBE4NHAmsBqwB9sr19zrL20eQ/RQDRTmfEGSjGQTt+z691AWwpJr6QUvdke+CnwL/RIaVqFdWyfW01K/BQ4TtJFlEHkRLH9PknnU/5OBOxv+6oGQ2psYFLtb9mMUgjp3uqwgUEGjDcyM6s9SiwPBx5p+9hq//Tqtm/r49Qjqo97jRpDt4ZTj54PfFXSfZSqvr+xffiA1/iaSi/GO4DDq/THpAs278HA7bZPkbShpE1s9+r/2VPLJps62hLHUtW2/a0xRZKSOmUWqIg3UCU8SVdSmrufSumv9BLgEbbH1haiTal6w2pbeq1KFcuLgOXDpuypVK/dhdJ24NuUokrvsv2o2gJdZJLWt32rpAf2+vywe+4mWZU2/ZhRMhMkbUe1asuQFXQlHUxZfX+g7c2qFOiTbO8xRDy17KVswpx7cz3gK5Q08jdDfz/LnP3gtwC3Vlko6wLr2f5l7YFHX1SqAj8OeJTtzSX9OXCq7Z2GvF4r9lRpyJ6SUY+27W+N6ZIBY8wj6Urbj1NX021Jl9gepCdbnfE0todoFG1681apnHut7a1GvM7IRZWaJunrtveS9BNmtz0Zac/dJKsyEl5l+79GuMYVlAbz11H2MAJg+5MDXONq4PGUxt/bVcdWtAjq8xrdeyk7/74T9e/adW+q62NHXz9L2yasYkZ1n28HfK/rPl/x+3aSSMP3lIx6tXl/a0y+pKROGUmbUtokPJHyoHEppSJe36kuwO3VG8/VVYW9/6JU12zKpDaKbk16re37JF0jaSPbPxvmGlVRpb+tiir9nrJ/ceLY3qv6uEnTsbTIg4EfVoO+7tXBQSY17rF95Ihx3Gn7rs4eO0mrs5Jepguoey/l2NV0b07jfvBpcZdtd/baVqu+k+pDVD0lKRM1twGnUfZExxi1fH9rTLgMGKfP54APAs+rXr+QUi7/CQNc48XAMuDvKQVb/pKyl6YRbUi1GUYL37wfCvygGhR072/t68GxzqJKbSDp3Lmpjr2OLRHH1XCN8yQdAnyN2YPOQVJBL5D0D8A6Kj0dD6+uN4ha9lK2haQdmSlGBNBvMaLWTFjFPF+SdDKwQZWGfQCTOzE6Sk/JWAQt3d8aEy4pqVNG0uW2nzDn2GW2nzjANY6w/U+rOhaDazK9VtJTeh0fJE1F0gmUAj5DF1Vqmkr7jPsB5wG7MvMLdX3gTI+53UlbdBWb+Zak+wGr9VlspnN+ryyGgVJBq9TpA4GnU/5dzgY+NsgERR17KdtioWJEA+4Lnfj94NOkSuH8C0oRtBX3ue1vNhrYkDRCT8lYfG3Z3xqTLwPGKdFVJOH1lAIHX6Ckcu0DrGX7bQNca95DxaTuI2ybpt+8Jf0ZM6lCV9j+1YDnj1xUqWmSjgBeTVlt+QUzA8ZbgY/a/kBDoTVmlGIzXcVVNnXVa3SEOJ5H6VE6dBXhOvZStkUdxYjmXC/v4y0gabnt7ZuOow4aoadkREyODBinxJwiCXP1WyRhX+BFlDYD3UVa1qfsT3pqHbFGMyT9LfAe4HzKfbIL8Drb/9pkXE2R9ErbJzYdRxuMUmymzuIq1YTE7sCFlEmvsz1gRd8mC3TVrY5iRHOul9WGFpD0QeATtr/bdCx1kLQFMz0lz3WfPSUjYnJkD+P0eIPtL404y38JpcDNg5nZ8wJlE/u1owYYjXsjsENnVbFKHfoWpUVGX2oqqtQW90nawPYtAJIeAOy7RB+oRyk2U1txFdv7S1qD0nPwRcCHJH3T9kGrOLVbHXsp26KOYkQrLNF7u412Aw6V9FNKan+nQvPEVUmtjNRTMiLaLyuMU6LmWf51gTuqypqbU/ZanGn77lqCjUbMXTGq9otd088qUtc5l1GKKn2+OvRC4JVz981OAklX2952zrElmbJXVUO+hdJz9ZWUYjM/dB+9VxejlHs1aHwmpRLvLrY3HODckfdStkUd+46jfar9wvPY/um4YxmVau4pGRHtlAHjlFCNPf8kLaekKz4AuAy4kjJ7uF8twUYjJL0H2JqZwd4+lN6MbxjgGiMXVWoLSdcC23T2h1VtQ661vWWzkY1fVYjjIEYrNjNycRVJz6RMQuxGSZ3+IqWAxkBpqRFtJunTtl+8qmOTQFPUUzIiFpaU1OlRZwl12b5d0oHAibbf3SmZHZNH0lq277T9OknPp+xRFfAR26f3eY1OUaXzJB3N7KJK31iMuMfgbEp5+5MoP8thwFnNhjR+1Urztba3YoTS/jWVcn8Z5d46dNjCN9Xq5MuBJ1eHzgdOnqQMCUkX295Z0m3MTg3upC6u31BoUY9Zk1LVZNWkFsGZpp6SEbGArDBOmZpm+a+ipKS9HzjQ9g/6LYAR7dOVrjz0DHYdRZXaphooHcpMsYZzKKtq9670xCkk6bPAMbZ/VtP1hi6uUkMl348BawCdqqgvBu4dcB9kRO0kHQP8A7AOM71CBdxFmcA7pqnYhiXpKEqrpacB76T0lPxcCopFTJesME6Zmmb5jwCOAU6vBoubUnrWxWRaU9JLgR2rFcZZ3EcPRdubLEpkDbJ9H/Dh6s9S91DgB1Vxle7+mmMtriLpBcB7manke6KkQSv57mB7m67X35Z0zTDxNGnOym9Mhx/bXk/Sl2z/bdPBjKpKZf8ipc7BrcCjgDd7QntKRsTCMmCcbkOll9m+kFLWHkkPqaquTlzT61jhMGA/YAPgOXM+Z2CVA8ZeJH3E9iGjhdYcSTsBxwEPp7wXdtL9Jm61tAZvbTqAyrGMWMkXuFfSZrZvrK6xKTNN7ydGVXTsGkkb1bXyG407BjgVeETTgdShSkX9iktPyQwSI6ZYBoxTrKYS6mdQ9kbG5Hqo7ZdXFUA/UuN1H1fjtZrwceA1wHImcEBRJ9sXVJUbH2n7W5LuB6zWQCjL5qSg/g+wbMBrvI6y1/YmyiTAwynVVidRrSu/0bjaWtC0yGWSdpiWnpIR0VsGjLEqw6a1Rnt0ZrUPA+ocMA60t6yFfmf7zKaDaANJBwOHAA8ENgMeBpxE2d85TmdJOpvZlXz7+jeS9ALbpwI3UfZUPYry/nX9sAV0WqAtK79RjzqL07XFtPWUjIgeUvQmVmqU4hXRDnW2XJlz3WXA/W3fOlKADZH0Lsoq2peZ3RT9e40F1ZCqNP7jgcu7SuM3UuhK0t8AO1EePC8coJJvbb1oIxZTHcXp2mKaekpGxMKywhg9SdqZkp72oWof0f1t92qIHe1X26y2pM9RVirvpaRy/omk99l+T02xjlOnn2R3aq2B3RuIpWl32r6r1LAASaszu53D2Ng+rWuSA0kPtP2bPk6dunS/qkjV/wX+lDKATluNKVBTcbq2eHuvnpKU6sQRMSUyYIx5JL2F8hD9KOAUSon6z1Bm/WPC2L6Lss9kxxpmtR9j+1ZJ+1H2t76BMnCcuAGj7d2ajqFFLpD0D8A6kp5GaavztXEHIelQ4HjgDuA+qgES0E8homlM93s38BzbP2o6kFg0Q/c+bYlp6ikZEQvIgDF6eR6wHfA9ANv/KWm9ZkOKUdU0q71G1Rj9ucAHbN/dadg8aSS9uddx28ePO5YWOBo4ELiO0pvyDOBjDcRxFLCl7V8PemLNEyNt8d8ZLE63Sd3y0d1TUlJnW8KKnpKNBRYRiyIDxujlrqpctgEkrdt0QFG7YWe1TwZuBq4BLqz2r0zkHka6qk4CawN7AUvq4VzSubb3AN5p+w00v9pxIzMNzYcyDel+Xf1Sr5T0ReArzN5nO1QrnIgaTVVPyYhYuRS9iXkkHUWpMvg04J3AAcDnbJ/YaGDRSpJWt31P03GMStJawFdtP6PpWMZF0g+Bl1Mqor6IOQOscRcAkrQdJQ3+cmYPkIbqAzupRbsknbKST9v2AWMLJqKHFJmKWFoyYIyeqn1MT6c8QJ5tO015A0lHUB7ob6OkLG4HHG37nEYDq4GkBwBX2H5k07GMi6S9KamoOwNXzvm0bY+1AFDVb/BiSmrsfV2BfHKccUTEyi1W9e2IaKcMGCOib5Kusb2NpGcArwDeBJwyiTPMkq5jphLoasCGwPG2P9BcVM2Q9Cbbb2tBHJfY3rHpONpC0ruBt1OKAJ0FbAO82vZnGg0sljxJazJTZOqg6vCKIlO2L2gotIhYBBkwxjwp5R4LkXSt7a0l/RNwvu3TJV3V6d03CSRtYvsnc/qH3UMpMDLxqbXDqHpqvgjY1PbxkjYCHmL7ijHH8Y/ATykVWrtTUvtpqzF1JF1te1tJz6MUmnoNcJ7tbZqNLKKYpp6SEbGwDBhjHkk/JqXco4dqb9XDgE0oqx2rUQaOE1NGXdJy29t3FXxZ8iR9mJICurvtR1fpuefY3mHMcfTq9Wrb/bTVmDqSfmB7S0kfBU6zfVZnlb/p2CLmmrTJw4joX6qkRi8p5R4LOZCyZ+Um27dLehCwf7MhDWxZ1Wt0c0lHzv2k7fc1EFPTnlAVsLgKwPZvq5SzsZD0AtunAnvYvmlc33cCfE3S9ZSU1MMlbQj8seGYIhbSdJXliFgky5oOIFrpSklflLSvpOd3/jQdVLSCgccAnaqV61JaUkySF1IeulcH1uvxZym6u2q43WmlsyFdRWfG4Jjq47+O8Xu2lqQXVP95MvAk4HG276a0HPk/jQUWsRKTWJE4IvqTlNSYZ4GS7inlHq1JXayDpD1tn9l0HG0gaT9gH0oRi08CewPHVqt+4/j+qbjYJS0LIiKiTTJgjIi+dT3IrtirMg17qiR93fZeTcfRhKrgzROB3wB7UIpcnTvOtPRUXJwtA+iIiGiT7GGMFSS93va7JZ3ITLuBFYZtnh1TpenUxcXysKYDaIrt+ySdYPtJwPUNxXAXcJmkHVNxEYBnMzOAPqE6tmIAHRERMU4ZMEa3zorC3AbeER3/DJwO/GnVAmFv4NhmQ6rFVU0H0LBzJP0N8GU3mHbSGSxW1FQcTcsAOiIi2iQpqbEgSetT9i7e1nQs0R6StqCh1MW6SVoH2Mj2DU3H0iRJt1EKGN1DKQjUeO9VSYeniMaMtCyIiIimZMAY80h6HHAKpWKkgFuAA2wvbzKuaF7V0H0e2z8bdyyjkvQc4L3AmrY3kbQtcHz2h0UbZQAdERFNyYAx5pF0LfAK2xdVr3cGPmR762Yji6ZJuo6yf1GUdhqbADfY3rLRwIYgaTmwO3B+VwGfa5f6fS7pONvHNR1HREREtEP6MEYvt3UGiwC2LwaSlhrYfqztrauPjwQeD1zcdFxDusf275oOooWywhoRERErpOhNrCCpU1DhCkknA5+nrCbtA5zfVFzRXra/J2niejBWvi/pRcBqkh4JvAq4pOGY2mDJFpuJiIiI+ZKSGitIOm8ln7bt3ccWTLSSpCO7Xi6jlP5/kO1nNBTS0CTdD3gj8HTKIOls4G22/9hoYA2TtMz2NLRKiYiIiBpkwBgRfZP0lq6X9wA3A6ct9UHWpJO0NnAgsCVlbyoAtg9oLKiIiIhohaSkxjySNgBeAmxM1z1i+1UNhRQtYfutTcdQF0mbA0cx/z5fiivpnwauB54BHA/sx0xf1oiIiFjCssIY80i6BLgMuA5YkZpm+5ONBRWtIOmrPQ7/DrgSOHmSVholXQOcBCwH7u0cX4rtYzo9/jpVYiWtAZy9RAfPERER0SUrjNHL2raPXPWXxRL0E2BDSkEkKAWR/hvYHPgo8OKG4hrGPbY/3HQQLXF39fEWSVsBv6SsvEZERMQSlxXGmEfSa4DfA18H7uwct/2bxoKKVpB0oe0n9zom6QeT1I9R0nHAr4DTWeL3uaSDgNOArYFTgPsDb7J9cqOBRUREROMyYIx5JL0C+EfgFkpbDShVUjdtLKhoBUk/Ap5h+2fV642As2w/ppPW2GyE/ZP0kx6Hc59HREREdElKavRyJPAI279uOpBondcCF0u6kdKKYhPgcEnrAhO1x9X2Jk3H0BaSHgQcB+xEmSS6iNJi5H+ajCsiIiKalxXGmKcqbPJC27c3HUu0g6QX2D5V0ibAfwJbUAaM109SoRsASbvb/rak5/f6vO0vjzumpkn6JnAh8Jnq0H7Arraf2lxUERER0QYZMMY8kk6n9GM7j9l7u9JWY4mS9D3bf9X52HQ8o5D0VttvkXRKj097KfYelLTc9vZzjl1p+3FNxRQRERHtkAFjzCPppb2Op63G0lWtQK0ObEtJV5zF9l+PO6aoj6T3UlqjfKk6tDewpe23NBdVREREtEEGjNGTpDUprRIAbrB998q+PqZbdT/8FaXB+0HV4T+npKdi+4KGQhuYpJW2jLH9vnHF0haSbgPWpfSjFLAM+EP1adtev6nYIiIiolkpehPzSNqVUsDkZsrD419KeqntCxsMKxpk+y7gMkk72v7/MJOm2nBow1iv6QDaxnb+TiIiIqKnrDDGPJKWAy+yfUP1enPg83P3OMXSNmltNGI+SVvYvl5Sz4G/7e+NO6aIiIhol6wwRi9rdAaLALb/n6Q1mgwoWumjTQcwCkkbAgcDG9P1XrjEit4cCRwCnNDjcwZ2H284ERER0TZZYYx5JP0L5WHx09Wh/YDVbe/fXFQR9ZJ0CaWAz3LK3j0AbJ/WWFBj1tUuZVPbNzUdT0RERLRPBowxj6S1gFcAO1P2MF4IfMj2nSs9MWKCSLra9rZNx9GkaWqXEhEREYsjA8aYR9K6wB9t31u9Xg1Yy/btzUYWUR9JbwcusX1G07E0Je1SIiIiYlUyYIx5JF0GPNX276vX9wfOsb1js5FF1KerlcSdwN2U1fQl1UJimtqlRERExOJI0ZvoZe3OYBHA9u8l3a/JgCLqllYSU9cuJSIiIhZBBozRyx8k/VWnpL6k7YE7Go4pohZpJTFfZ7BYUWOBREREROtkwBi9vBo4VdJ/Vq8fCuzTXDgRtUoriZWb6HYpERERUa/sYYwVukrsbwL8HHgUZbXhett3NxtdRD3SSiIiIiKifxkwxgopsR9LQe7ziIiIiP5lwBgrpMR+LAW5zyMiIiL6lwFjrJAS+7EU5D6PiIiI6F8GjDGPpA1TYj+mXe7ziIiIiFVb1nQA0T4psR9LQe7ziIiIiFXLgDFWJSX2YynIfR4RERHRQ1JSIyIiIiIioqesMEZERERERERPGTBGRERERERETxkwRkRE1EjSJyRZ0sZNxxIRETGqDBgjIiJWoRoAruzPy5qOMSIiYjGs3nQAERERE+StCxy/epxBREREjEsGjBEREX2yfVzTMURERIxTUlIjIiLGQNLLJJ0m6SZJd0i6VdJ3JP3dSs7ZQdI5km6rvv5bkp4k6bgqFXbXOV+/i6SvSfq5pDsl/VLSZZLestg/X0RETKesMEZERIzHh4EfAhcC/wU8CHgW8GlJj7L9pu4vlrQLcA6wBnAacCPwWOA84NtzLy7pmcA3gFuBrwK/AB4IPBo4nIXTaSMiIhaUAWNERESfJB3X4/DNtj/Rx+lb2b5xzvXWBM4EjpZ0ku1fVMeXAf8CrA08y/aZXeccRhl8znUwJXNoV9vXzPk+D+4jvoiIiHkyYIyIiOhfr9TOC4BPrOrEuYPF6thdkj4I7A7sAXyq+tSOwCOA87oHi5WPAK8BNl/gW93R4/v8elXxRURE9JI9jBEREX2yrR5/du3nXEkbSfqgpOsl3d5pyUFJNwV4WNeXb1d9vLhHDPcBl/T4Fp+tPl4u6SRJ+0j6i/5+soiIiN6ywhgREbHIJG0KXAE8ALiIsjfxd8C9wMbAS4G1uk75k+rjfy9wyXnHbX9Z0l7Aa4EDgEOr770cOMb2N0f+QSIiYsnJgDEiImLxHUkpcrP/3P2OkvalDBi73Vp9/LMFrtfzuO1vAN+QtC7wBGAv4OXA1yVtZ/uHw4UfERFLVVJSIyIiFt8jqo+n9fjcU3ocu6r6uPPcT1QFcXZc2Tez/Qfb37Z9JPAOYE1gz/7DjYiIKDJgjIiIWHw3Vx937T4o6RnAQT2+/juUNhq7SZo70DuEHgVvJO0haZ0e1+qsRt4+QLwRERFAUlIjIiLG4UPA/sCpkk6j9EjcCngm8CVgn+4vtn2fpIOAs4CvVufcCGwNPI3SimNP4L6u004ANpZ0PmWAehewPaUC60+BLyzSzxYREVMsK4wRERGLzPa1wG6U6qbPouwrXB94PnDSAuecT0lXPR94NvAqYJ3qOjdVX3Zr1ynvoAwkt6SsWh5GWV18B7CD7d/W+CNFRMQSIdtNxxAREREDkPQdSlGbP7H9h6bjiYiI6ZUVxoiIiBaSdD9JG/Q4/jJK0ZtzMliMiIjFlhXGiIiIFpK0BaVa6jeBH1PqDmxHqZx6C7Cj7R81FmBERCwJGTBGRES0kKQHAO+h7GN8CLAW8EvgW8A/2r6xwfAiImKJyIAxIiIiIiIiesoexoiIiIiIiOgpA8aIiIiIiIjoKQPGiIiIiIiI6CkDxoiIiIiIiOgpA8aIiIiIiIjoKQPGiIiIiIiI6Ol/AY3yOj0mimP8AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = o1flags_list.copy()\n",
    "x.append('ALL')\n",
    "plt.figure(figsize=(15,6))\n",
    "plt.scatter(x, t1, color='red', marker='o')\n",
    "plt.xticks(rotation=90);\n",
    "plt.xlabel('Flags', fontsize=20)\n",
    "plt.ylabel('Multiplication time (s)', fontsize=16)\n",
    "plt.yticks(fontsize=14);\n",
    "plt.title(\"GCC O1 flags\", fontsize=18);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd277dd1-24ed-4a95-afb3-ac75d0eae8f9",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## GCC O2 Flags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "c6096e16-724e-4254-941f-68971aaae99e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-falign-functions b' Matrix multiplication took:    2.4355219999999997       s\\n'\n",
      "-falign-jumps b' Matrix multiplication took:    2.4127700000000001       s\\n'\n",
      "-falign-labels b' Matrix multiplication took:    2.4153259999999999       s\\n'\n",
      "-falign-loops b' Matrix multiplication took:    2.4305980000000003       s\\n'\n",
      "-fcaller-saves b' Matrix multiplication took:    2.4284720000000002       s\\n'\n",
      "-fcode-hoisting b' Matrix multiplication took:    2.4179640000000000       s\\n'\n",
      "-fcrossjumping b' Matrix multiplication took:    2.4261889999999999       s\\n'\n",
      "-fcse-follow-jumps b' Matrix multiplication took:    2.4208439999999998       s\\n'\n",
      "-fcse-skip-blocks b' Matrix multiplication took:    2.4149500000000002       s\\n'\n",
      "-fdelete-null-pointer-checks b' Matrix multiplication took:    2.4038640000000000       s\\n'\n",
      "-fdevirtualize b' Matrix multiplication took:    2.4052359999999999       s\\n'\n",
      "-fdevirtualize-speculatively b' Matrix multiplication took:    2.4124360000000000       s\\n'\n",
      "-fexpensive-optimizations b' Matrix multiplication took:    2.4302290000000002       s\\n'\n",
      "-ffinite-loops b' Matrix multiplication took:    2.4225120000000002       s\\n'\n",
      "-fgcse b' Matrix multiplication took:    2.4310090000000000       s\\n'\n",
      "-fgcse-lm b' Matrix multiplication took:    2.4235099999999998       s\\n'\n",
      "-fhoist-adjacent-loads b' Matrix multiplication took:    2.4231549999999999       s\\n'\n",
      "-finline-functions b' Matrix multiplication took:    2.4136839999999999       s\\n'\n",
      "-finline-small-functions b' Matrix multiplication took:    2.4527649999999999       s\\n'\n",
      "-findirect-inlining b' Matrix multiplication took:    2.4076710000000001       s\\n'\n",
      "-fipa-bit-cp b' Matrix multiplication took:    2.4276380000000000       s\\n'\n",
      "-fipa-cp b' Matrix multiplication took:    2.4631349999999999       s\\n'\n",
      "-fipa-icf b' Matrix multiplication took:    2.4180109999999999       s\\n'\n",
      "-fipa-ra b' Matrix multiplication took:    2.4140669999999997       s\\n'\n",
      "-fipa-sra b' Matrix multiplication took:    2.4226989999999997       s\\n'\n",
      "-fipa-vrp b' Matrix multiplication took:    2.4397359999999999       s\\n'\n",
      "-fisolate-erroneous-paths-dereference b' Matrix multiplication took:    2.4326150000000002       s\\n'\n",
      "-flra-remat b' Matrix multiplication took:    2.4193660000000001       s\\n'\n",
      "-foptimize-sibling-calls b' Matrix multiplication took:    2.4320839999999997       s\\n'\n",
      "-foptimize-strlen b' Matrix multiplication took:    2.4361179999999996       s\\n'\n",
      "-fpartial-inlining b' Matrix multiplication took:    2.4429870000000000       s\\n'\n",
      "-fpeephole2 b' Matrix multiplication took:    2.4259679999999997       s\\n'\n",
      "-freorder-blocks-algorithm=stc b' Matrix multiplication took:    2.4243199999999998       s\\n'\n",
      "-freorder-blocks-and-partition b' Matrix multiplication took:    2.4225460000000001       s\\n'\n",
      "-freorder-functions b' Matrix multiplication took:    2.4337299999999997       s\\n'\n",
      "-frerun-cse-after-loop b' Matrix multiplication took:    2.4406120000000002       s\\n'\n",
      "-fschedule-insns b' Matrix multiplication took:    2.4199889999999997       s\\n'\n",
      "-fschedule-insns2 b' Matrix multiplication took:    2.4473900000000000       s\\n'\n",
      "-fsched-interblock b' Matrix multiplication took:    2.4188810000000003       s\\n'\n",
      "-fsched-spec b' Matrix multiplication took:    2.4242490000000001       s\\n'\n",
      "-fstore-merging b' Matrix multiplication took:    2.4373450000000001       s\\n'\n",
      "-fstrict-aliasing b' Matrix multiplication took:    2.4301059999999999       s\\n'\n",
      "-fthread-jumps b' Matrix multiplication took:    2.4302440000000001       s\\n'\n",
      "-ftree-builtin-call-dce b' Matrix multiplication took:    2.4524180000000002       s\\n'\n",
      "-ftree-pre b' Matrix multiplication took:    2.4406970000000001       s\\n'\n",
      "-ftree-switch-conversion b' Matrix multiplication took:    2.4483790000000001       s\\n'\n",
      "-ftree-tail-merge b' Matrix multiplication took:    2.4331040000000002       s\\n'\n",
      "-ftree-vrp b' Matrix multiplication took:    2.4175629999999999       s\\n'\n",
      "ALL b' Matrix multiplication took:    2.4299759999999999       s\\n'\n"
     ]
    }
   ],
   "source": [
    "t2=[]\n",
    "for flag in o2flags_list:\n",
    "        comp = subprocess.run([compiler, flag, sourcefile], capture_output=True)\n",
    "        if comp.returncode != 0:\n",
    "            print('Compilation with this flag failed', flag)\n",
    "            print('Error message: ', comp.stderr)\n",
    "        else:\n",
    "            run = subprocess.run(['./a.out'], capture_output=True)\n",
    "            print(flag, run.stdout)\n",
    "            t2.append(retrieve_time(run.stdout))\n",
    "# now combine all flags\n",
    "cmd = o2flags_list.copy()\n",
    "cmd.insert(0, compiler)\n",
    "cmd.append(sourcefile)\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('ALL', run.stdout)\n",
    "    t2.append(retrieve_time(run.stdout))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "f7cee574-3e59-41a4-971c-2e8dc90e494f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = o2flags_list.copy()\n",
    "x.append('ALL')\n",
    "plt.figure(figsize=(15,6))\n",
    "plt.scatter(x, t2, color='blue', marker='s')\n",
    "plt.xticks(rotation=90);\n",
    "plt.xlabel('Flags', fontsize=20)\n",
    "plt.ylabel('Multiplication time (s)', fontsize=16)\n",
    "plt.yticks(fontsize=14);\n",
    "plt.title(\"GCC O2 flags\", fontsize=18);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a63d2e21-61fe-49ee-a5ca-d05f86510a63",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## GCC O3 Flags"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "a5323c4a-b975-4a7e-8818-9874387a67d3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-fgcse-after-reload b' Matrix multiplication took:    2.4262280000000001       s\\n'\n",
      "-fipa-cp-clone b' Matrix multiplication took:    2.4080599999999999       s\\n'\n",
      "-floop-interchange b' Matrix multiplication took:    2.4482990000000000       s\\n'\n",
      "-floop-unroll-and-jam b' Matrix multiplication took:    2.4117199999999999       s\\n'\n",
      "-fpeel-loops b' Matrix multiplication took:    2.4068909999999999       s\\n'\n",
      "-fpredictive-commoning b' Matrix multiplication took:    2.4246729999999999       s\\n'\n",
      "-fsplit-loops b' Matrix multiplication took:    2.4188890000000001       s\\n'\n",
      "-fsplit-paths b' Matrix multiplication took:    2.4205299999999998       s\\n'\n",
      "-ftree-loop-distribution b' Matrix multiplication took:    2.4329890000000001       s\\n'\n",
      "-ftree-loop-vectorize b' Matrix multiplication took:    2.4183599999999998       s\\n'\n",
      "-ftree-partial-pre b' Matrix multiplication took:    2.4484409999999999       s\\n'\n",
      "-ftree-slp-vectorize b' Matrix multiplication took:    2.4389550000000000       s\\n'\n",
      "-funswitch-loops b' Matrix multiplication took:    2.4325329999999998       s\\n'\n",
      "-fvect-cost-model b' Matrix multiplication took:    2.4320849999999998       s\\n'\n",
      "-fvect-cost-model=dynamic b' Matrix multiplication took:    2.4250500000000001       s\\n'\n",
      "-fversion-loops-for-strides b' Matrix multiplication took:    2.4187230000000000       s\\n'\n",
      "ALL b' Matrix multiplication took:    2.4445450000000002       s\\n'\n"
     ]
    }
   ],
   "source": [
    "t3 = []\n",
    "for flag in o3flags_list:\n",
    "        comp = subprocess.run([compiler, flag, sourcefile], capture_output=True)\n",
    "        if comp.returncode != 0:\n",
    "            print('Compilation with this flag failed', flag)\n",
    "            print('Error message: ', comp.stderr)\n",
    "        else:\n",
    "            run = subprocess.run(['./a.out'], capture_output=True)\n",
    "            print(flag, run.stdout)\n",
    "            t3.append(retrieve_time(run.stdout))\n",
    "# now combine all flags\n",
    "cmd = o3flags_list.copy()\n",
    "cmd.insert(0, compiler)\n",
    "cmd.append(sourcefile)\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('ALL', run.stdout)\n",
    "    t3.append(retrieve_time(run.stdout))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "995eb15a-39a5-42c0-b26e-83565bbc776b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = o3flags_list.copy()\n",
    "x.append('ALL')\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.scatter(x, t3, color='green', marker='^')\n",
    "plt.xticks(rotation=90);\n",
    "plt.xlabel('Flags', fontsize=20)\n",
    "plt.ylabel('Multiplication time (s)', fontsize=16)\n",
    "plt.yticks(fontsize=14);\n",
    "plt.title(\"GCC O3 flags\", fontsize=18);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5f87e9b-357c-4720-ba97-f5dd5d4663a8",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "## All flags combined"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e85a6a35-9453-4db6-bed3-ccc602393f4f",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### O1 + O2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "7d417228-ab6f-4d76-89b6-31dad1962162",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O1 + O2 b' Matrix multiplication took:    2.4036590000000002       s\\n'\n"
     ]
    }
   ],
   "source": [
    "cmd = o1flags_list.copy()\n",
    "cmd = cmd + o2flags_list\n",
    "cmd.insert(0, compiler)\n",
    "cmd.append(sourcefile)\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('O1 + O2', run.stdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdc01a69-2b36-45b9-a714-8ae43e95d6ad",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### O1 + O2 + O3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "437e6260-47fe-4ab6-b38c-70c20f236a90",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "O1 + O2 b' Matrix multiplication took:    2.4869919999999999       s\\n'\n"
     ]
    }
   ],
   "source": [
    "cmd = o1flags_list.copy()\n",
    "cmd = cmd + o2flags_list + o3flags_list\n",
    "cmd.insert(0, compiler)\n",
    "cmd.append(sourcefile)\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('O1 + O2 + 03', run.stdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "280af73d-7e43-498b-b70c-d0f85020c61b",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "# Using combo flags"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e438f9a1-459c-4b25-abbd-4d6cc96ff324",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### No optimization (O0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "b99645ca-cc14-4ad8-96f6-1a447d29078b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-O0 b' Matrix multiplication took:    2.4108269999999998       s\\n'\n"
     ]
    }
   ],
   "source": [
    "cmd = [compiler, '-O0', sourcefile]\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('-O0', run.stdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9c03d92-e791-4472-a29c-65b7941a2e5d",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Level 1 optimization (O1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "469402e9-acf4-4eaa-bc03-5eb839640882",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-O1 b' Matrix multiplication took:   0.33455999999999997       s\\n'\n"
     ]
    }
   ],
   "source": [
    "cmd = [compiler, '-O1', sourcefile]\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('-O1', run.stdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f69c337-1519-49da-bc01-ccab34d0681f",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Level 2 optimization (O2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "4c93565e-2e65-4ba3-8a42-dcfb06d7bedc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-O2 b' Matrix multiplication took:    4.0000000000005309E-006  s\\n'\n"
     ]
    }
   ],
   "source": [
    "cmd = [compiler, '-O2', sourcefile]\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('-O2', run.stdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a02bf2bd-fe48-48dc-a5b2-20b3e2113573",
   "metadata": {
    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
    "### Level 3 optimization (O3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "2402c147-4cb6-4677-a30c-cf2abcbdeba5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-O3 b' Matrix multiplication took:    2.0000000000002655E-006  s\\n'\n"
     ]
    }
   ],
   "source": [
    "cmd = [compiler, '-O3', sourcefile]\n",
    "comp = subprocess.run(cmd, capture_output=True)\n",
    "if comp.returncode != 0:\n",
    "    print('One of the flags failed')\n",
    "    print(comp.stderr)\n",
    "else:\n",
    "    run = subprocess.run(['./a.out'], capture_output=True)\n",
    "    print('-O3', run.stdout)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1223475e-8fb5-4c86-82ab-63d636fa007c",
   "metadata": {
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   },
   "source": [
    "# Conclusions\n",
    "\n",
    "- None of the flags listed in the *Optimize Options* of the GNU Compiler documentation changes the execution time of a matrix multiplication significantly.\n",
    "- Instead of trying individual options, one should always first use the bundled options (-Ox)\n",
    "- For this simple code, level 2 optimization reduces execution time dramatically\n",
    "- Compiler optimizations can be obscure. Make sure your code runs without errors before using them (writing a simple test is a good practice)"
   ]
  }
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