{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "58fc6db9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e07be4b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "f = open(\"compressed_tree.json\")\n",
    "tree = json.loads(f.read())\n",
    "layers = tree[\"layers\"]\n",
    "classes = tree[\"classes\"]\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1516ff91",
   "metadata": {},
   "outputs": [],
   "source": [
    "field_width = {\n",
    "\t\"src\": 16,\n",
    "\t\"dst\": 16,\n",
    "\t\"protocl\": 8,\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "55167c28",
   "metadata": {},
   "outputs": [],
   "source": [
    "def worst_case(tree):\n",
    "\n",
    "\trmt = []\n",
    "\n",
    "\tstep = 0\n",
    "\n",
    "\tfor layer in layers:\n",
    "\n",
    "\t\t# assume that each range requires all of 2*k bits when performing prefix expansion\n",
    "\t\tnum_ranges = len(layers[layer])\n",
    "\t\trange_expansion_bits = 2 * field_width[layer]\n",
    "\n",
    "\t\ttcam = {\n",
    "\t\t\t\"id\": f\"{layer}_range\",\n",
    "\t\t\t\"step\": step,\n",
    "\t\t\t\"match\": \"ternary\",\n",
    "\t\t\t\"entries\": num_ranges,\n",
    "\t\t\t\"key_size\": range_expansion_bits\n",
    "\t\t}\n",
    "\n",
    "\t\t# assume no pointer reuse for metadata storage\n",
    "\t\tram = {\n",
    "\t\t\t\"id\": f\"{layer}_meta\",\n",
    "\t\t\t\"step\": step,\n",
    "\t\t\t\"match\": \"exact\",\n",
    "\t\t\t\"method\": \"index\",\n",
    "\t\t\t\"key_size\": math.ceil(math.log2(num_ranges)),\n",
    "\t\t\t\"data_size\": len(classes)\n",
    "\t\t}\n",
    "\n",
    "\t\trmt.append(tcam)\n",
    "\t\trmt.append(ram)\n",
    "\n",
    "\t\tstep += 1\n",
    "\n",
    "\treturn rmt\n",
    "\n",
    "worst_case_rmt = worst_case(tree)\n",
    "f = open(\"worst_case_rmt.json\", \"w+\")\n",
    "f.write(json.dumps(worst_case_rmt, indent=4))\n",
    "f.close()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "48011528",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TCAM mapping: \n",
      "[1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "SRAM mapping: \n",
      "[1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]\n",
      "id mapping: \n",
      "[['dst_range', 'dst_meta'], ['src_range', 'src_meta'], ['protocl_range', 'protocl_meta'], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], [], []]\n"
     ]
    }
   ],
   "source": [
    "! command python3 ideal-rmt-simulator/sim.py worst_case_rmt.json"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "switch",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.7"
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 "nbformat": 4,
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