{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 844,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "plt.rcParams[\"font.size\"] = 16\n",
    "\n",
    "g_label_fontsize = 16\n",
    "\n",
    "colors = [\n",
    "    \"#5D7599\",\n",
    "    \"#233142\",\n",
    "    \"#F95959\",\n",
    "]\n",
    "\n",
    "edgecolors = [\n",
    "    \"#FFFFFF\",\n",
    "    \"#FFFFFF\",\n",
    "    \"#FFFFFF\",\n",
    "]\n",
    "\n",
    "hatches = [\"\\\\\\\\\", \"\", \"\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 845,
   "metadata": {},
   "outputs": [
    {
     "data": {
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4QbNdG6Dc0tTfn3nmmbwb1tdee+3Yb7/96o7nzZsXt912Wxx//PGxzTbbRPfu3aOmpiZ69OgRO++8c/zqV7+KCRMmNFmdAM0hTf39384999x6/yOUuXPnxj777BMjR47Min/66aexzz77xMcffxwRX37ff+yxx2Lttddu8noByG/GjBmxbNmyvK8l9TOKlisN37nScA8ApaY3ZjPzAKRFmvu7mQegpUpTbzfvAPCVNPX3fzPvAJAOLXHewaIIVmvq1Kl54+3bt48OHToUnbempiZvfObMmUXnrE8a7gGglPTFbM8880zWcVVVVZx22mllqgageGnt7/Pnz4+jjz46MplM9OzZM/74xz82y3UBKkWa+vtNN92UN37ggQfGmmuuGW+//Xb813/9V2y44YZx5JFHxsiRI+PNN9+MWbNmxbJly+KTTz6J8ePHx0UXXRRbb711HHnkkTkD0ABJkab+/m+tW7eO++67L7bddtu8ry9fvjyOP/74+J//+Z+ora2NmTNnxl577RUTJ06MmpqauPrqq+OOO+7wH7IAlFl9n1EREd27dy86b7n/jomWKQ3fudJwDwClpjdmM/MApEVa+7uZB6AlS1NvN+8A8JU09fd/M+8AkA4tcd7BoghWa9q0aXnjjf3iUt9vjKb4w24a7gGglPTFbGPGjMk6PuKII2LrrbcuTzEAjZDW/n7iiSfG9OnTo1WrVnHrrbfGWmut1SzXBagUaenvtbW18cADD+R9bdddd41TTz01+vfvHzfccEMsXrw42rdvHz179oyOHTvWm/O2226Lfv36xfjx45ukZoCmlJb+/p86deoUjz32WGy33Xb1vufyyy+PIUOGxB577BETJkyIHXbYIV555ZU45ZRTmqVGAFatvs+oiMZ9TpX7M4qWKQ3fudJwDwClpjdmM/MApEVa+7uZB6AlS0tvN+8AkC0t/f0/mXcASL6WOO9gUQSrtWDBgrzxpvryVt/1GiMN9wBQSvriVxYtWhT3339/3XHr1q3jf//3f8tYEUDx0tjfb7755rjrrrsiIuLss8+OPfbYo8mvCVBp0tLfX3vttZg3b17e184888y4+uqrY5111onzzjsv3njjjVi0aFF8+OGHsWDBgvjXv/4Vp556aqyxxho5586dOzcGDRoUTz/9dJPUDdBU0tLf81l33XXjiSeeiAEDBtT7noceeiimTJkSAwcOjBdeeCH69evXbPUBsGqr+sxo27Zt0Xkr4TOKlicN37nScA8ApaY3fsXMA5AmaezvZh6Ali4tvd28A0C2tPT3fMw7ACRbS5x3sCiC1friiy/yxhvzmyIiorq6Om986dKljcqbTxruAaCU9MWv3HzzzVlfys4666zYZJNNylgRQPHS1t+nTp0aP/7xjyMiYscdd4wLLrigSa8HUKnS0t+feOKJVb5+3nnnxQcffBDnn39+9O/fP+u1LbfcMn73u9/FM888E126dMk5d9GiRTFs2LD45JNPSlozQFNKS3+vT+fOneOJJ56IQw45ZJXve/rpp+Pkk0+O5cuXN1NlAKxOfZ9Rbdq0iaqqqqLzVspnFC1LGr5zpeEeAEpNb/yKmQcgTdLW3808AKSnt5t3AMiWlv5eH/MOAMnVEucdLIpgter7jdHYLV8rV67MG1+2bFmj8uaThnsAKCV98UvLli2Lyy+/vO64b9++cd5555WxIoDGSVN/r62tjaOOOioWLFgQ7du3j9tuuy1at27dZNcDqGRp6e+vv/563vhOO+0UEydOjPPPPz/at2+/yhwDBgyIhx56KNZcc82c1+bMmRNHHXVUKUoFaBZp6e+r0rZt27jnnnvi+OOPX+X7rr/++thrr71i9uzZzVQZAKvSEj6jaDnS8Os5DfcAUGp645fMPABpk6b+buYB4Etp6e3mHQCypaW/r4p5B4BkagmfUf/JoghWK5PJ5I03dstXbW1t3nhNTU2j8uaThnsAKCV98Ut/+tOfYurUqRHx5WavG264oWJrBWiINPX3X//61/HPf/4zIiJ+97vfxWabbdZk1wKodGnp75MmTcobHzJkSPTs2bPBeXbeeec455xz8r72+OOPx+OPP15UfQDNLS39fXWefvrpePDBB6N169YxYMCAet/33HPPxS677BLvvvtuM1YHQD4t5TOKliENv57TcA8ApaY3fsnMA5A2aervZh4AvpSW3m7eASBbWvr76ph3AEielvIZ9XUWRbBaHTp0aJK8S5YsyRtv7GaWfNJwDwClpC9GzJ07N+tJGhdccEHsvvvuZawIoPHS0t9ffvnluOCCCyIi4tBDD13tNl6AtEtLf588eXLeeK9evQrOdcYZZ8Q666yT97XLLrus4HwA5ZCW/r4qv/3tb2OfffaJ+fPnx7333hvPPfdc/OxnP6v3/e+//37ssssu8cILLzRjlQD8p5bwGUXLkYZfz2m4B4BS0xvNPADplJb+buYB4Ctp6e3mHQCypaW/r4p5B4BkagmfUf/JoghWq2PHjnnj9f3CbqilS5fmjTd2M0s+abgHgFLSFyN+8pOfxLx58yIi4jvf+U784he/KHNFAI2Xhv7+xRdfxPe///1Yvnx5bLDBBvHnP/+55NcASJo09Pfly5fHwoUL8762wQYbFJyvffv2cfLJJ+d9bezYsXXf9QEqWRr6e31WrlwZP/rRj+Kss86K2traGDlyZAwZMiRatWoVl156afzlL3+JNddcM++58+bNi/322y+ef/75ZqsXgGxp/oyi5UnDr+c03ANAqemNZh6AdEpDfzfzAJAtDb3dvANArjT09/qYdwBItjR/RtXHoghWq6l+YyxatChvvHPnzo3Km08a7gGglFp6X3zggQfilltuiYiI3r17x6233hpVVVVlrgqg8dLQ33/605/Gu+++G1VVVfGXv/yl3u3pAC1JGvp7fUMTERHdu3cvKmd9T1/KZDLxzDPPFJUToDmlob/ns3Llyjj88MPjj3/8Y0REnHbaafH9738/6z0/+MEP4h//+Ee9NS1YsCD222+/eOutt5q6XADySOtnFC1TGn49p+EeAEqtpfdGMw9AWqWhv5t5AMiWht5u3gEgVxr6ez7mHQCSL62fUatiUQSrtfbaa+eNN/Y3xoIFC/LGN95440blzScN9wBQSi25L06bNi2OO+64iIhYZ5114pFHHokuXbqUuSqA0kh6f3/wwQfj+uuvj4iIM844IwYNGlTS/ABJlfT+HvHl05PqU+z38Y033jj69++f97UXX3yxqJwAzSkN/f0/ZTKZOProo+Oee+6JiIg+ffrEpZdemve9AwcOjGeffTZ69OiR9/WFCxfG4MGDY/78+U1WLwD5pfEzipYrDb+e03APAKXWknujmQcgzZLe3808AORKem+PMO8AkE8a+vt/Mu8AkA5p/IxaHYsiWK2+ffvmjde3AaWhPvvss7zxnj17NipvPmm4B4BSaql9cfny5XH44YfH3LlzY80114zRo0fX++8CIImS3t+/vin9t7/9bVRVVRX1z7HHHps3f33vB6h0Se/vERFrrLFGva916tSp6Lz77bdf3vjMmTOLzgnQXNLQ3//TJZdcErfddlvd8cUXXxw1NTX1vn+rrbaKZ599Nnr16pX39Q8//DDOOuusUpcJwGrU9xm1cuXKRg1PVPrPEEinNHznSsM9AJRaS+2NZh6AtEt6fzfzAJAr6b09wrwDQD5p6O//ybwDQDq0xHkHiyJYrX79+uWNz5kzJ1asWFF03jlz5uSN1/cFqTHScA8ApdRS++KPf/zjeO6556JVq1Zx8803x5577lnukgBKKun9ffbs2SXNB5AWSe/vERHt27ev97U111yz6Lxbb7113vjcuXOLzgnQXNLQ37/uxRdfjHPPPbfueIMNNoihQ4eu9rw+ffrEk08+We8PzW688cZ45ZVXSlYnAKu30UYb1TvgPGPGjKLzVvrPEEinNHznSsM9AJRaS+2NZh6AtEt6fzfzAJAr6b09wrwDQD5p6O9fZ94BID1a4ryDRRGs1jrrrBPdu3fPidfW1sYnn3xSdN5Zs2bljW+//fZF56xPGu4BoJRaYl+89tpr4/rrr4+IiKuvvjoOO+ywMlcEUHotsb8DtARp6O8dOnSod3hi6dKlReet74eOy5YtKzonQHNJQ3//uh//+MdRW1tbd3zooYdG69atG3Rur1694h//+Eesu+66eV//7W9/W5IaAWi4LbfcMm98+vTpRef0d0yUQxq+c6XhHgBKrSX2RjMPQEvQEvs7QNqlobebdwDIlYb+/nXmHQDSpaXNO1gUQYNss802eePTpk0rKt+SJUvi008/zYmvt956sckmmxSVc3XScA8ApdSS+uLf/va3OO200yIi4oILLoiTTjqprPUANKWW1N8BWpI09Pc+ffrkjc+bN6/onN26dcsb79KlS9E5AZpTGvp7RMRTTz0VL730UlZs0KBBBeXo27dv3HvvvXmHLUaPHh2LFy9uVI0AFKbUn1ERER9//HFOrFWrVrHTTjsVnRMaIg3fudJwDwCl1pJ6o5kHoCVpSf0doKVIQ2837wCQKw39PcK8A0AatbR5B4siaJD9998/b/yDDz4oKt/UqVPzxgcMGFBUvoZIwz0AlFJL6YsvvPBCHH744bFy5co47bTT4txzzy1rPQBNraX0d4CWJg39fauttsobL/YeIiI6duyYN17fhnaASpOG/h4Rcdttt+XE6uv7q7LnnnvG+eefnxNfunRpjBs3rpjSAChSqT+jFi9eHLNnz86J9+vXr97v9VAqafjOlYZ7ACi1ltIbzTwALU1L6e8ALUkaert5B4BcaejvEeYdANKopc07WBRBgwwZMiRv/NVXXy0q3+TJk/PGBw8eXFS+hkjDPQCUUkvoixMmTIgDDjggvvjiizj66KPjyiuvLFstAM0lyf09k8mU5J+bbrqpoPwASZDk/v5vu+22W974hAkTis7Zvn37vPFiflgHUA5p6O8REc8++2xOrHv37kXlOuuss2L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",
      "text/plain": [
       "<Figure size 4200x1567.16 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(14, 14 / 2.68), ncols=2, nrows=2, constrained_layout=True, dpi=300\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 846,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name_a = [\n",
    "    \"ModelA\\n8DP\",\n",
    "    \"ModelA\\n8TP\",\n",
    "    \"ModelB\\n8TP\",\n",
    "    \"ModelC\\n8DP\",\n",
    "    \"ModelC\\n8TP\",\n",
    "    \"ModelD\\n8TP\",\n",
    "]\n",
    "labels_name_b = [\n",
    "    \"ModelA\\n16DP\",\n",
    "    \"ModelA\\n16TP\",\n",
    "    \"ModelB\\n16TP\",\n",
    "    \"ModelC\\n16DP\",\n",
    "    \"ModelC\\n16TP\",\n",
    "    \"ModelD\\n16TP\",\n",
    "]\n",
    "labels_name_c = [\n",
    "    \"ModelA\\n2DP$\\\\times$4TP\",\n",
    "    \"ModelA\\n4DP$\\\\times$2TP\",\n",
    "    \"ModelB\\n4DP$\\\\times$2TP\",\n",
    "    \"ModelC\\n2DP$\\\\times$4TP\",\n",
    "    \"ModelC\\n4DP$\\\\times$2TP\",\n",
    "    \"ModelD\\n2DP$\\\\times$4TP\",\n",
    "]\n",
    "labels_name_d = [\n",
    "    \"ModelA\\n15DP\",\n",
    "    \"ModelA\\n15TP\",\n",
    "    \"ModelB\\n15TP\",\n",
    "    \"ModelC\\n15DP\",\n",
    "    \"ModelC\\n15TP\",\n",
    "    \"ModelD\\n15TP\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 847,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MFU\n",
    "data_a = {\n",
    "    labels_name_a[0]: [41.0, 34.2, 44.4],  # 22.64\n",
    "    labels_name_a[1]: [26.2, 36.8, 43.6],  # 22.64\n",
    "    labels_name_a[2]: [30.1, 39.6, 49.4],  # 37\n",
    "    labels_name_a[3]: [0, 0, 0],  # 37\n",
    "    labels_name_a[4]: [0, 0, 0],  # 22.64\n",
    "    labels_name_a[5]: [0, 0, 0],  # 22.64\n",
    "}\n",
    "data_b = {\n",
    "    labels_name_b[0]: [0, 0, 0],  # 37\n",
    "    labels_name_b[1]: [0, 0, 0],  # 22.64\n",
    "    labels_name_b[2]: [0, 0, 0],  # 22.64\n",
    "    labels_name_b[3]: [0, 0, 0],  # 37\n",
    "    labels_name_b[4]: [0, 0, 0],  # 22.64\n",
    "    labels_name_b[5]: [0, 0, 0],  # 22.64\n",
    "}\n",
    "data_c = {\n",
    "    labels_name_c[0]: [37.1, 30.4, 44.6],  # 2DP 4TP\n",
    "    labels_name_c[1]: [40.4, 30.5, 44.7],  # 4DP 2TP\n",
    "    labels_name_c[2]: [-1, 31.7, 38.0],  #\n",
    "    labels_name_c[3]: [0, 0, 0],  # 37\n",
    "    labels_name_c[4]: [0, 0, 0],  # 22.64\n",
    "    labels_name_c[5]: [0, 0, 0],  # 22.64\n",
    "}\n",
    "data_d = {\n",
    "    labels_name_d[0]: [0, 0, 0],  # 37\n",
    "    labels_name_d[1]: [0, 0, 0],  # 22.64\n",
    "    labels_name_d[2]: [0, 0, 0],  # 22.64\n",
    "    labels_name_d[3]: [0, 0, 0],  # 37\n",
    "    labels_name_d[4]: [0, 0, 0],  # 22.64\n",
    "    labels_name_d[5]: [0, 0, 0],  # 22.64\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 848,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"DLRover-Lynx\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 849,
   "metadata": {},
   "outputs": [],
   "source": [
    "bar_width = 0.2\n",
    "group_spaing = 0.15\n",
    "\n",
    "group_positions = {}\n",
    "current_pos = 0\n",
    "\n",
    "x_label_cnt = len(data_a.keys())\n",
    "x_label_group_cnt = 3\n",
    "\n",
    "for idx in range(x_label_cnt):\n",
    "    group_positions[idx] = []\n",
    "    for _ in range(x_label_group_cnt):\n",
    "        group_positions[idx].append(current_pos)\n",
    "        current_pos += bar_width\n",
    "    current_pos += group_spaing\n",
    "\n",
    "group_centers = {}\n",
    "for idx, positions in group_positions.items():\n",
    "    group_centers[idx] = sum(positions) / len(positions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 850,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '(a) Single-node, single parallel')"
      ]
     },
     "execution_count": 850,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_set = set()\n",
    "for idx, (x_label, y_data) in enumerate(data_a.items()):\n",
    "    positions = group_positions[idx]\n",
    "    for i, (pos, value, color, edgecolor, hatch, label) in enumerate(\n",
    "        zip(\n",
    "            positions,\n",
    "            y_data,\n",
    "            colors,\n",
    "            edgecolors,\n",
    "            hatches,\n",
    "            legend_labels,\n",
    "        )\n",
    "    ):\n",
    "        if label in label_set:\n",
    "            local_label = None\n",
    "        else:\n",
    "            local_label = label\n",
    "            label_set.add(local_label)\n",
    "        ax[0][0].bar(\n",
    "            pos,\n",
    "            value,\n",
    "            width=bar_width,\n",
    "            color=color,\n",
    "            label=local_label,\n",
    "            hatch=hatch,\n",
    "            edgecolor=edgecolor,\n",
    "        )\n",
    "\n",
    "ax[0][0].set_xticks(list(group_centers.values()))\n",
    "ax[0][0].set_xticklabels(list(data_a.keys()))\n",
    "\n",
    "ax[0][0].set_ylim(0, 100)\n",
    "ax[0][0].set_yticks([0, 50, 100])\n",
    "ax[0][0].set_yticklabels([\"0\", \"50\", \"100\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax[0][0].tick_params(axis=\"x\", bottom=False, labelsize=g_label_fontsize, pad=1)\n",
    "ax[0][0].tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "\n",
    "ax[0][0].set_ylabel(\"MFU (%)\", fontsize=g_label_fontsize)\n",
    "ax[0][0].set_title(\"(a) Single-node, single parallel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 851,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '(b) Two-node, single parallel')"
      ]
     },
     "execution_count": 851,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for idx, (x_label, y_data) in enumerate(data_b.items()):\n",
    "    positions = group_positions[idx]\n",
    "    for i, (pos, value, color, edgecolor, hatch) in enumerate(\n",
    "        zip(\n",
    "            positions,\n",
    "            y_data,\n",
    "            colors,\n",
    "            edgecolors,\n",
    "            hatches,\n",
    "        )\n",
    "    ):\n",
    "        ax[0][1].bar(\n",
    "            pos,\n",
    "            value,\n",
    "            width=bar_width,\n",
    "            color=color,\n",
    "            hatch=hatch,\n",
    "            edgecolor=edgecolor,\n",
    "        )\n",
    "\n",
    "ax[0][1].set_xticks(list(group_centers.values()))\n",
    "ax[0][1].set_xticklabels(list(data_b.keys()))\n",
    "\n",
    "ax[0][1].set_ylim(0, 100)\n",
    "ax[0][1].set_yticks([0, 50, 100])\n",
    "ax[0][1].set_yticklabels([\"0\", \"50\", \"100\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax[0][1].tick_params(axis=\"x\", bottom=False, labelsize=g_label_fontsize, pad=1)\n",
    "ax[0][1].tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "\n",
    "ax[0][1].set_title(\"(b) Two-node, single parallel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 852,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '(c) Single-node, hybrid parallel')"
      ]
     },
     "execution_count": 852,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for idx, (x_label, y_data) in enumerate(data_c.items()):\n",
    "    positions = group_positions[idx]\n",
    "    for i, (pos, value, color, edgecolor, hatch) in enumerate(\n",
    "        zip(\n",
    "            positions,\n",
    "            y_data,\n",
    "            colors,\n",
    "            edgecolors,\n",
    "            hatches,\n",
    "        )\n",
    "    ):\n",
    "        if value == -1:\n",
    "            ax[1][0].text(\n",
    "                pos,\n",
    "                1,\n",
    "                \"OOM$\\\\times$\",\n",
    "                rotation=90,\n",
    "                ha=\"center\",\n",
    "                va=\"bottom\",\n",
    "                color=\"red\",\n",
    "            )\n",
    "        ax[1][0].bar(\n",
    "            pos,\n",
    "            value,\n",
    "            width=bar_width,\n",
    "            color=color,\n",
    "            label=local_label,\n",
    "            hatch=hatch,\n",
    "            edgecolor=edgecolor,\n",
    "        )\n",
    "\n",
    "ax[1][0].set_xticks(list(group_centers.values()))\n",
    "ax[1][0].set_xticklabels(list(data_c.keys()))\n",
    "\n",
    "ax[1][0].set_ylim(0, 100)\n",
    "ax[1][0].set_yticks([0, 50, 100])\n",
    "ax[1][0].set_yticklabels([\"0\", \"50\", \"100\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax[1][0].tick_params(axis=\"x\", bottom=False, labelsize=g_label_fontsize, pad=1)\n",
    "ax[1][0].tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "\n",
    "ax[1][0].set_ylabel(\"MFU (%)\", fontsize=g_label_fontsize)\n",
    "ax[1][0].set_title(\"(c) Single-node, hybrid parallel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 853,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '(d) Two-node, hybrid parallel')"
      ]
     },
     "execution_count": 853,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for idx, (x_label, y_data) in enumerate(data_d.items()):\n",
    "    positions = group_positions[idx]\n",
    "    for i, (pos, value, color, edgecolor, hatch) in enumerate(\n",
    "        zip(\n",
    "            positions,\n",
    "            y_data,\n",
    "            colors,\n",
    "            edgecolors,\n",
    "            hatches,\n",
    "        )\n",
    "    ):\n",
    "        ax[1][1].bar(\n",
    "            pos,\n",
    "            value,\n",
    "            width=bar_width,\n",
    "            color=color,\n",
    "            hatch=hatch,\n",
    "            edgecolor=edgecolor,\n",
    "        )\n",
    "\n",
    "ax[1][1].set_xticks(list(group_centers.values()))\n",
    "ax[1][1].set_xticklabels(list(data_d.keys()))\n",
    "\n",
    "ax[1][1].set_ylim(0, 100)\n",
    "ax[1][1].set_yticks([0, 50, 100])\n",
    "ax[1][1].set_yticklabels([\"0\", \"50\", \"100\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax[1][1].tick_params(axis=\"x\", bottom=False, labelsize=g_label_fontsize, pad=1)\n",
    "ax[1][1].tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "\n",
    "ax[1][1].set_title(\"(d) Two-node, hybrid parallel\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 854,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f64073264e0>"
      ]
     },
     "execution_count": 854,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.legend(\n",
    "    ncol=3,\n",
    "    loc=\"upper center\",\n",
    "    frameon=False,\n",
    "    shadow=False,\n",
    "    bbox_to_anchor=(0.5, 1.1),\n",
    "    fontsize=g_label_fontsize,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 855,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 4200x1567.16 with 4 Axes>"
      ]
     },
     "execution_count": 855,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.savefig(\"end_to_end_mfu.pdf\", bbox_inches=\"tight\", dpi=1000)\n",
    "fig"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.12.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}