paper_note/lynx/scalability.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import random\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": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2100x1050 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(7, 7 / 2), ncols=1, nrows=1, constrained_layout=True, dpi=300\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name_a = [\n",
    "    \"1-node\",\n",
    "    \"2-node\",\n",
    "    \"4-node\",\n",
    "    \"8-node\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MFU\n",
    "data_a = {\n",
    "    labels_name_a[0]: [40.1, 55.8, 62.4],\n",
    "    labels_name_a[1]: [39.6, 48.9, 55.2],\n",
    "    labels_name_a[2]: [38.2, 47.9, 54.0],\n",
    "    labels_name_a[3]: [38.1, 47.8, 53.2],\n",
    "}\n",
    "\n",
    "data_pa = []\n",
    "data_pb = []\n",
    "data_pc = []\n",
    "\n",
    "for v in data_a.values():\n",
    "    v[1] = v[0] * 0.82 if v[1] == 0 else v[1]\n",
    "    v[2] = v[0] * 1.2 if v[2] == 0 else v[2]\n",
    "    data_pa.append(v[0])\n",
    "    data_pb.append(v[1])\n",
    "    data_pc.append(v[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"DLRover-Lynx\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "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": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(13.333333333333346, 0.5, 'MFU (%)')"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "label_set = set()\n",
    "\n",
    "x_a = []\n",
    "x_b = []\n",
    "x_c = []\n",
    "\n",
    "for idx, (x_label, y_data) in enumerate(data_a.items()):\n",
    "    positions = group_positions[idx]\n",
    "    x_a.append(positions[0])\n",
    "    x_b.append(positions[1])\n",
    "    x_c.append(positions[2])\n",
    "\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",
    "\n",
    "        ax.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.set_xticks(list(group_centers.values()))\n",
    "ax.set_xticklabels(list(data_a.keys()))\n",
    "\n",
    "ax.set_ylim(0, 100)\n",
    "ax.set_yticks([0, 50, 100])\n",
    "ax.set_yticklabels([\"0\", \"50\", \"100\"], rotation=90, ha=\"center\", va=\"center\")\n",
    "\n",
    "ax.plot(x_a, data_pa, color=colors[0], marker=\"x\", linestyle=\"--\", alpha=0.68)\n",
    "ax.plot(x_b, data_pb, color=colors[1], marker=\"v\", linestyle=\"--\", alpha=0.68)\n",
    "ax.plot(x_c, data_pc, color=colors[2], marker=\"^\", linestyle=\"--\", alpha=0.68)\n",
    "\n",
    "\n",
    "ax.tick_params(axis=\"x\", bottom=False, labelsize=g_label_fontsize, pad=1)\n",
    "ax.tick_params(axis=\"y\", left=True, labelsize=g_label_fontsize, pad=5)\n",
    "ax.set_ylabel(\"MFU (%)\", fontsize=g_label_fontsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f15bdcd81a0>"
      ]
     },
     "execution_count": 125,
     "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, 0.97),\n",
    "    fontsize=g_label_fontsize,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2100x1050 with 1 Axes>"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.savefig(\"scalability.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
}