paper_note/lynx/scalability.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 109,
   "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": 110,
   "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": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name_a = [\n",
    "    \"1-node\",\n",
    "    \"2-node\",\n",
    "    \"4-node\",\n",
    "    \"8-node\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"DLRover-Lynx\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "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": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(13.333333333333346, 0.5, 'MFU (%)')"
      ]
     },
     "execution_count": 115,
     "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": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f15bdc49d60>"
      ]
     },
     "execution_count": 116,
     "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": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2100x1050 with 1 Axes>"
      ]
     },
     "execution_count": 117,
     "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
}