paper_note/lynx/scalability.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x840 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(\n",
    "    figsize=(14 / 3, 14 / 5), ncols=1, nrows=1, constrained_layout=True, dpi=300\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name_a = [\n",
    "    \"1-node\",\n",
    "    \"2-node\",\n",
    "    \"4-node\",\n",
    "    \"8-node\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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",
    "    data_pa.append(v[0])\n",
    "    data_pb.append(v[1])\n",
    "    data_pc.append(v[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"Lynx\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 13.333333333333332, 'The number of node')"
      ]
     },
     "execution_count": 7,
     "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, 110)\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)\n",
    "ax.set_xlabel(\"The number of node\", fontsize=g_label_fontsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f832d254b60>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig.legend(\n",
    "    ncol=1,\n",
    "    loc=\"upper center\",\n",
    "    frameon=False,\n",
    "    shadow=False,\n",
    "    fontsize=g_label_fontsize,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x840 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "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
}