paper_note/lynx/scalability.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 28,
   "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": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels_name_a = [\n",
    "    \"1-node\",\n",
    "    \"2-node\",\n",
    "    \"4-node\",\n",
    "    \"8-node\",\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# MFU\n",
    "data_a = {\n",
    "    labels_name_a[0]: [40.6, 0, 0],\n",
    "    labels_name_a[1]: [40.6, 0, 0],\n",
    "    labels_name_a[2]: [40.5, 0, 0],\n",
    "    labels_name_a[3]: [40.5, 0, 0],\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\n",
    "    v[2] = v[0] * 1.2\n",
    "    data_pa.append(v[0])\n",
    "    data_pb.append(v[1])\n",
    "    data_pc.append(v[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "legend_labels = [\"Megatron-LM\", \"XLA\", \"DLRover-Lynx\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(13.333333333333346, 0.5, 'MFU (%)')"
      ]
     },
     "execution_count": 34,
     "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": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f5cdc7d7770>"
      ]
     },
     "execution_count": 35,
     "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": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2100x1050 with 1 Axes>"
      ]
     },
     "execution_count": 36,
     "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
}