OpenJij/OpenJij

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docs/tutorial/ja/005-benchmark_sparse_dense.ipynb

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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# OpenJijにおける相互作用行列の保持の仕方\n",
    "解きたい問題によって、イジングハミルトニアンの相互作用行列$J$やQUBOの相互作用行列$Q$に含まれる非ゼロの要素数は大きく変化します。\n",
    "実問題の多くでは、相互作用行列の中の非ゼロの要素数は比較的少なく疎な行列であることが多いです。\n",
    "そこで、OpenJijでは、デフォルトでは内部で相互作用係数を疎行列として保持するようになっています。\n",
    "ですが、解きたい問題によっては必ずしも疎行列であるというわけではありません。\n",
    "この場合には、疎行列形式のデータ保持では計算速度が低下してしまいます。\n",
    "この点を解決するために、OpenJijは、ユーザーが自分で行列保持の仕方を制御できるパラメータである`sparse`が用意されています。\n",
    "このチュートリアルでは、この`sparse`の使い方を説明し、疎行列でデータを保持した場合と密行列でデータを保持した場合の速度を比較してみます。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import openjij as oj\n",
    "import numpy as np\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "データの内部保持の仕方は、次のように設定することができます。\n",
    "```python\n",
    "sampler = oj.SASampler()\n",
    "response = sampler.sample_ising(h, J, sparse = True)\n",
    "```\n",
    "ここで、`sparse = True`とすると内部の相互作用行列のデータ保持の仕方が疎行列になります。現在のOpenJijでは、デフォルトで`sparse = True`となっています(2022/10 現在 (v0.6.5))。\n",
    "このフラグを\n",
    "```python\n",
    "response = sampler.sample_ising(h, J, sparse = False)\n",
    "```\n",
    "のようにすると、内部でのデータ保持の仕方を密行列にすることができます。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sparseモードとdenseモードでの実行速度の比較\n",
    "次に、データ保持の仕方を変化することで実行速度にどのように違いが出るかを検証してみます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "NUM_READS = 1\n",
    "\n",
    "BETA_MAX = 14000000\n",
    "BETA_MIN = 0.0015\n",
    "\n",
    "num_spins = [100,200,500,1000,2000,5000]\n",
    "p_list = [0.1,0.3,0.5,0.8]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ここでは、外場のないSherrington-Kirkpatrick模型を変形させた用いてベンチマークを取りたいと思います、\n",
    "外場のないSherrington-Kirkpatrick(SK)模型は、次のようなハミルトニアンを持つ模型です。\n",
    "\n",
    "$$ H = \\frac{1}{N}\\sum_{ij} J_{ij} \\sigma_i \\sigma_j,\\\\ \\ J_{ij} \\sim \\mathcal{N}(0,1), J_{ij} = J_{ji}$$\n",
    "\n",
    "ここで、$\\mathcal{N}(0,1)$は平均0、分散1のランダムガウスノイズです。\n",
    "SK模型では全ての要素がランダム分布に従っていますが、ここでは、相互作用行列$J$に入っている要素の割合を変化させていき、相互作用を疎にしていくことで、計算時間がどのように変化するかを調べます。\n",
    "\n",
    "まず、初めにランダムな相互作用を作ります。ここで、パラメータはスピン数$n$と相互作用行列$J$に入っている要素の割合$p$です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_random_interaction(n,p):\n",
    "    h,J = {},{}\n",
    "    for i in range(n-1):\n",
    "        for j in range(i+1, n):\n",
    "            if np.random.random() <= p:\n",
    "                # OpenJijでは、上三角行列の形でデータを保持している。\n",
    "                J[i, j] = np.random.normal(0, 1) / np.sqrt(n)\n",
    "\n",
    "    return J,h"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最初に密行列を用いた場合を計算してみます。\n",
    "ここでは、スピン数を$n=100,200,500,1000,2000,5000$と変化させ、相互作用行列$J$に入っている要素の割合$p$も$p=0.1,0.3,0.5,0.8$と変化させます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OpenJij Dense\n",
      "p = 0.1, n = 100 : \telapsed_time:0.02439586600007715[sec]\n",
      "p = 0.1, n = 200 : \telapsed_time:0.04425178099995719[sec]\n",
      "p = 0.1, n = 500 : \telapsed_time:0.07739514899992628[sec]\n",
      "p = 0.1, n = 1000 : \telapsed_time:0.2425712609999664[sec]\n",
      "p = 0.1, n = 2000 : \telapsed_time:1.6797769239999525[sec]\n",
      "p = 0.1, n = 5000 : \telapsed_time:13.506819940000014[sec]\n",
      "p = 0.3, n = 100 : \telapsed_time:0.006876676999922893[sec]\n",
      "p = 0.3, n = 200 : \telapsed_time:0.0159878800000115[sec]\n",
      "p = 0.3, n = 500 : \telapsed_time:0.07934188900003392[sec]\n",
      "p = 0.3, n = 1000 : \telapsed_time:0.3215275050000628[sec]\n",
      "p = 0.3, n = 2000 : \telapsed_time:2.319988950000038[sec]\n",
      "p = 0.3, n = 5000 : \telapsed_time:15.02982138099992[sec]\n",
      "p = 0.5, n = 100 : \telapsed_time:0.007885184999963712[sec]\n",
      "p = 0.5, n = 200 : \telapsed_time:0.020288821000008284[sec]\n",
      "p = 0.5, n = 500 : \telapsed_time:0.10879908200001864[sec]\n",
      "p = 0.5, n = 1000 : \telapsed_time:0.41148077200000444[sec]\n",
      "p = 0.5, n = 2000 : \telapsed_time:2.1696542160000263[sec]\n",
      "p = 0.5, n = 5000 : \telapsed_time:17.148261606999995[sec]\n",
      "p = 0.8, n = 100 : \telapsed_time:0.010947117999990041[sec]\n",
      "p = 0.8, n = 200 : \telapsed_time:0.02529107300006217[sec]\n",
      "p = 0.8, n = 500 : \telapsed_time:0.14675048200001584[sec]\n",
      "p = 0.8, n = 1000 : \telapsed_time:0.565918201000045[sec]\n",
      "p = 0.8, n = 2000 : \telapsed_time:2.900591609999992[sec]\n",
      "p = 0.8, n = 5000 : \telapsed_time:20.427944155999967[sec]\n"
     ]
    }
   ],
   "source": [
    "# Benchmark OpenJij Dense\n",
    "print('OpenJij Dense')\n",
    "sampler = oj.SASampler()\n",
    "openjij_dense_time = []\n",
    "openjij_dense_energy = []\n",
    "\n",
    "for p in p_list:\n",
    "    for n in num_spins:\n",
    "        J,h = create_random_interaction(n,p)\n",
    "        start = time.perf_counter()\n",
    "        response = sampler.sample_ising(h, J, num_sweeps=1000, num_reads=NUM_READS, beta_max=BETA_MAX, beta_min=BETA_MIN,sparse = False)\n",
    "        elapsed_time = time.perf_counter() - start\n",
    "\n",
    "        openjij_dense_time.append(elapsed_time)\n",
    "        openjij_dense_energy.append(np.mean(response.energies))\n",
    "\n",
    "        print(f\"p = {p}, n = {n} : \\telapsed_time:{elapsed_time}[sec]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "次に、疎行列を用いた場合を検証します。実行条件は密行列の場合と同様です。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OpenJij Sparse\n",
      "p = 0.1, n = 100 : \telapsed_time:0.018858227999999144[sec]\n",
      "p = 0.1, n = 200 : \telapsed_time:0.011375076999911471[sec]\n",
      "p = 0.1, n = 500 : \telapsed_time:0.040720876000023054[sec]\n",
      "p = 0.1, n = 1000 : \telapsed_time:0.1434848740000234[sec]\n",
      "p = 0.1, n = 2000 : \telapsed_time:0.5859196809999503[sec]\n",
      "p = 0.1, n = 5000 : \telapsed_time:4.693539175000069[sec]\n",
      "p = 0.3, n = 100 : \telapsed_time:0.008090091999974902[sec]\n",
      "p = 0.3, n = 200 : \telapsed_time:0.01928631900000255[sec]\n",
      "p = 0.3, n = 500 : \telapsed_time:0.09923592899986033[sec]\n",
      "p = 0.3, n = 1000 : \telapsed_time:0.3975637910000387[sec]\n",
      "p = 0.3, n = 2000 : \telapsed_time:1.9902634820000458[sec]\n",
      "p = 0.3, n = 5000 : \telapsed_time:14.41226490400004[sec]\n",
      "p = 0.5, n = 100 : \telapsed_time:0.010653709000052913[sec]\n",
      "p = 0.5, n = 200 : \telapsed_time:0.02600566599994636[sec]\n",
      "p = 0.5, n = 500 : \telapsed_time:0.16183085200009373[sec]\n",
      "p = 0.5, n = 1000 : \telapsed_time:0.6748764890000984[sec]\n",
      "p = 0.5, n = 2000 : \telapsed_time:3.276416020999932[sec]\n",
      "p = 0.5, n = 5000 : \telapsed_time:21.87782676500001[sec]\n",
      "p = 0.8, n = 100 : \telapsed_time:0.014087553000081243[sec]\n",
      "p = 0.8, n = 200 : \telapsed_time:0.03917992299989237[sec]\n",
      "p = 0.8, n = 500 : \telapsed_time:0.24562845499985997[sec]\n",
      "p = 0.8, n = 1000 : \telapsed_time:1.0560938139999507[sec]\n",
      "p = 0.8, n = 2000 : \telapsed_time:5.183320384999888[sec]\n",
      "p = 0.8, n = 5000 : \telapsed_time:33.83915293400014[sec]\n"
     ]
    }
   ],
   "source": [
    "# Benchmark OpenJij Sparse\n",
    "print('OpenJij Sparse')\n",
    "sampler = oj.SASampler()\n",
    "openjij_sparse_time = []\n",
    "openjij_sparse_energy = []\n",
    "for p in p_list:\n",
    "    for n in num_spins:\n",
    "        J,h = create_random_interaction(n,p)\n",
    "        start = time.perf_counter()\n",
    "        response = sampler.sample_ising(h, J, num_sweeps=1000, num_reads=NUM_READS, beta_max=BETA_MAX, beta_min=BETA_MIN, sparse=True)\n",
    "        elapsed_time = time.perf_counter() - start\n",
    "\n",
    "        openjij_sparse_time.append(elapsed_time)\n",
    "        openjij_sparse_energy.append(np.mean(response.energies))\n",
    "\n",
    "        print(f\"p = {p}, n = {n} : \\telapsed_time:{elapsed_time}[sec]\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "密行列と疎行列の場合で得られた結果を比較するために、プロットしてみます。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = plt.figure(figsize=(10,6))\n",
    "sparse_time = np.array(openjij_sparse_time).reshape(len(p_list),-1)\n",
    "dense_time = np.array(openjij_dense_time).reshape(len(p_list),-1)\n",
    "color_list = [\"blue\", \"red\", \"green\", \"orange\"]\n",
    "for index,p in enumerate(p_list):\n",
    "    plt.plot(num_spins,dense_time[index], '-o', label=f'dense $p$ ={p}',color = color_list[index],markersize=8)\n",
    "    plt.plot(num_spins,sparse_time[index], '-^', label=f'sparse $p$ ={p}',color = color_list[index],markersize=8)\n",
    "plt.xscale(\"log\")\n",
    "plt.yscale(\"log\")\n",
    "plt.xlabel('number of spins',fontsize=18)\n",
    "plt.ylabel('time [sec]',fontsize=18)\n",
    "plt.legend(fontsize=12, ncol = 4, bbox_to_anchor=(0.7, 0.7, 0.3, 0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相互作用行列の中に詰められている要素の割合が$p=0.1$の場合には、`sparse=True`とした疎行列の場合の方が密行列の場合に比べて数倍早いことがわかります。\n",
    "しかし、$p=0.3$程度になるとおおよそ両者の速度は同程度になります。\n",
    "さらに、相互作用行列の中に詰められている要素の割合が$p=0.5,0.8$では密行列を用いる方が速いことがわかりました。\n",
    "このように、疎行列、密行列のどちらを用いるかで実行速度が変化することがわかります。\n",
    "ですので、扱う問題に合わせて適切に切り替えることで、より速く結果を得ることができるようになります。"
   ]
  }
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