diff --git a/ipynb/utils/energy_model_example.ipynb b/ipynb/utils/energy_model_example.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..b0cf5e07ca60ce53f942fa388590d3ef723f7969
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+++ b/ipynb/utils/energy_model_example.ipynb
@@ -0,0 +1,134 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from __future__ import division\n",
+    "from scipy.interpolate import spline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# \n",
+    "# Use Juno's energy model as example, platform only need modify\n",
+    "# energy_model structure to verify energy model is reasonable or not\n",
+    "#\n",
+    "energy_model = {\n",
+    "    'cluster_0' : {\n",
+    "        'label'    : np.array(['450MHz(L)', '575MHz(L)', '700MHz(L)', '775MHz(L)', '850Mhz(L)']),\n",
+    "        'capacity' : np.array([235, 302, 368, 406, 447]),\n",
+    "        'energy'   : np.array([33, 46, 61, 76, 93]),\n",
+    "    },\n",
+    "    \n",
+    "    'cluster_1' : {\n",
+    "        'label'    : np.array(['450MHz(B)', '625MHz(B)', '800MHz(B)', '950MHz(B)', '1100Mhz(B)']),\n",
+    "        'capacity' : np.array([417, 579, 744, 883, 1024]),\n",
+    "        'energy'   : np.array([168, 251, 359, 479, 616]),\n",
+    "    },\n",
+    "}\n",
+    "\n",
+    "# set plot size\n",
+    "plt.figure(figsize=(12,6), dpi=80)\n",
+    "\n",
+    "plt.subplot(211)\n",
+    "\n",
+    "# plot for power efficiency\n",
+    "xlable_range = np.array([])\n",
+    "xlable = np.array([])\n",
+    "core_range = np.array([])\n",
+    "range_base = 1\n",
+    "for key in energy_model:\n",
+    "    xlable_range = np.append(xlable_range, np.array(range(len(energy_model[key]['label']))) + range_base)\n",
+    "    xlable = np.append(xlable, energy_model[key]['label'])\n",
+    "    core_range = np.array(range(len(energy_model[key]['label']))) + range_base\n",
+    "    \n",
+    "    energy_model[key]['efficiency'] = energy_model[key]['energy'] / energy_model[key]['capacity']\n",
+    "    x_sm = np.array(core_range)\n",
+    "    x_smooth = np.linspace(x_sm.min(), x_sm.max(), 200)\n",
+    "    y_smooth = spline(core_range, energy_model[key]['efficiency'], x_smooth)\n",
+    "    plt.plot(x_smooth, y_smooth, color=\"green\", linewidth=3, linestyle=\"-\", label=key)\n",
+    "    plt.plot(core_range, energy_model[key]['efficiency'], 'go')\n",
+    "    range_base += len(energy_model[key]['label']) + 1\n",
+    "\n",
+    "plt.xticks(xlable_range, xlable)\n",
+    "\n",
+    "plt.legend(loc='upper left', frameon=False)\n",
+    "\n",
+    "plt.xlim(0, 12)\n",
+    "plt.ylim(0.1, 0.7)\n",
+    "plt.xlabel('CPU OPPs')\n",
+    "plt.ylabel('CPU Power Efficiency')\n",
+    "\n",
+    "plt.subplot(212)\n",
+    "\n",
+    "# plot for cpu's capacity\n",
+    "core_range = np.array([])\n",
+    "range_base = 1\n",
+    "for key in energy_model:\n",
+    "    core_range = np.array(range(len(energy_model[key]['label']))) + range_base\n",
+    "    range_base += len(energy_model[key]['label']) + 1\n",
+    "    x_sm = np.array(core_range)\n",
+    "    x_smooth = np.linspace(x_sm.min(), x_sm.max(), 200)\n",
+    "    y_smooth = spline(core_range, energy_model[key]['capacity'], x_smooth)\n",
+    "    plt.plot(x_smooth, y_smooth, color=\"green\", linewidth=3, linestyle=\"-\", label=key)\n",
+    "    plt.plot(core_range, energy_model[key]['capacity'], 'go')\n",
+    "\n",
+    "plt.xticks(xlable_range, xlable)\n",
+    "\n",
+    "plt.legend(loc='upper left', frameon=False)\n",
+    "\n",
+    "plt.xlim(0, 12)\n",
+    "plt.ylim(0, 1100)\n",
+    "plt.xlabel('CPU OPPs')\n",
+    "plt.ylabel('CPU Capacity')\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}