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gisbi-kim/cuda-pin-vs-unpin-experiment.ipynb

Created July 21, 2023 15:41
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  1. Giseop Kim revised this gist Jul 21, 2023. 1 changed file with 12 additions and 1 deletion.
    13 changes: 12 additions & 1 deletion cuda-pin-vs-unpin-experiment.ipynb
    View file
    Original file line number Diff line number Diff line change
    @@ -5,7 +5,8 @@
    "colab": {
    "provenance": [],
    "gpuType": "T4",
    "authorship_tag": "ABX9TyMo6+Dp4M/ww06pQl4GAMDO"
    "authorship_tag": "ABX9TyMo6+Dp4M/ww06pQl4GAMDO",
    "include_colab_link": true
    },
    "kernelspec": {
    "name": "python3",
    @@ -17,6 +18,16 @@
    "accelerator": "GPU"
    },
    "cells": [
    {
    "cell_type": "markdown",
    "metadata": {
    "id": "view-in-github",
    "colab_type": "text"
    },
    "source": [
    "<a href=\"https://colab.research.google.com/gist/gisbi-kim/1c422d42261e270d9fbbc1a6ed0730c0/cuda-pin-vs-unpin-experiment.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
    ]
    },
    {
    "cell_type": "code",
    "source": [
  2. Giseop Kim created this gist Jul 21, 2023.
    305 changes: 305 additions & 0 deletions cuda-pin-vs-unpin-experiment.ipynb
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    Original file line number Diff line number Diff line change
    @@ -0,0 +1,305 @@
    {
    "nbformat": 4,
    "nbformat_minor": 0,
    "metadata": {
    "colab": {
    "provenance": [],
    "gpuType": "T4",
    "authorship_tag": "ABX9TyMo6+Dp4M/ww06pQl4GAMDO"
    },
    "kernelspec": {
    "name": "python3",
    "display_name": "Python 3"
    },
    "language_info": {
    "name": "python"
    },
    "accelerator": "GPU"
    },
    "cells": [
    {
    "cell_type": "code",
    "source": [
    "import torch\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import GPUtil\n",
    "\n",
    "torch.cuda.empty_cache()\n",
    "\n",
    "ks = [1, 5, 10, 50, 100, 500, 1000, 2500, 5000, 7500, 10000, 12500, 15000, 17500, 20000, 22500]\n",
    "times_without_pinning = []\n",
    "times_with_pinning = []\n",
    "times_generate_without_pinning = []\n",
    "times_generate_with_pinning = []\n",
    "device = torch.device('cuda')\n",
    "\n",
    "for k in ks:\n",
    " # Non-pinned memory\n",
    " start = time.time()\n",
    " large_tensor = torch.ones((k, k))\n",
    " end = time.time()\n",
    " elapsed = end - start\n",
    " times_generate_without_pinning.append(elapsed)\n",
    " print(f\"Non-Pinned memory generating time for k={k}: {elapsed:.5f} sec\")\n",
    "\n",
    " start = time.time()\n",
    " gpu_memory = large_tensor.to(device)\n",
    " torch.cuda.synchronize() # Ensure the copy is completed\n",
    " end = time.time()\n",
    " elapsed = end - start\n",
    " times_without_pinning.append(elapsed)\n",
    " print(f\"Without pinning for k={k}: {elapsed:.5f} seconds\")\n",
    " del large_tensor, gpu_memory\n",
    " GPUtil.showUtilization()\n",
    "\n",
    " # Pinned memory\n",
    " start = time.time()\n",
    " large_tensor_pinned = torch.ones((k, k), pin_memory=True)\n",
    " end = time.time()\n",
    " elapsed = end - start\n",
    " times_generate_with_pinning.append(elapsed)\n",
    " print(f\"\\nPinned memory generating time for k={k}: {end - start:.5f} sec\")\n",
    "\n",
    " start = time.time()\n",
    " gpu_memory_pinned = large_tensor_pinned.to(device, non_blocking=True)\n",
    " torch.cuda.synchronize() # Ensure the copy is completed\n",
    " end = time.time()\n",
    " elapsed = end - start\n",
    " times_with_pinning.append(elapsed)\n",
    " print(f\"With pinning for k={k}: {elapsed:.5f} seconds\")\n",
    " del large_tensor_pinned, gpu_memory_pinned\n",
    " GPUtil.showUtilization()\n",
    "\n",
    "# Plot the results\n",
    "plt.figure(figsize=(10, 6))\n",
    "\n",
    "# Plotting memory generation times\n",
    "plt.plot(ks, times_generate_without_pinning, '--', label='Memory Generation without pinning', color='tab:blue')\n",
    "plt.plot(ks, times_generate_with_pinning, '--', label='Memory Generation with pinning', color='tab:orange')\n",
    "\n",
    "# Plotting tensor copy times\n",
    "plt.plot(ks, times_without_pinning, label='Without pinning', color='tab:blue')\n",
    "plt.plot(ks, times_with_pinning, label='With pinning', color='tab:orange')\n",
    "\n",
    "plt.legend()\n",
    "plt.xlabel('Size of tensor (k x k)')\n",
    "plt.ylabel('Time (seconds)')\n",
    "plt.title('Time to generate and copy tensor to GPU with and without pinning')\n",
    "plt.show()\n"
    ],
    "metadata": {
    "colab": {
    "base_uri": "https://localhost:8080/",
    "height": 1000
    },
    "id": "yVhbsZIMGAgc",
    "outputId": "3313924a-6202-4798-db1a-38d0b4a61beb"
    },
    "execution_count": 18,
    "outputs": [
    {
    "output_type": "stream",
    "name": "stdout",
    "text": [
    "Non-Pinned memory generating time for k=1: 0.00008 sec\n",
    "Without pinning for k=1: 0.00093 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 1% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=1: 0.00011 sec\n",
    "With pinning for k=1: 0.00022 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 1% | 1% |\n",
    "Non-Pinned memory generating time for k=5: 0.00008 sec\n",
    "Without pinning for k=5: 0.00020 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 1% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=5: 0.00012 sec\n",
    "With pinning for k=5: 0.00018 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 1% | 1% |\n",
    "Non-Pinned memory generating time for k=10: 0.00009 sec\n",
    "Without pinning for k=10: 0.00198 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 1% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=10: 0.00011 sec\n",
    "With pinning for k=10: 0.00022 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 1% | 1% |\n",
    "Non-Pinned memory generating time for k=50: 0.00009 sec\n",
    "Without pinning for k=50: 0.00022 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=50: 0.00012 sec\n",
    "With pinning for k=50: 0.00658 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "Non-Pinned memory generating time for k=100: 0.00010 sec\n",
    "Without pinning for k=100: 0.00024 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=100: 0.00141 sec\n",
    "With pinning for k=100: 0.00106 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "Non-Pinned memory generating time for k=500: 0.00023 sec\n",
    "Without pinning for k=500: 0.00334 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=500: 0.00175 sec\n",
    "With pinning for k=500: 0.00021 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "Non-Pinned memory generating time for k=1000: 0.00060 sec\n",
    "Without pinning for k=1000: 0.01037 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=1000: 0.00168 sec\n",
    "With pinning for k=1000: 0.00047 seconds\n",
    "| ID | GPU | MEM |\n",
    "-------------------\n",
    "| 0 | 100% | 1% |\n",
    "Non-Pinned memory generating time for k=2500: 0.00511 sec\n",
    "Without pinning for k=2500: 0.00680 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 59% | 1% |\n",
    "\n",
    "Pinned memory generating time for k=2500: 0.00476 sec\n",
    "With pinning for k=2500: 0.00269 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 59% | 1% |\n",
    "Non-Pinned memory generating time for k=5000: 0.08405 sec\n",
    "Without pinning for k=5000: 0.02597 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 7% | 2% |\n",
    "\n",
    "Pinned memory generating time for k=5000: 0.01543 sec\n",
    "With pinning for k=5000: 0.01063 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 7% | 2% |\n",
    "Non-Pinned memory generating time for k=7500: 0.13757 sec\n",
    "Without pinning for k=7500: 0.05257 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 5% | 3% |\n",
    "\n",
    "Pinned memory generating time for k=7500: 0.03040 sec\n",
    "With pinning for k=7500: 0.02247 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 5% | 3% |\n",
    "Non-Pinned memory generating time for k=10000: 0.24703 sec\n",
    "Without pinning for k=10000: 0.09248 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 0% | 6% |\n",
    "\n",
    "Pinned memory generating time for k=10000: 0.04954 sec\n",
    "With pinning for k=10000: 0.03800 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 17% | 6% |\n",
    "Non-Pinned memory generating time for k=12500: 0.38572 sec\n",
    "Without pinning for k=12500: 0.15839 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 20% | 9% |\n",
    "\n",
    "Pinned memory generating time for k=12500: 0.08153 sec\n",
    "With pinning for k=12500: 0.05746 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 34% | 9% |\n",
    "Non-Pinned memory generating time for k=15000: 0.44358 sec\n",
    "Without pinning for k=15000: 0.20067 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 26% | 15% |\n",
    "\n",
    "Pinned memory generating time for k=15000: 0.10763 sec\n",
    "With pinning for k=15000: 0.07887 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 14% | 15% |\n",
    "Non-Pinned memory generating time for k=17500: 0.58884 sec\n",
    "Without pinning for k=17500: 0.27370 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 22% | 23% |\n",
    "\n",
    "Pinned memory generating time for k=17500: 0.14726 sec\n",
    "With pinning for k=17500: 0.10651 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 39% | 23% |\n",
    "Non-Pinned memory generating time for k=20000: 0.74188 sec\n",
    "Without pinning for k=20000: 0.35279 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 39% | 33% |\n",
    "\n",
    "Pinned memory generating time for k=20000: 0.18881 sec\n",
    "With pinning for k=20000: 0.13755 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 25% | 33% |\n",
    "Non-Pinned memory generating time for k=22500: 0.91399 sec\n",
    "Without pinning for k=22500: 0.46183 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 36% | 45% |\n",
    "\n",
    "Pinned memory generating time for k=22500: 0.22889 sec\n",
    "With pinning for k=22500: 0.17159 seconds\n",
    "| ID | GPU | MEM |\n",
    "------------------\n",
    "| 0 | 34% | 45% |\n"
    ]
    },
    {
    "output_type": "display_data",
    "data": {
    "text/plain": [
    "<Figure size 1000x600 with 1 Axes>"
    ],
    "image/png": 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\n"
    },
    "metadata": {}
    }
    ]
    },
    {
    "cell_type": "code",
    "source": [],
    "metadata": {
    "id": "GSVKskTUGgMg"
    },
    "execution_count": 15,
    "outputs": []
    }
    ]
    }