Julia_Colab_Notebook_Template.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tQ1r1bbb0yBv"
      },
      "source": [
        "# <img src=\"https://github.com/JuliaLang/julia-logo-graphics/raw/master/images/julia-logo-color.png\" height=\"100\" /> _Colab Notebook Template_\n",
        "\n",
        "## Instructions\n",
        "1. Work on a copy of this notebook: _File_ > _Save a copy in Drive_ (you will need a Google account). Alternatively, you can download the notebook using _File_ > _Download .ipynb_, then upload it to [Colab](https://colab.research.google.com/).\n",
        "2. If you need a GPU: _Runtime_ > _Change runtime type_ > _Harware accelerator_ = _GPU_.\n",
        "3. Execute the following cell (click on it and press Ctrl+Enter) to install Julia, IJulia and other packages (if needed, update `JULIA_VERSION` and the other parameters). This takes a couple of minutes.\n",
        "4. Reload this page (press Ctrl+R, or ⌘+R, or the F5 key) and continue to the next section.\n",
        "\n",
        "_Notes_:\n",
        "* If your Colab Runtime gets reset (e.g., due to inactivity), repeat steps 2, 3 and 4.\n",
        "* After installation, if you want to change the Julia version or activate/deactivate the GPU, you will need to reset the Runtime: _Runtime_ > _Factory reset runtime_ and repeat steps 3 and 4."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GIeFXS0F0zww",
        "outputId": "060067e1-9494-4045-ffc7-d1ead0347458"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Installing Julia 1.8.2 on the current Colab Runtime...\n",
            "2022-11-02 02:02:18 URL:https://storage.googleapis.com/julialang2/bin/linux/x64/1.8/julia-1.8.2-linux-x86_64.tar.gz [135859273/135859273] -> \"/tmp/julia.tar.gz\" [1]\n",
            "Installing Julia package IJulia...\n",
            "Installing Julia package BenchmarkTools...\n",
            "Installing IJulia kernel...\n",
            "\u001b[36m\u001b[1m[ \u001b[22m\u001b[39m\u001b[36m\u001b[1mInfo: \u001b[22m\u001b[39mInstalling julia kernelspec in /root/.local/share/jupyter/kernels/julia-1.8\n",
            "\n",
            "Successfully installed julia version 1.8.2!\n",
            "Please reload this page (press Ctrl+R, ⌘+R, or the F5 key) then\n",
            "jump to the 'Checking the Installation' section.\n"
          ]
        },
        {
          "data": {
            "text/plain": []
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "%%shell\n",
        "set -e\n",
        "\n",
        "#---------------------------------------------------#\n",
        "JULIA_VERSION=\"1.10.4\" # any version ≥ 0.7.0\n",
        "JULIA_PACKAGES=\"IJulia BenchmarkTools\"\n",
        "JULIA_PACKAGES_IF_GPU=\"CUDA\" # or CuArrays for older Julia versions\n",
        "JULIA_NUM_THREADS=2\n",
        "#---------------------------------------------------#\n",
        "\n",
        "if [ -z `which julia` ]; then\n",
        "  # Install Julia\n",
        "  JULIA_VER=`cut -d '.' -f -2 <<< \"$JULIA_VERSION\"`\n",
        "  echo \"Installing Julia $JULIA_VERSION on the current Colab Runtime...\"\n",
        "  BASE_URL=\"https://julialang-s3.julialang.org/bin/linux/x64\"\n",
        "  URL=\"$BASE_URL/$JULIA_VER/julia-$JULIA_VERSION-linux-x86_64.tar.gz\"\n",
        "  wget -nv $URL -O /tmp/julia.tar.gz # -nv means \"not verbose\"\n",
        "  tar -x -f /tmp/julia.tar.gz -C /usr/local --strip-components 1\n",
        "  rm /tmp/julia.tar.gz\n",
        "\n",
        "  # Install Packages\n",
        "  nvidia-smi -L &> /dev/null && export GPU=1 || export GPU=0\n",
        "  if [ $GPU -eq 1 ]; then\n",
        "    JULIA_PACKAGES=\"$JULIA_PACKAGES $JULIA_PACKAGES_IF_GPU\"\n",
        "  fi\n",
        "  for PKG in `echo $JULIA_PACKAGES`; do\n",
        "    echo \"Installing Julia package $PKG...\"\n",
        "    julia -e 'using Pkg; pkg\"add '$PKG'; precompile;\"' &> /dev/null\n",
        "  done\n",
        "\n",
        "  # Install kernel and rename it to \"julia\"\n",
        "  echo \"Installing IJulia kernel...\"\n",
        "  julia -e 'using IJulia; IJulia.installkernel(\"julia\", env=Dict(\n",
        "      \"JULIA_NUM_THREADS\"=>\"'\"$JULIA_NUM_THREADS\"'\"))'\n",
        "  KERNEL_DIR=`julia -e \"using IJulia; print(IJulia.kerneldir())\"`\n",
        "  KERNEL_NAME=`ls -d \"$KERNEL_DIR\"/julia*`\n",
        "  mv -f $KERNEL_NAME \"$KERNEL_DIR\"/julia  \n",
        "\n",
        "  echo ''\n",
        "  echo \"Successfully installed `julia -v`!\"\n",
        "  echo \"Please reload this page (press Ctrl+R, ⌘+R, or the F5 key) then\"\n",
        "  echo \"jump to the 'Checking the Installation' section.\"\n",
        "fi"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-OS3Ac017T1i"
      },
      "source": [
        "# Checking the Installation\n",
        "The `versioninfo()` function should print your Julia version and some other info about the system:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EEzvvzCl1i0F",
        "outputId": "83182c30-bc48-4ed9-c41c-f70ee1b050b4"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Julia Version 1.8.2\n",
            "Commit 36034abf260 (2022-09-29 15:21 UTC)\n",
            "Platform Info:\n",
            "  OS: Linux (x86_64-linux-gnu)\n",
            "  CPU: 2 × Intel(R) Xeon(R) CPU @ 2.20GHz\n",
            "  WORD_SIZE: 64\n",
            "  LIBM: libopenlibm\n",
            "  LLVM: libLLVM-13.0.1 (ORCJIT, broadwell)\n",
            "  Threads: 2 on 2 virtual cores\n",
            "Environment:\n",
            "  LD_LIBRARY_PATH = /usr/local/nvidia/lib:/usr/local/nvidia/lib64\n",
            "  LD_PRELOAD = /usr/lib/x86_64-linux-gnu/libtcmalloc.so.4\n",
            "  JULIA_NUM_THREADS = 2\n"
          ]
        }
      ],
      "source": [
        "versioninfo()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YjM_qq54lCcs",
        "outputId": "93bd073d-8853-46be-d54f-65c7f1bf4d30"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "  465.359 ms (2 allocations: 32.00 MiB)\n"
          ]
        }
      ],
      "source": [
        "using BenchmarkTools\n",
        "\n",
        "M = rand(Float32, 2^11, 2^11)\n",
        "\n",
        "@btime $M * $M;"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XciCcMAJOT3_",
        "outputId": "56f8a755-0799-4243-9277-7dea10fad14a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "No GPU found.\n"
          ]
        }
      ],
      "source": [
        "try\n",
        "    using CUDA\n",
        "catch\n",
        "    println(\"No GPU found.\")\n",
        "else\n",
        "    run(`nvidia-smi`)\n",
        "    # Copy the data to the GPU. Creates a CuArray:\n",
        "    M_on_gpu = cu(M)\n",
        "\n",
        "    # Alternatively, create a new random matrix directly on the GPU:\n",
        "    # M_on_gpu = CUDA.rand(Float32, 2^11, 2^11)\n",
        "\n",
        "    @btime CUDA.@sync $M_on_gpu * $M_on_gpu\n",
        "    nothing\n",
        "end"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8RC1QNNqk6h1"
      },
      "source": [
        "# Need Help?\n",
        "\n",
        "* Learning: https://julialang.org/learning/\n",
        "* Documentation: https://docs.julialang.org/\n",
        "* Questions & Discussions:\n",
        "  * https://discourse.julialang.org/\n",
        "  * http://julialang.slack.com/\n",
        "  * https://stackoverflow.com/questions/tagged/julia\n",
        "\n",
        "If you ever ask for help or file an issue about Julia, you should generally provide the output of `versioninfo()`."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2UMidUQB03vJ"
      },
      "source": [
        "Add new code cells by clicking the `+ Code` button (or _Insert_ > _Code cell_).\n",
        "\n",
        "Have fun!\n",
        "\n",
        "<img src=\"https://raw.githubusercontent.com/JuliaLang/julia-logo-graphics/master/images/julia-logo-mask.png\" height=\"100\" />"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "provenance": []
    },
    "gpuClass": "standard",
    "kernelspec": {
      "display_name": "Julia",
      "language": "julia",
      "name": "julia"
    },
    "language_info": {
      "file_extension": ".jl",
      "mimetype": "application/julia",
      "name": "julia"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}