Julia in Google Colab

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I am trying to setup Julia with Google Colab. Installation instructions as in https://discourse.julialang.org/t/julia-on-google-colab-free-gpu-accelerated-shareable-notebooks/15319 have been followed. Despite that, I am unable to launch Julia.

I am trying to use Julia with Google Colab. I followed the following steps:

  1. Install CUDA
!wget https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb
!dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64-deb
!apt-key add /var/cuda-repo-9-0-local/7fa2af80.pub
!apt update -q
!apt install cuda gcc-6 g++-6 -y -q
!ln -s /usr/bin/gcc-6 /usr/local/cuda/bin/gcc
!ln -s /usr/bin/g++-6 /usr/local/cuda/bin/g++
  1. Install Julia 1.2.0
!curl -sSL "https://julialang-s3.julialang.org/bin/linux/x64/1.2/julia-1.2.0-linux-x86_64.tar.gz" -o julia.tar.gz
!tar -xzf julia.tar.gz -C /usr --strip-components 1
!rm -rf julia.tar.gz*
!julia -e 'using Pkg; pkg"add IJulia; add CuArrays; add Flux; precompile"'

The above two steps run perfectly fine. I am unable to initiate a Julia session. I tried:

!julia

With this, the Julia start-up screen keeps showing with no command-line.


Turns out that it was just the sequence of steps that was wrong. Very helpful video posted https://www.youtube.com/watch?v=xpZo3L2dYTY. Just to reiterate:

  1. Save the following as .ipynb file, and upload it on Google Colab:
{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Julia on Colab.ipynb",
      "version": "0.3.2",
      "provenance": []
    },
    "kernelspec": {
      "name": "julia-1.2",
      "display_name": "Julia 1.2"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "metadata": {
        "id": "oMSuTc3pDlHv",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}
  1. Install CUDA in the same notebook using the commands mentioned in the question.
  2. Install Julia 1.2.0 in the same notebook using the commands mentioned above.
  3. Configure the settings as demonstrated in the video and you are all set!

Julia in Google Colab, Turns out that it was just the sequence of steps that was wrong. Very helpful video posted https://www.youtube.com/watch?v=xpZo3L2dYTY. I am trying to setup Julia with Google Colab. Installation instructions as in https:


In addition to the answer by user3856486: you can now skip the CUDA installation step (mentioned here). That saves a lot of time, especially since you have to rerun these steps whenever you close the notebook/the runtime disconnects.

How to run Julia on Google Colab - Uday Yadav, From here, you have 2 options. Utilize Colab's GPU; Just run on CPU. Just using CPU. Create a file with .ipynb extension and paste the� For Pythonic data-scientists, Google Colab is definitely not a new concept or product. Google Colab is an entirely new IPython notebook with a virtual kernel as a frontend for computation on Google’s servers. Colab is also free, which puts it ahead of similar services. To top it all off, Colab has Google integration, and absolutely no setup.


The easiest option is to use this Colab notebook template.

It supports any Julia version, and also has GPU support.

How to Install Julia Programming Language in Google Colab , Julia is a great language that is up and coming in the statistical computing place. Julia is actually very commonly used by biologists, medical� This notebook is open with private outputs. Outputs will not be saved. You can disable this in Notebook settings


Julia Box: Google Colab for Julia | by Emmett Boudreau, In order to proceed, we need to download and install, the custom branch of julia into the container used by the colaboratory backend. Please note the colab� A notebook for running Julia 1.3.1 on Google Colab using the IJulia package. Why? When I started learning Julia few months back, I searched for an IDE or notebook to run Julia efficiently, but I struggled to get a GPU functioning on my own computer. There were no websites offering free cloud computing for Julia. I searched on Julia Discourse


Download and install julia and the Julia:XLA compiler, @warn("Only the very latest Julia version on the `kf/tpu3` branch is supported!") end import Pkg if haskey(ENV, "COLAB_GPU� With Colab you can import an image dataset, train an image classifier on it, and evaluate the model, all in just a few lines of code. Colab notebooks execute code on Google's cloud servers, meaning you can leverage the power of Google hardware, including GPUs and TPUs, regardless of the power of your machine. All you need is a browser.


XLA.jl : Shakespeare RNN, I tried solving the problem the problem for the Julia in Google Colab .The the execution is pretty smooth and runs without errors. visit this … Google currently offers free access to Cloud TPUs through its Colab notebook service. Colab does not officially support julia at the moment, but it is possible to install julia by manually installing it into the runtime (though this has to be done every time the runtime gets reset).