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Re-posted from: https://geekmonkey.org/julia-gpu-programming-with-wsl2/

Julia GPU Programming with WSL2

I use Windows for gaming. It's been a long time since I've last done any serious development work on my Windows machine and yet I still spent a good chunk of money on building out a beefy machine for my efforts to learn machine learning. It has taken me a few months to finally sit down and get this machine ready for anything other than gaming.

With the recent announcement of GUI support for WSLg I got really excited to try out WSL and see how good the GPU support actually is, but that's not the main reason. I've been shying away from developing on Windows because I'm used to a *NIX environment. WSL gives you that, but up until recently you wouldn't have been able to interact with any GPU – and this all changed with this announcement!

You can watch the video below to see what's coming for WSL2.

The first half of this article will show you how to get everything set up and in the second half we'll set up CUDA.jl in Julia. Since the latter part is about CUDA I'll assume that you have a compatible nVidia GPU.

Installation

Here's a summary of what we need to go through to prepare our environment:

Update Windows 10 to latest release on the dev channel
Install nVidia CUDA drivers
Install Ubuntu 20.20 in WSL2
Install Linux CUDA packages
🎉

Windows 10 Insider Preview

At the time of writing all of the features are only available through the Windows Insider Program. The Windows Insider Program allows you to receive new Windows features before the hit the main update line. The program is split into three channels: Dev, Beta and Release Preview.

To receive the update with WSLg and GPU support we will need to switch to the dev channel.

Note: The dev channel comes with some rough edges and potential for system instability. Be mindful of this when you switch and make sure you have backups!

After installing all downloaded updates you should end up with OS Build 21364 or higher. You can check your OS Build by running winver in PowerShell/cmd.

With this all set we can hop on to install the latest WSL2 compatible CUDA drivers.

CUDA drivers

NVIDIA are providing special CUDA drivers for Windows 10 WSL. The link below will take you to the download page. It's required to sign up for the NVIDIA Developer Program, which is free.

Follow the setup wizard (I chose the express installation which keeps existing settings in place).

Note: There's also a documentation page provided by NVIDIA around setting up your GPU for WSL. I found the docs to be outdated and not working on my machine.

Installing Ubuntu 20.04 LTS with WSL2

Before we can proceed with installing Ubuntu I advise to update the WSL kernel by running:

wsl --update

In case you're like me and don't enjoy the default terminal Windows comes with I suggest you install Windows Terminal from the Microsoft Store. This terminal comes is a lot more pleasant to use than either cmd or the PowerShell terminal ever were.

It's also a good idea to set WSL to default to version 2:

wsl --set-default-version 2

Finally let's install Ubuntu with:

wsl --install --distribution Ubuntu-20.04

In case you were wondering what other distributions are available you can simply run: wsl --list --online.

Ubuntu 20.04 LTS

With Ubuntu installed we have a couple of final steps. First we will add an upstream repo to apt for getting the latest CUDA builds directly from NVIDIA:

sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /"

Add CUDA apt repository for Ubuntu 20.04

We also need to add NVIDIA's GPG key for the apt repo:

sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub

Add nVidia gpg key

And finally to make sure that we prefer the packages provided by NVIDIA over packages in mainline Ubuntu we need to pin the apt repo:

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600

Pin file to prioritize CUDA apt repository

With this out of the way, we're ready to install the CUDA drivers inside our WSL Ubuntu installation:

 sudo apt update && sudo apt install -y cuda-drivers

In case setting up WSL2 with GPU support was all you wanted to do – we're done!

Julia + WSL2 + Cuda.jl

Ok, so as promised in the headline we're now going to install Julia inside our Ubuntu 20.04 and set up Cuda.jl.

Install Julia

At the time of writing Julia 1.6.1 is the latest version available (make sure to check for updates on Julia's download page).

First let's fetch the latest Julia tarball:

wget https://julialang-s3.julialang.org/bin/linux/x64/1.6/julia-1.6.1-linux-x86_64.tar.gz

Extract the .tar.gz:

tar -xvzf julia-1.6.1-linux-x86_64.tar.gz

Move the extracted folder to /opt:

sudo mv -r julia-1.6.1 /opt/

Finally, create a symbolic link to julia inside the /usr/local/bin folder:

sudo ln -s /opt/julia-1.6.1/bin/julia /usr/local/bin/julia

You may pick a different target directory for your installation of Julia or use a version manager like asdf-vm.

Install Cuda.jl

At this point simply run julia in your terminal and you should be dropped into the Julia REPL. I assume you've worked with Julia before and know how to operate it's package manager.

Hit ] to enter pkg mode and install CUDA with:

activate --temp
add CUDA

From here hit backspace and import CUDA. CUDA.jl provides a useful function called functional which will confirm that we've done everything right (well, that's the hope at least, right?).

using CUDA
CUDA.functional()

You can additionally run CUDA.versioninfo() to get a more detailed breakdown of the supported features on your GPU.

At this point you should have a working installation with WSL2, Ubuntu 20.04, Julia and CUDA.jl. In case you're new to CUDA.jl I suggest you follow the excellent introduction to GPU programming by JuliaGPU or jump in at the deep end with FluxML's GPU support.

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By: DSB

Re-posted from: https://medium.com/coffee-in-a-klein-bottle/vim-for-julia-18eba071c654?source=rss-8bd6ec95ab58------2

An easy setup for Vim as Julia IDE (on Ubuntu)

As someone who has been a Vim user for years, I can confidently say that Vim is highly addictive. Once you get used to it’s shortcuts, editing code without it becomes unbearable. Although many tutorials exist on how to setup a Vim IDE for Python and other languages, no tutorial seems to be available for using Vim with Julia. So this might be a first.

By no means this article is comprehensive, I intend to present a very neat and fast way of using Vim with Julia. Note that there are many alternatives to using “pure Vim”, one can code using Juno and install the vim-mode package in Atom. The method I propose is using “pure Vim”, but with the very cool SpaceVim.

If you are new to Vim, and is trying to learn it, you probably realized that Vim has thousands of plugins available, and setting up your “IDEish” Vim may be quite complicated. One has to learn how to install plugins, choose color highlighting themes, and much more. Here is where SpaceVim comes in.

SpaceVim is a Vim distribution that works pretty much like an IDE, with some of the most popular plugins already installed. It also comes with some preset shortcuts, allowing for a more efficient file navigation. And most importantly, it looks beautiful.

Installing Vim and SpaceVim

The first thing to do is to install Vim… Well, actually, NeoVim. If you are not familiar with NeoVim, it is pretty much an updated Vim. So why use it? The only reason is that in my experience, it just works better with SpaceVim and Julia, and also, I like the cursor better. But feel free to go with Vim if you prefer it. The commands below install NeoVim and then SpaceVim.

sudo apt install neovim

curl -sLf https://spacevim.org/install.sh | bash

To access NeoVim from the terminal, you just need to write

nvim “example.txt”

If like me, you prefer to use the common “vim” command, then you can create an alias.

If you are using bash (the standard shel), open the file ~/.bashrc and write alias vim="nvim $argv".

If you are using fish, then on the terminal write

function vim
    nvim $argv
end

This will create a function called “vim” in the fish shell. Then run the command funcsave vim , to save the function so it becomes permanant.

When you run Vim for the first time after installing SpaceVim, you will note that some plugins will be installed. By the end of the installation, you might get an error message about “vimproc”. To fix this, go into the command line of Vim by typing : , then write VimProcInstall .

Example on running VimProcInstall to fix possible error messages.

Setting up Julia

To set up Julia now is incredibly simple. If a plugin is already available in the SpaceVim “ecosystem”, you just need to add that plugin to your init.toml file, which is located in your home directory inside the folder .SpaceVim.d , and SpaceVim will install it for you.

Hence, to install the packages for dealing with Julia, just open ~/.SpaceVim.d/init.toml and write the following in the end of the file

[[layer]]

name= "lang#julia"

You might also want to add

[[layer]]

name= "colorscheme"

The code above will enable different colorschemes, which can be chosen by altering the attribute colorscheme.

This is it. You now have a Vim IDE for Julia!

Example of file ~/.SpaceVim.d/init.toml — Note that the ‘autocomplete’ layer is disabled. This is due to some incompatibility between the Julia packages and the autocomplete package. At the end of this article I present a fix for this problem.

Tips on using SpaceVim

There are tons of tutorials on how to use Vim, so I will not go into that. But there is not as much information on using SpaceVim. So I’ll give you some tips on how to get started.

Installing Plugins: I’ve already talked about how to install different plugins. You just have to pretty much add a layer to your init.toml file. Here is a list of the available plugins for SpaceVim;
Navigating file: the NerdTree plugin is already shipped with SpaceVim, so one just needs to press F3 to open the navigation menu. You can press l to go inside a folder, or h to go out of the folder;
<Leader> and SPC: If you read the documentation of SpaceVim, you will likely encounter shortcuts such as SPC <Tab> . The SPC stands for “space bar”. The <Leader> default key is \ ;
Commenting line: To comment a line, just do SPC c l (space bar + c +l), and SPC c l ;
Copy to system clipboad: A common difficulty to people starting with Vim is the fact that you cannot easily copy text from Vim to a another file not opened on the same Vim window (e.g your Browser). SpaceVim solves this to you, just use <Leader> y to copy to your system clipboard, and <Leader> p ;
Moving from Buffers (tabs): If you are working on a file, then press F3 and open another file, a new buffer will become active. You can then press SPC <Tab> to change buffers, therefore, easily going from one file to another. Amazingly, the buffers will be shown on the top of Vim, and you can actually just click on them if you want (but if you are using Vim, you probably don’t want to be using your mouse).

Image showing the different buffers of files opened.

If you like this article or has suggestions on how it could be improved, consider “Clapping” or leaving a comment, so I can get some feedback.

UPDATE: When using SpaceVim with Julia autocompletion, you might experience some freezing when pressing the Tab . This is due some incompatibility between the julia-vim package and the other autocompletion packages present on SpaceVim. To solve this issue, you may disable the Latex unicode tab command in the julia-vim package. To do this, open the file ~./SpaceVim/autoload/SpaceVim/layers/lang/julia.vim . And disable the following command.

let g:latex_to_unicode_tab = 0

Vim for Julia was originally published in Coffee in a Klein Bottle on Medium, where people are continuing the conversation by highlighting and responding to this story.

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