The Julia Language x GSoD x JSoD 2020

The Julia Language is proud to announce that we had 5 individuals selected to participate in our inaugural year of GSoD:

Project 1
Project name: Documentation for the JuliaGPU stack
Technical writer: Ellipse0934
Project length: Standard length (3 months)
Project description

Project 2
Project name: Bayesian inference for Gaussian Processes
Technical writer: Liza
Project length: Standard length (3 months)
Project description

Project 3
Project name: The unified documentation of Scientific Machine Learning
Technical writer: mkg33
Project length: Long-running (5 months)
Project description

Project 4
Project name: LightGraphs Docs 2.0 & User-Friendly JuliaGraphs Tutorials
Technical writer: Shuo Liu
Project length: Long running (5 months)
Project description

Project 5
Project name: Reinventing the FluxML Website
Technical writer: sophb
Project length: Standard length (3 months)
Project description

We are also fortunate to have 3 individuals joining us for our first year running JSoD:

Project 6
Project name: VS Code Extension Documentation
Technical writer: Samantha Gidlow
Project length: Standard length (3 months)

Currently, the VS Code Extension documentation is lacking. While investigating the documentation during the exploratory phase, there is a lot of gaps in the documentation that we can fill in with relevant information. I think the first thing we would want to do is make sure that we have a good solid Getting Started section of the documentation that will help users get started with the VS Code Extension. Once that documentation is complete, we can move onto documenting the remaining parts of the User’s Guide.

Project 7
Project name: Developing JuliaIntervals Documentation and Webpage
Technical writer: besselj
Project length: Long-running (5 months)

JuliaIntervals is an umbrella term for several packages related to Interval Arithmetic, which are mainly maintained by David P. Sanders and Luis Benet. Interval arithmetic allows to perform guaranteed computations. Traditional numerical algorithms generally output single numbers, which (hopefully) are a good approximation of the correct results. Interval arithmetic methods, on the other hand, return intervals which are guaranteed to contain the correct results. Interval methods allow to take into account rounding errors in a rigorous way and have been applied in several fields, such as global optimisation and constraint programming. Interval computations have been standardized with the IEEE 1788-2015 standard. The Julia implementation IntervalArithmetic.jl is approaching compliance with the standard and several packages for applications have already been produced. As the packages become more mature, the need for a detailed and accessible documentation also increases. This GSoD proposal aims at improving the documentation of the packages to give JuliaIntervals the visibility it deserves. The mentor for the project will be David P. Sanders

Project 8
Project name: SciML Automated Benchmarks and Performance Regression Flagging
Technical writer: kipply
Project length: Long-running (5 months)

Suggesting what’s proposed in, also interested in tutorial writing.

I like Julia as a language (mostly from the perspectives of studying compiler design) and especially from a background of working with compilers I love benchmarking and benchmark tools.
I believe the work in automated benchmarking itself is interesting and can serve as a basis for similar work for other projects, and it’ll benefit the ecosystem is having readily accessible and up to date information. Beyond that, I’m not sure I can further describe the project beyond what’s already listed on the site.

We are super excited to have all of these amazing folks working with us across the Julia Ecosystem. Thank’s to everyone who applied, our incredible mentors for committing time to these folks, and Google for selecting us as well as funding 5 projects. This is going to be an awesome season of docs!

-Logan, Chris, and Avik
Julia Season of Contributions Team