Tutorials

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From 15:00 on Thursday 9 July, there will be a tutorial session. During this session, there are a number of tutorials running in parallel for you to choose from. The list of tutorials is given below.

A beginner's guide to Rust

This session is aimed at people who don't use Rust yet, but are attending the workshop as they are interested in starting to use it. We will cover basic syntax in Rust and a few of the language's nicest features.

Before this session, please install Rust on your computer. There are instructions for doing this at rust-lang.org/tools/install.

Scientific computing with rustc

This session will guide the audience through the use of autodiff and gpu offloading in Rust.

As of a few weeks ago, we ship all needed dependencies for std::autodiff via rustup and nightly, so installation now takes ~5 seconds! A GSoC contributor is also working on adding rustup distribution for std::offload (gpu programming). Both these feature will be covered in this tutorial.0

Linear algebra in Rust with RLST

RLST (the Rust Linear Solver Toolbox) is a Rust linear algebra library that contains a number of data-structures, algorithms, and interfaces to external solvers.

In this tutorial, we will learn how to use many of the features of RLST with a focus on distributed arrays.

3D Scene Inference in ModPPL

This session introduces participants to probabilistic programming via inverse graphics: the computer-vision paradigm of inferring the 3D scene that produced an image. Participants will use ModPPL to combine rendering-based generative scene models with user-space MCMC inference, recovering structured 3D scene hypotheses directly from images across a series of scenes of increasing complexity, and will watch each hypothesis converge onto its observed image in real time.

Note this tutorial uses a live window display. Before this session, please install Rust (stable) and Git, then clone and build the repository github.com/agarret7/modppl-derender.