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Rust Compiler Autodiff Hacking
Learn how to build a Rust compiler with automatic differentiation, inspect LLVM IR rewrites, replace manual backpropagation, and train a Rust-translated LLM model.
I will start by showing everyone how simple it is to compile your own Rust compiler with support for automatic differentiation enabled.
Due to time constraints, I will just show the commands, and not run the actual build.
Next, we want to see it working, so I will compile some Rust code into the LLVM Intermediate Representation (IR) and show how our tool for automatic differentiation rewrites the IR to compute derivatives. I will show the different IR rewrite steps to explain why LLVM is usually very efficient here, and what is currently the best way to crash it.
As a final, bigger example I will introduce a Rusty version of Karpathy’s llm.c model which was auto-translated by rust2c.
With git show I will go through a diff which deletes hundreds of lines from Karpathy that implemented backpropagation manually, since we can replace them with a single line of std::autodiff. I will then run the code to train the model.
Adds automatic differentiation to Rust for differentiable programming and optimization.
Enzyme automatically computes high-performance gradients from existing LLVM IR code.
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