Join us for a focused deep dive on automatic differentiation in Slang with Shannon Woods. This session distills the core concepts of autodiff, emphasizing how forward and reverse modes work, how gradients propagate, and how to reason about correctness and efficiency with clear, minimal examples.
What we’ll cover:
Forward and backward gradient propagation: intuition and step‑by‑step examples
How to invoke autodiff from Slang
Diff pairs and the forward/backward operators
Differentiable vs. non‑differentiable types; making custom structs differentiable
Providing custom derivatives for fine‑grained control
Handling buffer access and gradient accumulation patterns
Practical techniques for debugging and validating gradients
Who should attend:
Graphics engineers exploring optimization or inverse problems
Researchers and practitioners in differentiable rendering or neural graphics
Developers curious about practical, GPU‑friendly autodiff concepts
Bring your questions—there will be time for discussion and hands‑on gradient debugging tips.