Detailed documentation for Raster's subsystems. For a quick overview, see the main README.
| Document | Description |
|---|---|
| Compiler Pipeline | Nanopass architecture, pass sequence, compile-aot, diagnostics |
| Automatic Differentiation | Forward-mode, reverse-mode, rrules, sensitivity analysis |
| GPU Computing | Parallel primitives, session API, backends, SoA layout |
| Deep Learning | Layers, loss, optimizers, compiled training, einsum |
The notebooks/raster/ directory contains Kindly/Clay notebooks that walk through features with runnable code:
| Notebook | Topics |
|---|---|
| Getting Started | deftm, typed dispatch, value types |
| Automatic Differentiation | Forward-mode, reverse-mode, value+grad |
| ODE Solvers | Lorenz attractor, adaptive solvers, events |
| Linear Algebra | Vec/Mat types, LU, Cholesky, SVD |
| Optimization | L-BFGS, Nelder-Mead, Newton's method |
| Deep Learning | MLP training with compiled AD |
The design/ directory contains architecture documents for ongoing and planned work:
| Document | Topic |
|---|---|
| Compiler | Compiler architecture overview |
| Type System | Typed multiple dispatch design |
| Autodiff | AD design and implementation |
| SOAC Fusion | Loop fusion design |
| Loop Vectorization | Auto-vectorization design |
| Functional Combinators | Pure parallel form design |
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