Automatic Differentiation for Legacy Fortran via LFortran and Enzyme
The team wired LFortran to Enzyme’s LLVM‑level AD, extracting exact gradients from a 220‑line Fortran heat solver and exposing it as a JAX primitive. This lets engineers run gradient‑based optimization on decades‑old simulation code without rewriting, opening ML pipelines to high‑performance scientific models.