Hacker News·4 min read·hard
Differentiable Fortran with LFortran and Enzyme
D
dionhaefner
✦AI Summary
Researchers are using LFortran and Enzyme to enable automatic differentiation in legacy Fortran, C, and C++ simulation code. This allows high-performance physics engines to be integrated into modern machine learning frameworks like JAX and PyTorch.
What if you could backpropagate through existing Fortran, C, or C++ simulation code, embed it into JAX and torch, and use it as a high-performance differentiable physics engine? Turns out, you can — if you’re brave enough…
technologyscience
✦
Get the full story
Sign up for Headlinne to unlock AI insights, political bias analysis, and your personalized news feed.
Create free accountAlready have an account? Sign in