Differentiable Fortran with LFortran and Enzyme
- ← Tesseract Blog 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… Decades of validated physics code in CFD, climate, aerospace, and nuclear sit behind a wall that modern ML pipelines can’t cross, because they don’t expose gradients.
- The usual answer is to rewrite it all in JAX or PyTorch.
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- ← Tesseract Blog 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… Decades of validated physics code in CFD, climate, aerospace, and nuclear sit behind a wall that modern ML pipelines can’t cross, because they don’t expose gradients.
- The usual answer is to rewrite it all in JAX or PyTorch.
Sources: Pasteurlabs