Is there an equivalent to cross-language link time optimization via LLVM?

[giordano]

@Benny

Never did autodifferentiation let alone Enzyme, so noob question: is that issue implying that Enzyme works or is intended to work on LLVM IR across ccall boundaries?

Yes, Enzyme works at the LLVM level, which means it couldn’t care less about the frontend language: as long as it receives LLVM IR/bitcode, it can do anything. And Enzyme is “just” an optimisation pass, so the same applies to other passes.

@Benny

What went wrong there exactly, couldn’t tell how the working and failed functions differed after that Numba name-unmangling.

If you want a more positive example:

Get Numba LLVM IR differentiated in Julia using Enzyme.jl

You made it so easy for me to fix it! Indeed I was making a call to the Numba’s internal function, namely _ZN8__main__4funcB2v1B52c8tJTIeFIjxB2IKSgI4CrvQClUYkACQB1EiFSRRB9GgCAA_3d_3dEdddd which returns an i32, 0 for the success and 1 for Python exception. The first argument double* %retptr is where the result is stored, the second argument { i8*, i32, i8*, i8*, i32 }** is a pointer for Numba’s exception info block (%excinfo), and then the rest four arguments for a, w, p and t as double’s. Wher…