[jpsamaroo]

> This is a complete novice, ill informed, question. So forgive it in advanced, but why have an AMD specific backend at all? Couldn't you just use AMD's HIP/HIP-IFY tool on the CUDA backend and get an AMD friendly version out?

HIP and HIPify only work on C++ source code, via a Perl script. Since we start with plain Julia code, and we already have LLVM integrated into Julia's compiler, it's easiest to just change the LLVM "target" from Native to AMDGPU (or NVPTX in CUDA.jl's case) to get native machine code, while preserving Julia's semantics for the most part.

Also, interfacing to ROCR (AMD's implementation of the Heterogeneous System Architecture or HSA runtime) was really easy when I first started on this, and codegen through Julia's compiler and LLVM is trivial when you have CUDAnative.jl (CUDA.jl's predecessor) to look at :)

I should also mention that not everything that CUDA does maps well to AMD GPU; CUDA's streams are generally in-order (blocking), whereas AMD's queues are non-blocking unless barriers are scheduled. Also, things like hostcall (calling a CPU function from the GPU) doesn't have an obvious alternative with CUDA.

[soganess]

Thank you for taking the time! I found this quite helpful.

[MayeulC]

Something that is hinted at, but not spelled out loud in our posts is that AMD actively upstreams and maintains a LLVM back-end for their GPUs, so it really is a matter of switching the binary target for the generated code, at least in theory :)