Flux already has the ability to borrow Torch kernels. This was released fairly recently. https://github.com/FluxML/Torch.jl https://github.com/FluxML/Torch.jl

Flux already has the ability to borrow Torch kernels. This was released fairly recently. https://github.com/FluxML/Torch.jl https://github.com/FluxML/Torch.jl https://fluxml.ai/2020/06/29/acclerating-flux-torch.html https://fluxml.ai/2020/06/29/acclerating-flux-torch.html Also the gap between native GPU codegen in Julia and the hand-optimized kernels in PyTorch is lesser than you'd imagine. In fact, see this talk at JuliaCon, which compares Julia on a 1000 GPUs against a CUDA/C implementation, and finds them to be extremely close. https://www.youtube.com/watch?v=vPsfZUqI4_0 https://www.youtube.com/watch?v=vPsfZUqI4_0 https://github.com/eth-cscs/ImplicitGlobalGrid.jl https://github.com/eth-cscs/ImplicitGlobalGrid.jl