> Modern desktops also have GPUs, however, which are fast at running deep neural networks (DNNs).
That's the rub: deep learning is restricted to CUDA/cuDNN/NVIDIA GPUs, which exclude a large amount of desktops with AMD graphics (e.g. all modern Macs).
Current cloud GPU prices have dropped enough such that this approach may be pretty effective with spot/preemptible instances.
Does anyone know why AMD has dropped the ball so hard on not supporting Tensorflow/PyTorch? It seems like the kind of work 2-5 talented engineers could do (i.e. push harder on HipM, reimplement CuDNN, etc.), and would seriously impact sales, right? I probably misunderstand either the hardware limitations or business side from AMD's perspective.
Coriander [1] looks promising: "Build NVIDIA® CUDA™ code for OpenCL™ 1.2 devices".