The issue with that page is it assumes (1) that the reader is very familiar with CUDA and (2) has a feature checklist vs CUDA.
Eg, there is an "Important features include the following" section where a typical example is "User-mode queues and DMA". We've had user mode queues since Sedgewick's Algorithms in C. Or "Large memory allocations" which we've had since the introduction of the 64 bit CPU. Obviously these must be features in the context of a GPU, but they don't really have a lot of explanatory power for anyone not already intimately familiar with the field.
I suppose the obvious conclusion is ROCM is professionals only; but presumably those professionals are already perfectly happy with CUDA. I'd find it helpful to know what these professionals are expected to implement with all this so I can go figure that out.
Specifically for me I know Vulkan (aka OpenGL++) is a general purpose API for running things on a GPU. I don't understand if that supersedes ROCM, compliments ROCM or what. I'm assuming that Vulkan is all anyone needs and then ROCM is going to ... provide something, maybe libraries? ... as middleware to Tensorflow and related tools. But blow me down if I can find anything that fills me with confidence that I've got the right take. ROCM seems to be very low level which makes little sense to me given that Vulkan (and the slowly obsoleting OpenCL) seem to be where the compute work is being done.
If I wanted to summarise PyTorch it is "a Python API & library that provides convenience functions and data models for machine learning." Or CUDA, at a guess, is "a C++ API for highly parallel compute on Nvidia GPU". ROCm claims to be "the first open-source HPC/Hyperscale-class platform for GPU computing that’s also programming-language independent" and none of that means much to me. Doesn't hint what programming language I'm expecting to be using, and I don't think I even want Hyperscale computing. But I get the feeling I want ROCm because it is associated with PyTorch on AMD GPUs. Befuddling.
I dunno, the ROCm version of PyTorch looked complicated and convoluted so I'm just going to sit it out and wait for someone to explain who the circus is performing for.