https://rocm.github.io maybe a good place to start. I've been meaning to checkout TensorFlow for ROCm myself but it's challenging finding general info like what cards are supported (I'm pretty sure Radeon VII is).
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.
While Khronos was busy pushing the C only API they go from Apple, Nvidia created a GPGPU platform, with support for C, C++, Fortran and any language with PTX capable backend.
When Khronos woke up to the fact that most researchers don't want to use plain old C, it was too late.
It remains to be seen how much uptake SYSCL or SPIR-V will ever get, across GPGPU vendors.
Intel is trying to get back into the game via their extended SYSCL, so lets see.
Also note that on mobile devices only Apple actually has supported OpenCL, while Google pushed their Renderscript instead.
> Going to 11: Amping Up the Programming-Language Run-Time Foundation