My initiation into shaders was porting some graphics code from OpenGL on Windows to PS5 and Xbox, and (for your NDA and devkit fees) they give you some very nice debuggers on both platforms.

But yes, when you're stumbling around a black screen, tooling is everything. Porting bits of shader code between syntaxes is the easy bit.

Can you get better tooling on Windows if you stick to DirectX rather than OpenGL?

Is your code easy to transfer to other environments? The Apple vendor lock-in is not a great place for development if the end product runs on servers, unlike using AMD Gpus which can be found on the backend. Same goes for games because most gamers either have an AMD or an Nvidia graphics card as playing on Mac is still rare, so priority should be supporting those platforms

Its probably awesome to use Metal and everything but the vendor lock-in sounds like an issue.

It's a full featured and beautifully designed experience, and when it works it's amazing. However it regularly freezes of hangs for me, and I've lost count of the number of times I've had to 'force quit' Xcode or it's just outright crashed. Also, for anything non-trivial it often refuses to profile and I have to try to write a minimal repro to get it to capture anything.

I am writing compute shaders though, where one command buffer can run for seconds repeatedly processing over a 1GB buffer, and it seems the tools are heavily geared towards graphics work where the workload per frame is much lighter. (Will all the AI focus, hopefully they'll start addressing this use-case more).

nsys and nvtx are awesome.

many don't know but you can use them without GPUs :)

GDB supports it https://sourceware.org/gdb/current/onlinedocs/gdb.html/AMD-G...

You also get UMR from AMD https://gitlab.freedesktop.org/tomstdenis/umr

There is also a bunch of other tools provided: https://gpuopen.com/radeon-gpu-detective/ https://gpuopen.com/news/introducing-radeon-developer-tool-s...

> After searching for solutions, I came across rocgdb, a debugger for AMD’s ROCm environment.

It's like the 3rd sentence in the blog post.......

I've been using it for a few years on Gentoo. There were challenges with Python 2 years ago, but over the past year it's stabilized and I can even do img2video which is the most difficult local inference task so far.

Performance-wise, the 7900 xtx is still the most cost effective way of getting 24 gigabytes that isn't a sketchy VRAM mod. And VRAM is the main performance barrier since any LLM is going to barely fit in memory.

Highly suggest checking out TheRock. There's been a big rearchitecting of ROCm to improve the UX/quality.

I bought one when they were pretty new and I had issues with rocm (iirc I was getting kernel oopses due to GPU OOMs) when running LLMs. It worked mostly fine with ComfyUI unless I tried to do especially esoteric stuff. From what I've heard lately though, it should work just fine.

For LLMs, I just pulled the latest llama.cpp and built it. Haven't had any issues with it. This was quite recently though, things used be a lot worse as I understand it.

You'd be much better off wiht any decent nVidia against the 7900 series.

AMD doesn't have a unified architecture across GPU and compute like nVidia.

AMD compute cards are sold under the Insinct line and are vastly more powerfull than their GPUs.

Supposedly, they are moving back to a unified architecture in the next generation of GPU cards.

I tested some image and text generation models, and generally things just worked after replacing the default torch libraries with AMD's rocm variants.

I've done it with a 6800XT, which should be similar. It's a little trickier than with an Nvidia card (because everything is designed for CUDA) but doable.

try it with ramalama[1]. worked fine here with a 7840u and a 6900xt.

[1] https://ramalama.ai/