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CUDA Moat Still Alive

semianalysis.com

11–20 of 176 posts

Re: CUDA Moat Still Alive

#11
post #5

> It’s not just that it’s immature software, they need to change how they do development. I remember geohot saying something similar about a year ago

"The software needs to be better" is (and was) an easy call to make for anyone paying attention. The problem is that "AMD just needs to do better" is not and will never be an implementable strategy. Engineering isn't just about money. It's also about the process of exploring all the edge cases.

"We recommend that AMD to fix their GEMM libraries’ heuristic model such that it picks the correct algorithm out of the box instead of wasting the end user’s time doing tuning on their end." Is such a profoundly unhelpful thing to say unless you imagine AMDs engineers just sitting around wondering what to do all day.

AMD needs to make their drivers better, and they have. Shit just takes time.

Re: CUDA Moat Still Alive

#12
I made the mistake of clicking on one of the links to commits they mentioned only to end up at a MR changing multiple autogenerated yaml files with 10k line diffs and incomprehensible names. I guess this is where the whole "bad talent" thing comes in - a year later and you are thousands of YAML files deep but still no one can run a simple PyTorch compile ops and get the performance you sold, absolutely unhinged.

Re: CUDA Moat Still Alive

#13
> Give AMD Engineers more compute and engineering resources to fix and improve the AMD ecosystem, they have very few internal gpu boxes relative to what Nvidia provides to their engineers.

This is real. We’ve found ourselves having to give hardware to engineers at AMD because they’re unable to get allocation of it internally.

Re: CUDA Moat Still Alive

#14
post #2

What I couldn't find is inference benchmarks for consumer hardware. Just pick a reasonable workload with llama.cpp or ollama and show us some numbers. I'm particularly interested in building a Home Assistant machine that can run the voice assistant locally (STT/TTS/LLM) while using the least amount of power / generating the least amount of heat and noise.

You might just check out the Home Assistant Voice:

https://ameridroid.com/products/home-assistant-voice-preview...

Re: CUDA Moat Still Alive

#15
> CUDA Moat Still Alive

Wrong conclusion. AMD is slower than NVidia, but not _that_ much slower. They are actually pretty cost-competitive.

The just need to do some improvements, and they'll be a very viable competitor.

Re: CUDA Moat Still Alive

#17
post #5

> It’s not just that it’s immature software, they need to change how they do development. I remember geohot saying something similar about a year ago

In buggy numerical code many bugs go trough the software stack without any problems. No crash, no errors. For example,you might switch two double parameters to a function and if their value range is similar, everything works fine except it's all bullshit.

If there are bugs in AMD code that prevent running tests, I bet there are even more bugs that don't manifest until you look at results.

Re: CUDA Moat Still Alive

#18
post #2

What I couldn't find is inference benchmarks for consumer hardware. Just pick a reasonable workload with llama.cpp or ollama and show us some numbers. I'm particularly interested in building a Home Assistant machine that can run the voice assistant locally (STT/TTS/LLM) while using the least amount of power / generating the least amount of heat and noise.

You might just check out the Home Assistant Voice: https://ameridroid.com/products/home-assistant-voice-preview...

Yes, that's exactly what I was checking out. You need fast enough hardware to run the speech to text, text to speech and (most importantly) LLM locally: https://www.youtube.com/watch?v=XvbVePuP7NY (he has dual 3090 GPUs but that's not a practical setup for most people - budget / power / noise).

Re: CUDA Moat Still Alive

#19
post #5

> It’s not just that it’s immature software, they need to change how they do development. I remember geohot saying something similar about a year ago

I expect everyone has been saying it for a while, the calls are just getting more strident and public as it becomes clear that AMD's failures are strategic rather than tactical. And as people try to build business on their half-hearted attempts.

I still think it is a mistake to say that CUDA is a moat. IMO the problem here is that AMD still doesn't seem to think that GPGPU compute is a thing. They don't seem to understand the idea that someone might want to use their graphics cards to multiply matricies independently of a graphics pipeline. All the features CUDA supports are irrelevant compared to the fact that AMD can't handle GEMM performantly out of the box. In my experience it just can't do it, back in the day my attempts to multiply matrices would crash drivers. That isn't a moat, but it certainly is something spectacular.

If they could manage an engineering process that delivered good GEMM performance then the other stuff can probably get handled. But without it there really is a question of what these cards are for.

Re: CUDA Moat Still Alive

#20
post #5

> It’s not just that it’s immature software, they need to change how they do development. I remember geohot saying something similar about a year ago

Anyone who looks at the mess that is ROCm and the design choices they made could easily see that.

GPU support lagged behind for years, no support for APUs and no guaranteed forward compatibility were clear signs that as a whole they have no idea what they are doing when it comes to building and shipping a software ecosystem.

To that you can add the long history of both AMD and ATI before they merged releasing dog shit software and then dropping support for it.

On the other hand you can take any CUDA binary even one that dates back to the original Tesla and run it on any modern NVIDIA GPU.

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