Might have to do with the fact that AMD just doesn't seem to have the resources (see the common complaints about their drivers' quality) to fully support every chip.
Another reason is certainly that they simply don't need to - just like Intel's iGPU, people working with deep learning opt for discrete GPUs (either built-in or external), both just isn't an option (yet?) for M1-based systems.
The audience would be a niche within a niche and the cost-benefit-ratio doesn't seem to justify the effort for them.
AMD's net income for 2020 was about $2.5B. If it was a management priority, they would fund more people to focus on this.
I would love to support open-source drivers, but AMD's efforts with ROCm on consumer hardware are a joke. It's been said in other comments that AMD only cares about the datacenter. That certainly seems to be the case. So until AMD takes this seriously and gets a legitimate developer story together, I'm spending my money elsewhere.
> So until AMD takes this seriously and gets a legitimate developer story together, I'm spending my money elsewhere.
Fair enough. Thing is, AMD's market share in the mobile market has been below 15% over the past years [1] and only last year increased to about 20%.
Of these 20%, how many notebooks are (think realistically for a second) intended to be used for DL while also not featuring an NVIDIA dGPU?
ROCm on consumer cards isn't a priority for AMD, since profits are small compared to the datacentre market and there's not that many people actually using consumer hardware for this kind of work.
I always feel there's a ton of bias going on and one should refer to sales data and market analysis to find out what the actual importance of one's particular niche really is.
AMD's focus w.r.t. consumer hardware is on gaming an CPU performance. That's just how it is and it's not going to change anytime soon. On the notebook side of things, and AMD APU + NVIDIA dGPU is the best you can get right now.
> ROCm on consumer cards isn't a priority for AMD, since profits are small compared to the datacentre market and there's not that many people actually using consumer hardware for this kind of work.
I think causality runs the other way: Profits are small and there aren't many people using AMD cards for this _because_ the developer experience for GPGPU on AMD is terrible (and that because it's not a priority for AMD).
That would imply that there even was a laptop market for AMD in the first place. As the market numbers show, up until last year, AMD simply wasn't relevant at all in the notebook segment, so what developer experience are you even talking about if there were no developers on AMD's platform?
I agree that AMD on mobile is a wasteland. But AMD has shipped over 500m desktop GPUs in the last 10 years. Surely some of those could/would have been better used for GPGPU dev if there was a decent developer experience.
I disagree with you. AMD is running behind developers to use AMD for GPU based training. Just 1 month or so back, it announced partnership with AWS to get its GPU on the cloud.
So I would disagree with your claim about marketshare being the reason for its helplessness to create a superior developer-laptop experience.
Cluelessness? sure. But not helplessness. If it wants the developer market (versus the gamer), then it better start acting like a developer tools company...which includes cosying up to Google/Facebook/AWS/Microsoft and throwing money on ROCm. Education is one of them - https://developer.nvidia.com/educators/existing-courses ... and giving developers a generally superior development experience on the maximum number of machines is another.
Well, NVIDIA view themselves as a software company that also builds hardware.
> "NVIDIA is a software-defined company today," Huang said, "with rich software content like GeForce NOW, NVIDIA virtual workstation in the cloud, NVIDIA AI, and NVIDIA Drive that will add recurring software revenue to our business model." [1]
Not sure that's the case with AMD. AMD lags behind massively when it comes to software- and developer support and I doubt that a few guys who insist on ROCm running on their APUs are in their focus.
For a more personal take on your answer - do consider the rest of world. For example, Ryzen is very popular in India. Discrete GPU are unaffordable for that college student who wants to train a non-English NLP model on GPU.
How does that contradict my point - Apple has to support the M1, since their M1-based SoCs don't support dGPUs (yet), so the M1 is all there is.
Besides, Apple is the most valuable company in the world and has exactly the kind of resources AMD doesn't have.
> or example, Ryzen is very popular in India. Discrete GPU are unaffordable for that college student who wants to train a non-English NLP model on GPU.
Well Google Collab is free and there are many affordable cloud-based offers as well. Training big DL models is not something you'd want to do on a laptop anyway. Small models can be trained on CPUs, so that shouldn't be an issue.
Inference is fast enough on CPUs anyway and if you really need to train models on your Ryzen APU, there's always other libraries, such as TensorflowJS, which is hardware agnostic as it runs on top of WebGL.
That's why I don't think this is a big deal at all - especially given that Intel still holds >90% of the integrated GPU market and doesn't even have an equivalent to ROCm. Again, niche within a niche, no matter where you look.
Another reason is certainly that they simply don't need to - just like Intel's iGPU, people working with deep learning opt for discrete GPUs (either built-in or external), both just isn't an option (yet?) for M1-based systems.
The audience would be a niche within a niche and the cost-benefit-ratio doesn't seem to justify the effort for them.