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> I’m not at all happy with this situation. As long as AMDs investment into software and evangelism remains at ~$0, I don’t see how any hardware they put out wi

> I’m not at all happy with this situation. As long as AMDs investment into software and evangelism remains at ~$0, I don’t see how any hardware they put out will make a difference. It appears AMD initial strategy is courting the HPC crowd and hyperscalers, they have big budgets, lower support overhead and are willing and able to write code that papers-over AMDs not-great software while appreciating lower-than-Nvidia TCO. I think this this incremental strategy is sensible, considering where most of the money is. As a first mover, Nvidia had to start from the bottom up; CUDA used to run only/mostly on consumer GPUs - AMD is going top-down, starting with high-margin DC hardware, before trickling down rack-level users, and eventually APUs later as revenue growth allows more re-investment.

antupis 2y ago
That is wrong move personally would start from localllm/llama folks who crave more memory and build up from there.
- sangnoir 2y ago
  Seeing that they don't have a mature software stack, I think for now AMD would prefer one customer who brings in $10m revenue over 10'000 customers at $1000 a pop.
landryraccoon 2y ago
They’re making the wrong strategic play. They will fail if they go after the highest margin customers. Nvidia has every advantage and every motivation to keep those customers. They would need a trillion dollars in capital to have a chance imho. It would be like trying to go after Intel in the early 2000s by trying to target server cpus, or going after the desktop operating system market in the 90s against Microsoft. Its aiming for your competition where they are strongest and you are weakest. Their only chance to disrupt is to try to get some of the customers that Nvidia doesn’t care about, like consumer level inference / academic or hobbyist models. Intel failed when they got beaten in a market they didn’t care about, i.e mobile / small power devices.
- acchow 2y ago
  > They would need a trillion dollars in capital to have a chance imho. All AMD would really need is for Nvidia innovation to stall. Which, with many of their engineers coasting on $10M annual compensation, seems not too far fetched
  - sangnoir 2y ago
    AMD can go toe to toe with Nvidia on hardware innovation. What AMD had realised (correctly, IMO), is that all they need is for hyperscalers to match/come close to Nvidia on software innovation on AMD hardware - Amazon/Meta/Microsoft engineers can get their foundation models running on M1300X well enough for their needs - CUDA is not much of moat in that market-segment where there are dedicated AI-infrastructure teams. If the price is right, they may shift some of those CapEx dollars from Nvidia to AMD. Few AI practitioners - and even fewer LLM consumers - care about the libraries underpinning torch/numpy/high-level-python-framework/$LLM-service, as long as it works.
- Certhas 2y ago
  This is a common sentiment, no doubt also driven by the wish thay AMD would cater to us. But I see no evidence that the strategy is wrong or failing. AMD is already powering a massive and rapidly growing share of Top 500 HPC: https://www.top500.org/statistics/treemaps/ https://www.top500.org/statistics/treemaps/ AMD compute growth isn't in places where people see it, and I think that gives a wrong impression. (Or it means people have missed the big shifts over the last two years.)
  - Jlagreen 2y ago
    Super computers are in 95% cases government funded and I recommend that you check in conditions for tenders and how government has check on certain condition in buying. That isn't a normal business partner who only looks at performance, there are many more other criteria in the descision making. Or let me ask you directly, can you name me one enterprise which would buy a super computer and wait 5+ years for it and fund the development of HW for it which doesn't exist yet? At the same time when the competition can deliver a super computer within the year with an existing product? No sane CEO would have done Frontier or El Capitan. Such things work only with government funding where the government decides to wait and fund an alternative. But AMD is indeed a bit lucky that it happened or otherwise they wouldn't been forced to push the Instinct line. In the commercial world, things work differently. There is always a TCO calculation. But one critical aspect since the 90s is SW. No matter how good the HW is, the opportunity costs in SW could force enterprises to use the inferior HW due to SW deployment. If vision computing SW in industry is supporting and optimized for CUDA or even runs only with CUDA then any competition has a very hard time penetrating that market. They first have to invest a lot of money to make their products equally appealing. AMD makes a huge mistake and is by far not paranoid enough to see it. For 2 decades, AMD and Intel have been in a nice spot with PC and HPC computing requiring x86. It basically to this date has guaranteed a steady demand. But in that timeframe mobile computing has been lost to ARM. ML/AI doesn't require x86 as Nvidia demonstrates by combining their ARM CPUs into the mix but also ARM themselves want more and more of the PC and HPC computing cake. And MS is eager to help with OS for ARM solutions. What that means is that if some day x86 isn't as dominant anymore and ARM becomes equally good then AMD/Intel will suddenly have more competition in CPUs and might even offer non-x86 solutions as well. Their position will therefore drop into yet another commodity CPU offering. In the AI accelerator space we will witness something similiar. Nvidia has created a platform and earns tons of money with it by combining and optimizing SW+HW. Big Tech is great at SW but not yeat at HW. So the only logical thing to do is getting better at HW. All large Tech companies are working on their own accelerators and they will build their platform around it to compete with Nvidia and locking in customers all the same way. The primary losers in all of this will be HW only vendors without a platform, hoping that Big Tech will support them on their platforms. Amazon and Google have already shown today that they have no intention to support anything besides their platform and Nvidia (which they only must due to customer demand).
binkHN 2y ago
> It appears AMD initial strategy is courting the HPC crowd and hyperscaler... I don't agree with this at all! Give me something that I can easily prototype at home and then quickly scale up at work!
lostmsu 2y ago
I doesn't make sense because they can market to both at the same time.

antupis 2y ago

That is wrong move personally would start from localllm/llama folks who crave more memory and build up from there.

sangnoir 2y ago
Seeing that they don't have a mature software stack, I think for now AMD would prefer one customer who brings in $10m revenue over 10'000 customers at $1000 a pop.

landryraccoon 2y ago

They’re making the wrong strategic play. They will fail if they go after the highest margin customers. Nvidia has every advantage and every motivation to keep those customers. They would need a trillion dollars in capital to have a chance imho. It would be like trying to go after Intel in the early 2000s by trying to target server cpus, or going after the desktop operating system market in the 90s against Microsoft. Its aiming for your competition where they are strongest and you are weakest. Their only chance to disrupt is to try to get some of the customers that Nvidia doesn’t care about, like consumer level inference / academic or hobbyist models. Intel failed when they got beaten in a market they didn’t care about, i.e mobile / small power devices.

acchow 2y ago
> They would need a trillion dollars in capital to have a chance imho. All AMD would really need is for Nvidia innovation to stall. Which, with many of their engineers coasting on $10M annual compensation, seems not too far fetched
- sangnoir 2y ago
  AMD can go toe to toe with Nvidia on hardware innovation. What AMD had realised (correctly, IMO), is that all they need is for hyperscalers to match/come close to Nvidia on software innovation on AMD hardware - Amazon/Meta/Microsoft engineers can get their foundation models running on M1300X well enough for their needs - CUDA is not much of moat in that market-segment where there are dedicated AI-infrastructure teams. If the price is right, they may shift some of those CapEx dollars from Nvidia to AMD. Few AI practitioners - and even fewer LLM consumers - care about the libraries underpinning torch/numpy/high-level-python-framework/$LLM-service, as long as it works.
Certhas 2y ago
This is a common sentiment, no doubt also driven by the wish thay AMD would cater to us. But I see no evidence that the strategy is wrong or failing. AMD is already powering a massive and rapidly growing share of Top 500 HPC: https://www.top500.org/statistics/treemaps/ https://www.top500.org/statistics/treemaps/ AMD compute growth isn't in places where people see it, and I think that gives a wrong impression. (Or it means people have missed the big shifts over the last two years.)
- Jlagreen 2y ago
  Super computers are in 95% cases government funded and I recommend that you check in conditions for tenders and how government has check on certain condition in buying. That isn't a normal business partner who only looks at performance, there are many more other criteria in the descision making. Or let me ask you directly, can you name me one enterprise which would buy a super computer and wait 5+ years for it and fund the development of HW for it which doesn't exist yet? At the same time when the competition can deliver a super computer within the year with an existing product? No sane CEO would have done Frontier or El Capitan. Such things work only with government funding where the government decides to wait and fund an alternative. But AMD is indeed a bit lucky that it happened or otherwise they wouldn't been forced to push the Instinct line. In the commercial world, things work differently. There is always a TCO calculation. But one critical aspect since the 90s is SW. No matter how good the HW is, the opportunity costs in SW could force enterprises to use the inferior HW due to SW deployment. If vision computing SW in industry is supporting and optimized for CUDA or even runs only with CUDA then any competition has a very hard time penetrating that market. They first have to invest a lot of money to make their products equally appealing. AMD makes a huge mistake and is by far not paranoid enough to see it. For 2 decades, AMD and Intel have been in a nice spot with PC and HPC computing requiring x86. It basically to this date has guaranteed a steady demand. But in that timeframe mobile computing has been lost to ARM. ML/AI doesn't require x86 as Nvidia demonstrates by combining their ARM CPUs into the mix but also ARM themselves want more and more of the PC and HPC computing cake. And MS is eager to help with OS for ARM solutions. What that means is that if some day x86 isn't as dominant anymore and ARM becomes equally good then AMD/Intel will suddenly have more competition in CPUs and might even offer non-x86 solutions as well. Their position will therefore drop into yet another commodity CPU offering. In the AI accelerator space we will witness something similiar. Nvidia has created a platform and earns tons of money with it by combining and optimizing SW+HW. Big Tech is great at SW but not yeat at HW. So the only logical thing to do is getting better at HW. All large Tech companies are working on their own accelerators and they will build their platform around it to compete with Nvidia and locking in customers all the same way. The primary losers in all of this will be HW only vendors without a platform, hoping that Big Tech will support them on their platforms. Amazon and Google have already shown today that they have no intention to support anything besides their platform and Nvidia (which they only must due to customer demand).

binkHN 2y ago

> It appears AMD initial strategy is courting the HPC crowd and hyperscaler... I don't agree with this at all! Give me something that I can easily prototype at home and then quickly scale up at work!

lostmsu 2y ago

I doesn't make sense because they can market to both at the same time.