For AI chips... also probably not, unless AMD can compete with CUDA (or CUDA becomes irrelevant)
I think that AMD could do it, but they choose not to. If you look at their most recent lineup of cards (various SKUs of 9070 and 9060), they are not so much better than Nvidia at each price point that they are a must buy. They even released an outright bad card a few weeks ago (9060 8 GB). I assume that the rationale is that even if they could somehow dominate the gamer market, that is peanuts compared to the potential in AI.
And for AI, CUDA is already becoming less relevant. Most of the big players use chips by their own designs: Google has its TPUs, Amazon has some in house designs, Apple has it's own CPU/GPU line and doesn't even support anything nvidia at this point, MS do their own thing for Azure, etc.
You are basically making the Intel will stay big because Intel is big for Nvidia. Except of course that stopped being true for Intel. They are still largish. But a lot of data centers are transitioning to ARM CPUs. They lost Apple as a customer. And there are now some decent windows laptops using ARM CPUs as well.
While on Windows it has been hit and miss with their SDKs and shader tooling, anyone remembers RenderMonkey?
So NVidia it is.
I'm team AMD for CPU (currently waiting for consumer X3D laptops to become reasonably priced).
But for GPU, if only for the "It Just Works" factor, I'm wedded to NVIDIA for the foreseeable future.
cause the team they have the last decade is clearly retarded.
they played that part beautifully in the past decades for Intel
AMD stubbornly refuses to recognise the huge numbers of low- or medium- budget researchers, hobbyists, and open source developers.
This ignorance of how software development is done has resulted in them losing out on a multi-trillion-dollar market.
It's incredible to me how obstinate certain segments of the industry (such as hardware design) can be.
AI research used to be fringe and not well funded.
Back in those days, 99.9% of hardware was Xeon.
AMD is doing just fine, Oracle just announced an AI cluster with up to 131,072 of AMD's new MI355X GPUs.
AMD needs to focus on bringing rack-scale mi400 as quickly as possible to market, rather than those hobbyists always find something to complain instead of spending money.
this guy gets it - absolutely no one cares about the hobby market because it's absolutely not how software development is done (nor is it how software is paid for).
we're talking about the majority of open source developers (I'm one of them). if researchers don't get access to hardware X, they write their paper using hardware Y (Nvidia). AMD isn't doing fine because most low level research on AI is done purely on CUDA.
I am really sympathetic to the complaints. It would just be incredibly useful to have competition and options further down the food chain. But the argument that this is a core strategic mistake makes no sense to me.
AMD has demonstrably not even acknowledged that they needed to play catch-up for a significant chunk of the last 20 years. The mistake isn't a recent one.
There are plenty of research institutions that can easily spend >$250k on computational resources. Many routinely spend multiples of that volume.
They'll be fine.
Look at China. A couple of years ago people thought people in China weren't doing good AI research, but the thing is, there's good AI research from basically everywhere-- even South America. You can't assume that institutions can spend >$250k on computational resources.
Many can, but many can't.
AMD is very far behind, and their earnings are so low that even with a nonsensical pe ratio they’re still less than a tenth of nvidia. No, they are not doing anywhere near fine.
Are hobbyists the reason for this? I’m not sure. However, what AMD is doing is clearly failing.
If you design software for N00000 customers, it can't be shit, because you can't hold the hands of that many people, it's just not possible. By intending to design software for a wide variety of users, it forces you to make your software not suck, or you'll drown in support requests that you cannot possibly handle.
Honestly, if they "don't have the resources to satisfy N00000 customers", they better get them. That will teach them in the hard way to work differently.
If you don't need 8, then that's exactly why we offer 1xMI300x VM's.
We see it now with 8x UBB and it will get worse with direct liquid cooling and larger power requirements. Mi300x is 700w. Mi355 is 1200w. Mi450 will be even more.
Certainly amd should make some consumer grade stuff, but they won’t stop on the enterprise side either. Your only option to get super computer level compute, will be to rent it.
That said, I am confident that Nvidia will continue serve those of us who want our own hardware.
But 355 has fp4/6 added in, which until udma comes out, likely won’t get emulated.
It is fine if you dont need the features of newer hardware, but if you do… then desktop won’t help you.
https://images.nvidia.com/aem-dam/Solutions/geforce/blackwel...
FP4 is given a full page advertising it while FP6 support in “RTX Blackwell” is a footnote.
[1] This is the AMD Instinct MI350:
https://www.servethehome.com/this-is-the-amd-instinct-mi350/
https://www.tomshardware.com/pc-components/gpus/amd-says-ins...
The table linked by you is good for revealing the meaning of a part of the many AMD code names.
AMD went down the wrong path by focusing on traditional rendering instead of machine learning.
I think future AMD consumer GPUs would go back to GCN.
AMD has not disclosed how they will achieve the unification, but it is far more likely that the unified architecture will be an evolution of CDNA 4, i.e. an evolution of the old GCN, than an evolution of RDNA, because basing the unified architecture on CDNA/GCN, will create less problems in software porting than basing it on RDNA 4 or 3. The unified architecture will probably take some features from RDNA only when they are hard to emulate on CDNA.
While the first generation of RDNA has been acclaimed for having a good performance increase in games over the previous GCN-based Vega, it is not clear how much of that performance increase was due to RDNA being better for games and how much to the fact that the first RDNA GPUs happened to have double-width vector pipelines in comparison with the previous GCN GPUs, thus double throughput per clock cycle and per CU (32 FP32 operations/cycle vs. 16 FP32 operations/cycle).
It is possible that RDNA was not really a better architecture, but omitting some of the hardware that was rarely used in games from GCN allowed the implementation of the wider pipelines that were more useful for games. So RDNA was a better compromise for the technology available at that time, not necessarily better in other circumstances.
pella•7mo ago
kristianp•7mo ago
See https://arxiv.org/abs/2402.17764
treesciencebot•7mo ago
I will doubt that they will be able to reach %60-70 of the FLOPs in majority of the workloads (unless they hand craft and tune a specific GEMM kernel for their benchmark shape). But would be happy to be proven wrong, and go buy a bunch of them
pella•7mo ago
Tinygrad:
" https://x.com/__tinygrad__/status/1935364905949110532LeonM•7mo ago
Don't get me wrong, I think it's impressive what he achieved so far, and I hope tiny can stay competitive in this market.
[0] https://news.ycombinator.com/item?id=36193625
ryao•7mo ago
imtringued•7mo ago
I'm not quite sure why he decided to pivot to datacenter GPUs where AMD has shown at least some commitment to ROCm. The intersection between users of tinygrad and people who use MI350s should essentially be George himself and no one else.
roenxi•7mo ago
George is just some dude and I doubt AMD paid him much attention anywhere through this saga, but AMD had screwed up to the point where he could give some precise commentary about how they'd managed to duck and weave to avoid the overwhelming torrent of money trying to rush in and buy graphics hardware. They should make some time in their busy schedules to talk with people like that.
lhl•7mo ago