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Why Nvidia Keeps Winning
- TeeWEE 3y agoSummary from ChatGPT: "The main reasons for Nvidia's success, are its creation of a GPU ecosystem, lack of significant competitors, and the benefits derived from its compute and software ecosystem."
- jacooper 3y agoBecause AMD is sleeping.
- FredPret 3y agoThey have working Linux drivers. I tried setting up Tensorflow with an AMD card once. I send a thousand dollars to Nvidia after a week
- ChatGTP 3y agoThey might have them, but they're closed source and when there are issues, you're completely fucked.
- eropple 3y agoAs opposed to the everyday case with AMD, where you have adventures all the time?
- FredPret 3y agoThey both need to get this 1000% better stat. I think it's probably the best ROI the CEO of AMD can get - put a team of engineers on Linux drivers full time, increase your AI market share... and triple your market cap.
- unmole 3y agoI've had no problems with Nvidia Linux drivers themselves in the last 15 years or so. Yes, they don't play well with the rest of the ecosystem. Using Optimus laptops was a nightmare but you could still get hardware acceleration if you needed it, with performance on par with Windows. ATI on the other hand is a choose your own adventure kind of a deal.
- ChatGTP 3y agoWe’ll I did have problems, so there ?
- wisty 3y agoIf the GCC compiler has an issue, I'm in a lot of trouble too, even though it's open source. I guess I could scan the code and figure out any minor problems (or figure out why I was misusing it) but I'm not an expert in compilers, or even at tensor programming. Obviously it would be better if they're open source, since someone would be able to fix them, and it helps to know how your tools really work. But a better closed source driver is probably the right tool for most problems.
- ecshafer 3y agoI love open source, but this is just isn't true. If you are a company, and you find an actual problem with Nvidia, and you just spent some multiple of $100k or more on graphics cards for a cluster. You are able to get an ear and get that driver fixed.
- shmerl 3y agoWorking is moot. Their Linux support is the worst among all GPU makers.
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- babypuncher 3y agoFor this particular use case, Nvidia works better on Linux than AMD
- shmerl 3y agoAs soon as you are out of what they care about, your support will become abysmal. And they don't care about modern desktop use case (such as they didn't have Wayland support for decades). So if you are a Linux user - simply avoid Nvidia. They don't care about you.
- mkl 3y ago> Wayland support for decades It's only 15 years old!
- shmerl 3y agoAnd Nvidia did nothing to support until like a just a few years ago and even now their support is basically half cooked. If it takes them that long, it's very clear they don't care about Linux in general. Same thing is reflected in them not working with upstream kernel.
- jcranmer 3y agoNvidia's Linux compute solution is far better than AMD's compute solution, and their Linux graphics solution is far worse than AMD (and Intel)'s graphics solution. So the recommendation comes down to why you want that GPU.
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- thescriptkiddie 3y agoNvidia is famous for having the worst Linux drivers. Linus himself told Nvida to go fuck themselves on stage.
- mardifoufs 3y agoCUDA on Linux just works. And works very well. If anything most CUDA workloads run on Linux machines, and it's completely pain free compared to setting up ROCm even on Linux.
- mike_hearn 3y agoNo, they are "famous" for having the best drivers but not open sourcing them. NVIDIA's drivers are practically the same size as an OS anyway. Arguably they are an OS, for the GPU instead of the CPU. So it's not a huge surprise they don't give it all away for free, especially as software is a competitive advantage for them.
- josefx 3y agoFrom what I understand that was about them not cooperating with the kernel devs. and that their driver was a black box that had to interact with half the kernel didn't help. Driver wise my worst experiences where all solidly in the ATI/AMD binary camp, with the constant need to exorcise nouveau from various systems second.
- jjoonathan 3y agoBecause AMD's gpgpu offerings have been egregiously buggy for at least a decade. Now that AMD has money I'm hoping they can turn this around, but Geohotz hitting driver crashes from a loop around a demo suggests to me that things are still pretty bad.
- Const-me 3y agoYou don’t need these buggy AMD-specific technologies to leverage the AMD’s GPGPU hardware. Compute shaders are used by videogames for a decade now. For example, GTA5 from 2013 already used compute shaders to render stuff. At least in my experience, the tech is very reliable regardless of GPU vendor. I haven’t tested that, but I would expect on AMD hardware Vulkan compute to be comparable by now. After all, people bought couple millions of steam decks which uses Vulkan for the native GPU API, and emulates D3D on top of that.
- willis936 3y agoThat aligns closely with when AMD bought ATI. Before that ATI had a long history of egregiously buggy GPGPUs. I can't say what's gone wrong with Radeon, but I can say it's been going wrong for nearly my entire life.
- pier25 3y agoI've been very happy with an 6750X for gaming. Performa great for the price and I've had zero issues.
- EtienneK 3y agoSame here with my 6900XT. Honestly, I am amazed with all the complaints on here regarding AMD crashing. I have not seen this once while owning my card! All the while my friends on Discord keep complaining about their Nvidia cards while we’re playing Warzone.
- ccheney 3y agoGeohot is working w/ AMD and essentially pleading with them to fix their driver stacks - check out his interview on Latent Space
- karim79 3y agoI'm really disturbed by all of this - it doesn't quite check out with my that there are some quite capable players with kagillions of dollars who haven't managed to, or more disturbingly, won't even put up the investment nor effort to break into the AI shenanigans space within the GPU market.
- Solvency 3y agoWhat exactly is "disturbing"?
- karim79 3y agoThat nobody else seems to be trying hard enough, despite being well-funded and respectable companies. And until somebody does, we're stuck with NVidia/Cuda or half-working stuff that's way more hassle to prototype or build a product from.
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- pavelstoev 3y agoTo answer the question why there is not much competition, I would like to point out that the required expertise is very rare. Not specifically the chip design expertise but the expertise spanning both chip hardware and low-level software for such chip-specific hardware, that is all necessary to create the compilers, the frameworks and libraries and which can also plug-in well with the existing AI/ML ecosystem such as PyTorch.
- Eji1700 3y agoI don't think you understand just how insanely difficult it is to break into that market. There's a lot that goes into GPU's that makes it a very difficult industry to get going in. Even with apple money or something like that, it's a losing prospect because in the time it'll take you to get up and off the ground (which is FOREVER) your competition will crush you.
- re-thc 3y agoNvidia have had their "failures" e.g. with CPUs and SOCs. Tegra hasn't been going all that well except for Nintendo switch and some cars.
- andrewstuart 3y agoA big reason that Nvidia keeps winning is that AMD doesn’t bother to compete. Competition means giving customers exciting, fast, low cost GPUs. Nvidia, as #1, no longer needs to compete and has stopped winning via low cost, high performance GPUs. This opened a giant opportunity for AMD GPUs to give those things to consumers and start winning against Nvidia. But instead AMD has just followed Nvidia into making slow, uncompetitive GPUs at high prices. So in a real way AMD is keeping Nvidia at #1.
- didip 3y agoHard agree. AMD keep sleeping at the helm and there are no other competitors.
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- mochomocha 3y ago> But instead AMD has just followed Nvidia into making slow, uncompetitive GPUs at high prices. I'm curious: do you use GPUs? It's hard to take this claim seriously. Yes NVIDIA GPUs are expensive, but I don't think we live in the same matrix when you claim that their GPUs are slow and uncompetitive... Unless you have an alternative in mind, in which case I'm all ears.
- selectodude 3y agoYeah I'm not sure how a GPU can be both slow and uncompetitive and also the best GPU available at any price. That would imply that they're extremely competitive. Some people just have an ax to grind and will contort their facts to agree with preexisting thoughts and feelings. I think it's called cognitive dissonance.
- photonerd 3y ago> the best GPU available at any price That’s… very debatable. Don’t get me wrong, they’re definitely competitive at all levels but AMD absolutely is too & very arguably is better in some cases.
- rootusrootus 3y agoAt this point Apple is more of a competitor to Nvidia than AMD, at least when it comes to AI.
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- heliophobicdude 3y agoI recently found an article by Apple explaining how they optimized a transformer to work on Apple Neural Engine [1]. This was before their recent hardware refresh with 192 GB unified memory upgrade. Apple could have a real chance to push their boxes as an alternative to dedicated GPUs. 1: https://machinelearning.apple.com/research/neural-engine-transformers https://machinelearning.apple.com/research/neural-engine-tra...
- pjmlp 3y agoApple doesn't sell chips, and they don't care about servers other than powering XCode Cloud, or iCloud.
- taeric 3y agoI'd love to see more discussion on the assertion that Google is the only real competitor to Nvidia. I get the angle, but it still feels weird to think of them as competitors. Really odd to think of with how Google appears to be struggling with their AI story at the moment. It also wouldn't hurt if Google showed anywhere near the discipline that Nvidia has shown over the years. About the only thing Nvidia has done to upset anyone, is to not have open source drivers. Even there, though, many folks are far happier with their closed drivers than they are many of the open alternatives.
- 8note 3y agoAt that point, Amazon would be up there on top competitors to Nvidia. Google, Amazon, and apple aren't really selling people onsite ai inference or training, so I don't think they're actually competitors.
- sounds 3y agoI think the article is making the (reasonable?) assumption Google's search and advertising will use Google's own in-house Bard or something similar. The article mentioned something about Google having the full vertical stack: hardware, networking, software, ML model, product, and the users. As of right now, Bard is separate. Or if Google has integrated ML models into search and ads, it hasn't been widely discussed.
- taeric 3y agoI think I agree, but the article is definitely making the push that Google is a competitor.
- shanghaikid 3y agoI miss the company "ATI".
- a_bonobo 3y agoI miss 3dfx :) But the 3dfx remnants got swallowed by NVIDIA, so in a way, it lives on. It's funny that ATI got swallowed by AMD.
- annoyingnoob 3y agoI remember when ati.com sold little white boxes of fake poop. https://web.archive.org/web/19990221230513/http://aux.ati.com/ https://web.archive.org/web/19990221230513/http://aux.ati.co...
- ec109685 3y agoThe US is putting restrictions on this, so it feels like a short term workaround: “Jordan Schneider: Chinese firms, however, are not restricted in accessing cloud services overseas. Nothing is stopping a Chinese company from buying top-of-the-line Nvidia compute from AWS. Does that alter the dynamic?”
- xyzzy123 3y ago... where their workloads can be surveilled.
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- DonnyChen 3y ago[dead]
- synergy20 3y agoIt's not that Nvidia 'keeps winning', Nvidia failed mobile computing, failed embedded computing, had no market share in the server market or data centers, was left in the niche market of gaming as a companion to PC and was not that impressive all along. then its parallel GPU got "lucky", first the bitcoin mining, then the AI. it probably did not expect and plan for this, to some extent, it got super lucky. credit must be given to its CUDA ecosystem and the ability to better itself when chances knocked its door, it so far left all competitors in the dust, its showtime arrived, finally.
- bigdict 3y ago> it probably did not expect and plan for this You'll find out when you read TFA!
- brigadier132 3y ago> then its parallel GPU got "lucky", first the bitcoin mining, then the AI. it probably did not expect and plan for this, to some extent, it got super lucky. I feel like saying they got "lucky" after trying and failing in multiple other endeavors requires a special definition of luck. If someone rolls a 6 sided die six times and they roll a six once did they get lucky?
- hsbauauvhabzb 3y agoBeing good also has the facade of luck, every venture is a gamble none of which are guaranteed, but putting yourself in the most optimal positions (including diversifying) will result in some successes and some failures. You don’t end up with a $1t valuation based purely on luck.
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- nradov 3y agoFor corporations, just staying alive that long without a huge hit is very lucky. Look how many other chip companies failed or were acquired cheaply during that period.
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- smiley1437 3y agoI mean, silicon aside, isn't it all basically CUDA lock-in? CUDA is the defacto parallel computing platform, and exciting tech moves VERY fast with early mover advantage - so no researcher\computer scientist is going to bother learning another platform or risk\waste time\effort on their stuff breaking when ported to OpenCL\AMD. Unless a miracle happens, any new parallel-computing requirement that seizes the popular imagination in the next decade (or more) will done in CUDA.
- randmeerkat 3y ago> I mean, silicon aside, isn't it all basically CUDA lock-in? Everything is and always will be some form of lock-in. Look at what’s happened with CentOS or even Ubuntu. Even what was solid open source choices before have turned into some form of exploited lock-in. I’ve come to the realization that it’s impossible to optimize out of lock-in, instead it’s better to cost optimize for current best practices while continuously running test applications on different platforms and technologies when you have the resources to do so.
- empiricus 3y agoThe sad part is that most of the people are using a higher level API like PyTorch. So AMD or Intel just need a simple low level API to access their HW, and then write and tune some kernels for PyTorch (and I suspect the community or AI will gladly help with the tuning). So basically there does not seem to be a real CUDA lock-in, it's just the fact that the competition still seems unable to do even this.
- wilonth 3y agoApple was able to break the CUDA lock-in with their Metal computing api (MPS), in no time at all. Within months, now the major AI libraries like Pytorch and Tensorflow all support Apple GPU without a hitch. What's taking AMD so long? They just can't do software I guess?
- Eridrus 3y agoThe amount of money being spent on ML compute is pretty high. If it stays high, cost will be a relevant axis that others can compete on. GPUs are also not super available atm. We'll see if this is a temporary issue or one that persists for years. If you can't get A100s, you'll try the AMD/TPU competitors.
- superkuh 3y agoBecause their firmware actually does what the docs say it will instead of segfaulting when people attempt to use it for anything outside of gaming.
- semireg 3y agoI thought it was strange that the history of GPUs jumped from graphics to AI with nary a mention of crypto, but then I realized this was China-centric where this kind of GPU use-case is against the law.
- nologic01 3y agoIn the post Moore's law era my hunch is that the eventual "winner", if there is one, will be decided based on software not hardware. So far the main use cases that have pushed the computational performance envelope were hype-driven. In such a climate people will just accept developing costs, lock-in risks etc. as the cost of entering the bubble early enough. In "normalized" conditions the focus shifts back to developer and user productivity and cost-efficiency. We are slowly entering the commoditised HPC era, but HPC was always a volatile domain precisely because of its highly specialized nature. The broad, general purpose use and (relatively) easy set of tools of the x86 cpu era provided a stability that is unlikely to repeat. The vector accelerator market is (conceptually) for the CPU vendors to lose because they can create a more productive development environment that unifies CPU/GPU. To paraphrase, users dont care about GPU, they care about performant applications.
- hotdogscout 3y agoNVidia for one lobbies developers into using their tools which AMD refuses to do.
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- DeathArrow 3y agoMeanwhile AMD did some powerpoints about how heterogeneous computing is going to rule the world.
- firefoxkekw 3y agoThey just keep adding support to what the market demands, adding FP8 to the H100s and 40xx series was such a good move, their tooling is top notch, like what is the alternative of rapids in amd? Their drivers are so stable that you can rely on them not crashing in projects that need to train for weeks & months, sxm is another big win of nvidia. They also have their skin in the game and do a lot of research in ds. A single 4090 can do 0.66 PFLOPS which is mind blowing to me, borderline having in your room a supercomputer of the 200xs for a few k$. https://ourworldindata.org/grapher/supercomputer-power-flops https://ourworldindata.org/grapher/supercomputer-power-flops Edit ---- Obviously biased towards enterprise users, no clue how good they are in the gaming market.
- 123456780000 3y ago[flagged]
- DeathArrow 3y ago> This undermines Jensen’s claim that if we don’t let Chinese firms buy semiconductors, we’re going to fall behind. Given enough time and determination China will catch up in semiconductors. And after that, they will use their scale to try to win the game.
- DeathArrow 3y agoIsn't AMD ROCm a compatible CUDA replacement? Why aren't they able to compete with Nvidia?
- arc-in-space 3y agoROCm is a disaster. It doesn't even work with most AMD GPUs, and the software is awful(difficult to setup, very poorly supported). AMD keeps occasionally releasing new stuff in the GPGPU space, then leaves it unsupported and continues to fall further behind Nvidia.
- DeathArrow 3y agoNvidia also tried [0] to make an x86 CPU but Intel succeeded in preventing that. [1] [0] https://semiaccurate.com/2011/08/05/what-is-project-denver-based-on/ https://semiaccurate.com/2011/08/05/what-is-project-denver-b... [1] https://www.anandtech.com/show/4122/intel-settles-with-nvidia-more-money-fewer-problems-no-x86/2 https://www.anandtech.com/show/4122/intel-settles-with-nvidi...
- EVa5I7bHFq9mnYK 3y agoThanks for the insight, bought nvda puts for november. A typical crazy bubble.
- m3kw9 3y agoJensen made good bets on AI, and of course without OPenAI breakthru it would have delayed them winning this big, just a delay
- Const-me 3y agoCUDA was a great technology before 2018. Then in 2018, they prohibited usage of GeForce GPUs in data centers: https://www.datacenterdynamics.com/en/news/nvidia-updates-geforce-eula-to-prohibit-data-center-use/ https://www.datacenterdynamics.com/en/news/nvidia-updates-ge... And during 5 years which followed, they have reached the point where for many use cases nVidia is dramatically worse value compared to competitors. On my day job I do CAM/CAE, we compute a lot of FP64 numbers. Because we use D3D tech for GPGPU, we recently bought some computers with AMD 7900 XTX. These GPUs were sold for about $1000. An nVidia equivalent is L40: the AMD is 1.459 TFlops and 0.96 TB/sec memory bandwidth, the nVidia is 1.414 TFlops and 0.864 TB/sec memory bandwidth, but the nVidia is sold for about $9000. That’s an order of magnitude difference in cost efficiency.
- braza 3y agoIt’s really disturbing for me the possibility that a that a hardware vendor could enforce that on court. Does someone knows what’s the rationale for that from Nvidia?
- Const-me 3y agoI think it’s money. nVidia is selling same chips on different boards for different prices. An example from the current generation, $800 GeForce 4070 Ti, and $2500 L4 are based on the same chip. The difference between these two cards is amount of VRAM, some settings which control clock frequencies, and these legal/software limitations. Without the legal limitations, people who need to compute stuff which fits in 12GB VRAM would only pay them $800 for the GeForce model.
- P_I_Staker 3y agoI agree the cost difference being substantial, but something seems off here. I think you can buy nVidia cores that can beat anything AMD has for ~$1500-2000. That is gaming focused, but it makes me extremely skeptical of the overall numbers. If the AMD chip really is better for your job, that's not that crazy a claim, but it make no sense that nVidia wouldn't have something for 1.5-2x as much. This seems to be the going rate, currently. If you're getting comparable speed for 1/9 the cost, I don't think that product would exist for very long. I've been looking at graphics cards and nVidia clearly beats AMD in every category with around a 50-100% markup.
- Jordanpomeroy 3y agoFrom HPC industry experience with Nvidia, my take is that they are the smartest guys in the room. They’re solution architects that help customers implement and optimize CUDA area by far the best SA’s I’ve ever worked with. If that hiring ethos is pervasive they’ll keep winning.