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Nvidia announces financial results for second quarter fiscal 2024

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Re: Nvidia announces financial results for second quarter fiscal 2024

#401
post #318

Earlier quoted context omitted.

It’s because CPUs tend to be fundamentally limited in the ways they can efficiently utilize transistors to scale performance, by things like cache latency, reorder depth, branch prediction, etc. While gpus have always been god’s strongest soldier for putting transistors on silicon scalably. They were the perfect machine for a world where transistors per dollar doubled every 18 months. On the other hand now that it’s…

So if they're running into hardware fab limits, how does running deep learning on that limited hardware equate to a doubling of price? I don't quite follow the logic there? Yeah the upscaling is nice, but I dunno about $1200 nice... It was cool when they instead focused on things like creating mobile smaller versions of the cards with laptop level power draws, or better cooling systems that weren't as noisy etc. Whil…

> So if they're running into hardware fab limits, how does running deep learning on that limited hardware equate to a doubling of price? I don't quite follow the logic there? Yeah the upscaling is nice, but I dunno about $1200 nice...

Because moore's law wasn't just about transistor count but about the economic impact of exponential growth in transistors-per-$. In a world without moore's law, using more transistors will result in a higher-cost product. If you want to hold product cost fixed, or even contain the cost spiral, you need to do more with the same amount of transistors - performance-per-transistor is the metric that matters now.

AMD and NVIDIA have already stripped down their pure-raster implementation as far as they can go, with RDNA1 and Maxwell respectively. Maxwell actually cut too far (software scheduling, "minimal" DX12 support, etc) honestly. So where do you keep making perf/tr gains after that?

The gaming world has already pretty well settled on TAA (although some people will never accept it) and upscaling is already common in the console world. So, do TAA upscaling better such that you get the performance gains but not the reduction in visual quality that usually comes with it.

Tensor makes up a relatively small amount of die area (5.9% of total Turing die area, based on comparisons between Turing Major/RTX and Turing Minor/GTX SM engine die shots). And that gets you to about 30% faster than FSR2 for a given level of visual output quality. So the perf-per-transistor metric increases. Also, unlike a fixed-function accelerator, it can be used for all kinds of other stuff too. It's basically a whole programmable sub-processor, an accelerator for your accelerator.

https://www.reddit.com/r/hardware/comments/baajes/rtx_adds_1...

Now, why ML as opposed to just running it on shaders? Same logic as adding an AVX unit, math density is a lot higher and it can do a lot of work for applications that are specifically tailored to it. DLSS2 uses a relatively standard TAAU (similar to FSR2) but determines the weighting of the samples using a neural net. This produces a lot higher quality than a procedural algorithm currently can - especially under "bad conditions" like higher degrees of upscaling, low framerate/limited sample count, or temporally unstable/high-temporal-frequency areas of the image.

http://behindthepixels.io/assets/files/DLSS2.0.pdf

https://raw.githubusercontent.com/NVIDIA/DLSS/main/doc/DLSS_...

FSR2 does ok at 4K quality mode, but at 1440p and (especially) 1080p output resolutions and in performance modes it does much worse. FSR2 quality 1080p is more like DLSS2 performance mode or maybe balanced mode, so NVIDIA gets more speedup at a given level of visual quality. And DLAA can produce a better-than-native image when running with a native input quality.

The neural weighting just is a lot more efficient at using its samples, it understands what is going on in the scene (moving edges/occlusion etc) and can extract a higher signal-to-noise ratio from the samples and the textures. It's like an op-amp, the ratio of input:output pixels is the "gain factor", and FSR2 and other traditional TAAU algorithms are simply noisier at any given level of gain, whether that's unity or extreme gain, and have other edge-cases like turn-on threshold (bad performance with low samples). ML is the "schottky diode" of graphics amplification (dangerously mixed metaphor, lol), it's simply a lot more agile at shaping the signal than what came before.

(and while on paper plenty of people have argued that procedural programs should be able to do anything ML can, it's not like AMD and others haven't tried to improve TAAU with FSR2, and many others before them. DLSS2 is better, just like LLMs and Stable Diffusion are a lot better than procedural algorithms in their own niches.)

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All of this exists completely orthogonally to actual wafer costs or packaging or other things. Packaging may boost that transistors/$ metric a little bit but that just gives you a little more to play with. It does allow you to make chips with twice the transistors at twice the cost and have them yield at high rates, but fundamentally 2x400mm2 is still 800mm2 of silicon even if you yield at 100% - you're using more wafer, which drives up costs. Wafer costs have been increasing nearly as fast as density (and predicted to match/pass at 3nm) but there has been a small gain in tr/$, certainly nowhere near the rate of moore's law days. But if wafers cost 8x what they did for 28nm, and are continuing to increase at ~50% per generation, and you keep using more wafer area to compensate for slowing shrinks, then costs will go up (even more than they have).

There is no direct link between "running deep learning" and costs going up. That is just happening independently and affects AMD too, even when they didn't go in on deep learning. TSMC prices keep going up (as do their margins, even now) and even if they went to zero, the design+validation costs are still going up too. A lot of these costs are driven by hard physics problems and not just TSMC profit margin (although it doesn't help).

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> It was cool when they instead focused on things like creating mobile smaller versions of the cards with laptop level power draws, or better cooling systems that weren't as noisy etc.

I think a 30% performance boost at native visual quality, without power increase is pretty cool. Don't laptops benefit from having 30% higher perf/w just from turning on a setting? And Ada itself is a ~60% perf/w increase over previous generations too.

Like Ada is one of the most efficiency-focused generations ever, much moreso than Ampere or Turing with their trailing nodes. DLSS just stacks on top of this - and unlike FSR2, NVIDIA doesn't fall apart at 1080p resolutions that laptops tend to be using.

Cost is higher than people want, but on the other hand (a) that's going to be the reality unless there is a breakthrough in transistors-per-$, you can't make a fixed number of transistors infinitely fast, there is some asymptotic limit. And (b) people are cherrypicking favored examples or comparing against trailing-node products that had larger dies on slower, less energy efficient nodes to keep costs down.

GTX 970 at $329 was an outlier and the lowest x70 product of all time, on a trailing node (28nm again after 20nm fell through). GTX 670 launched at $399 for a similarly sized die over 10 years ago. GTX 1070 launched at $449 7 years ago with another similarly-sized (~300mm2) die. Turing, Ampere, and Maxwell were all abnormally cheap due and large due to the trailing-node but you paid for this with worse efficiency. There has never been a x70 product launched at $299 and you are welcome to check this!

First x70 product: https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_proces...

And yes I think the consensus is that nodes like 8nm probably are "good enough" especially if they are much cheaper, especially at the low end where PHY size is becoming a problem. PHYs don't shrink, so you can't scale a product arbitrarily small - the logic may shrink by 70% but those PHYs are just as big as ever. So there is a de-facto "minimum die size" that is ever worth producing, because there is a fixed PHY area that you simply cannot eliminate. And in a world where wafer costs are going up, that area costs more and more every generation.

A 3060 Ti 16GB wouldn't even need clamshell (it has 8 PHYs, 8x2GB per module=16GB) and could probably have hit $299 or $329 launch cost, if NVIDIA had gone down that road. And it's Good Enough for 1080p, and avoids some weird compromises that shake out of the need to trim PHY area.

AMD already did exactly this with the 7600 - which is held back on 6nm (N7 family) rather than using N5P (N5 family) like the rest of the RDNA2 lineup. Why? Cost.

Re: Nvidia announces financial results for second quarter fiscal 2024

#402
post #157

Earlier quoted context omitted.

Tech design and development seems, to me at least, pretty much naturally opposed to the "being kept in check with competition" state - as design isn't really a cost that scales per-unit, the company that sells slightly more can afford to put more into development at the same per-unit margin, which snowballs. At some point, they own the entire market - or enough that they functionally control it, and start leveraging…

At the end of the day, what nvidia does is just producing IP. All manufacture is by other companies. This means that nvidia capital is spend on testing/development infrastructure and creative labor. So, you don’t need monopoly breaking to handle nvidia if it keeps growing, but instead rethink IP laws. Testing infrastructure is less capital investment than production manufacture. (See ASML and TSMC beeing booked), and…

I think Intel having in-house manufacturing was one of the big causes of them getting "Too fat and slow to respond" - from the outside much of their fall from grace was due to massively delayed production improvements rather than designs and IP. As far as I can see, the architectures were pretty much done and ready to go, just the expected targeted process missed it's mark.

With Nvidia and other GPU competitors being IP-focused, effectively outsourcing all this "manufacturing stuff" (to the same 3rd party much of the time), that's one less thing for them to keep up with, and one less think that'll hurt if they do start "falling asleep". I can't see this happening to Nvidia in quite the same way right now. My point was that not having manufacturing makes advantages of consolidation larger, not smaller.

I wonder what would have happened if Intel realized it's manufacturing wasn't hitting targets and "quickly" added TSMC as an option, would AMD even have had a chance with ryzen? There was clearly a time when AMD had superior manufacturing processes through them, if Intel's designs of the time were on the same process would they have managed to grab the headlines?

And no, I Strongly disagree that NVidia running unchecked over the entire market being "Good for consumers", and not sure if the capital expenditure of getting over this moat is really much smaller than things like resource acquisition or infrastructure, they have $billions in current software ecosystems and hardware designs. Those $billions probably could buy you a fair bit of infrastructure investment on the scale you mentioned. Look how much Intel is burning right now just to get a toe into the market and not laughed out the door - and they're still clearly behind their competitors right now. Their chips aren't anywhere near competitive from a performance-per-area point of view, and their software is rather poor for the vast majority of use cases.

Re: Nvidia announces financial results for second quarter fiscal 2024

#403
post #399

Earlier quoted context omitted.

>There’s a good reason to never go above 70fps: human perception experts tend to agree that our visual system gives us quickly diminishing returns above 60fps, we can’t really see things any faster than that No. Please don't spread this nonsense rumor. It hasn't ever been true and still isn't. There are always diminishing returns, but human vision is perfectly capable of noticing the difference between 60 and say, 12…

I don’t disagree with your points, vision is indeed complex and not discrete, displays and games can all be different, but there is plenty of scientific perception research to back up my statement that 500 fps is not 5x better than 100 fps to a human. We don’t need 500fps movies, ever. Games want high fps because there’s a feedback loop. Do you have sources that show otherwise and back up your claim that this idea is…

You're twisting my words and changing what you claimed.

>my statement that 500 fps is not 5x better than 100 fps to a human

I never said that. I also stated that I know about diminishing returns. You claimed "There’s a good reason to never go above 70fp". There absolutely is a large difference in motion clarity between 70 and something like 120/240/etc. Is the difference from 70->120 as large as 30->60? No, absolutely not. But it is significant and can be seen easily with a cheap monitor.

>You aren’t really addressing what was main point: that fps throughput isn’t the reason for high frame rates in games. The primary reason for this happening is to decrease latency.

>We wouldn’t need 500fps for games if we lowered the latency. Or at the very least, the benefits would be much lower. Reducing latency is a great reason to want high fps, but there are other ways to reduce latency.

While there is a latency improvement and some people care about that, the motion clarity is also significantly improved. (again, just drag some windows around on a 120hz monitor) That's true of movies just as well as games. Movies have pulled a lot of tricks to mask this issue over the years, but 60 is quickly becoming the standard over 30. (And once bandwidth and processing improves, it's likely some day decades from now it will jump even higher)

>You replied to the wrong comment, btw. I almost didn’t catch your reply.

Yeah, not sure how that happened.

Re: Nvidia announces financial results for second quarter fiscal 2024

#404

Earlier quoted context omitted.

> This is what having a monopoly looks like ! As someone who has been in the AI/ML space for over a decade, and even had an AMD/Radeon card for more than half of that, I can't help but feel that this is partially AMD's own fault. For many, many years it seemed to me that AMD just didn't take AI/ML seriously whereas, for all it's faults, NVIDIA seemed to catch on very early that ML presented a tremendous potential mar…

AMD has an entire line specifically for AI/ML... https://www.amd.com/en/graphics/instinct-server-accelerators They just don't have those capabilities in their consumer GPUs. AMD is also nearly 50/50 with nVidia for supercomputers in the Top500 (and dominates at the top) It took a few years after completeing the massive purchase of Xilinx to get going, but they are picking up speed rapidly.

AMD should do a high-memory-density MCD variant of 7900XT/XTX with a MCD that has 4 PHYs instead of 2. You could get 7900XTX to 48GB with no clamshell and 96GB with clamshell, which is getting into H100 territory.

Re: Nvidia announces financial results for second quarter fiscal 2024

#405

Earlier quoted context omitted.

Ok? But the other RTX models are fine - I know I had a 3070 until recently. Yes, there is a continuum of models with progressively more power. That’s good - the high end blazes a trail for the low end. The architecture that supports AI also support gaming. It’s the same overall architecture just different scales and price points. That’s good, it ensures enormous investment at the high end which is scaled down for dif…

Yes, it's fine to have a large product line with different price points for different consumers, but I don't think it's quite fair to add the last generation's cards in there too (because they won't be around forever). Typically they only keep 2-3 generations alive in the marketplace at any given time, and if the prices keep going up, once the 30xxs disappear, so too will the affordability. Even an entry-level 4060 i…

Perhaps - but as long as they’re are profitable skus I don’t see that happening. The lower and mid range build scale for them. If they need more scale for the high end they can simply produce fewer, but by making as many as they can at any cost point they improve economics. Also often there is a probability distribution of quality of components, and by having a low end to saturate the excess that is below high end grade they can improve margins and efficiency.

Re: Nvidia announces financial results for second quarter fiscal 2024

#406
post #390

Earlier quoted context omitted.

This, but also if we took it at face value (we shouldn't for the reasons in the reply above), then this means Intel is even further ahead when adjusting for the difference in node sizes. i.e. This would mean Intel will be getting a four-node-scale jump in performance (10nm->7nm->5nm->3nm->1.8nm) from where they are with Raptor Lake by 2025 if they can stay on track. I don't have any insight into this but I would hope…

> I don't have any insight into this but I would hope Pat Geslinger is righting the salary, perks and incentive structure as a matter of priority to stop the shedding of talent. Absolutely not and this is one of the strongest headwinds intel faces. They just did a big round of layoffs and then everyone who didn’t get cut got a surprise 20% pay cut after, and retention bonuses for seniors was typically low-3-digits to…

What’s wrong with Arizona?

Re: Nvidia announces financial results for second quarter fiscal 2024

#407
post #399

Earlier quoted context omitted.

I don’t disagree with your points, vision is indeed complex and not discrete, displays and games can all be different, but there is plenty of scientific perception research to back up my statement that 500 fps is not 5x better than 100 fps to a human. We don’t need 500fps movies, ever. Games want high fps because there’s a feedback loop. Do you have sources that show otherwise and back up your claim that this idea is…

You're twisting my words and changing what you claimed. >my statement that 500 fps is not 5x better than 100 fps to a human I never said that. I also stated that I know about diminishing returns . You claimed "There’s a good reason to never go above 70fp". There absolutely is a large difference in motion clarity between 70 and something like 120/240/etc. Is the difference from 70->120 as large as 30->60? No, absolute…

Alright we’re in a cycle of misunderstanding each other, and rabbit holing on something that is rather tangential to my original point. I acknowledge I should not have used the word “never”. I meant rarely, and I meant for “most” games, not literally never, and not all games.

When you said “No. Please don't spread this nonsense rumor. It hasn't ever been true and still isn't.”, combined with the downvote, I assumed you were referring and objecting to everything I said including diminishing returns (even though I see you acknowledging it next paragraph.)

We are mostly agreeing violently, I acknowledge that there’s no known hard fps threshold above which nobody can see something. I acknowledge that there are benefits above 60fps, even if they grow smaller.

But it’s still true that the primary reason games are going to 500fps is for the latency benefits, not for the smoothness or high flicker rate. A frame rate that high isn’t generally perceptible, while the latency of today’s games - a latency of multiple frames - is actually well inside the known measurable threshold of response times. The problem isn’t generally the need for more frames per second, the big problem is the time between input and the visible change on screen.

The other topic that would be nicer to discuss is the quality trade offs. High frame rate takes away from other options.

Re: Nvidia announces financial results for second quarter fiscal 2024

#408
post #255

How durable do we think their Revenue is? To remind us all, they're selling capitalized assets, not contracts or services. Is the marginal demand for GPU chips over the next 3 years enough to sustain (or grow?) current revenues and keep this valuation afloat? To me, it feels like a comparatively fragile situation to find themselves in, to convince the world of 2025 that they need even more chips , unless "everybody n…

it will be sticky as long as there's a cambrian explosion of AI innovations happening. NVIDIA built the best swiss-army-knife for handling GPGPU problems in general, spent 15 years building the ecosystem and adoption around it, and then tailored it to AI specifically.

Once the tech settles down a bit, Google and Amazon and others can absolutely snipe the revenue at a lower cost, just like they did with the previous TPUs/gravitons. But then some new innovation comes out that the ASICs (or, ARM+accelerator) don't do, and everyone's back to using NVIDIA because it just works.

AMD potentially has a swiss-army knife too, but, they also have a crap software stack that segfaults just running demos in the supported OS/ROCm configurations, and a runtime with a lot of paper features and feature gaps. And NVIDIA's just works and has a massive ecosystem of libraries and tools available. And moreover they just have a mindshare advantage. Innovation happens on NVIDIA's platform (because NVIDIA spent billions of dollars building the ecosystem to make sure it happens on their platform). And it actually does just work and has a massive codebase etc. Sure it's a cage but it's got golden bars and room service.

https://github.com/RadeonOpenCompute/ROCm/issues/2198

So I guess I'd say it's sticky until the technology settles. Steady-state, I think competitors will capture a lot of that revenue. But during the periods of innovation everyone flocks back to NVIDIA. AMD could maybe break that trend but they'll have to actually do the work first, they have tried the "do nothing and let the community write it" strategy for the last 15 years and it hasn't worked. You gotta get the community to the starting line, at least. Writing a software ecosystem is one thing, writing runtime/drivers is another.

Re: Nvidia announces financial results for second quarter fiscal 2024

#409

Earlier quoted context omitted.

> the CEO announced a 10% paycut across the board Which is still better than a 10% layoff, anyway!

Only for 10% of the workers.

Morale after layoffs goes down for all workers. So no, not only for 10% of the workers.

Re: Nvidia announces financial results for second quarter fiscal 2024

#410
post #351

Earlier quoted context omitted.

Nvidia started working on CUDA back in the mid-2000s. Nobody else cared about GPU compute back then.

I didn't know CUDA was in development for that long, thanks! I'm curious if there were serious attempts to create something similar over the years and how far they managed to progress. I've never used OpenCL but from looking at it from afar its adoption always seemed limited. Irrespectively though I don't see how a competitor can replicate the context and tacit knowledge associated building something like CUDA for cl…

The first version of CUDA was released in 2007 so I would not be surprised if they started working on it in the 90s. These things take time.

Nvidia also made sure that CUDA runs on gaming GPUs and supports Windows. This is why its tools are so good. You don't need to buy a datacenter GPU, no need to mess with Linux. Just buy any gaming GPU, install CUDA SDK and you're good to go.

AMD wasn't like that. Their alternative - ROCM didn't even work on gaming GPUs. Their datacenter GPUs didn't even support Windows. Basically the opposite approach of NVIDIA. Now AMD is rushing to add Windows and consumer GPU support to ROCM, but it's a bit too little too late.

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