Comment by jiggawatts | Hacker News Reader

Comment by jiggawatts | Hacker News Reader

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What's really freaky is that the RTX 30xx series of cards aren't even being manufactured on the current-gen process!

NVIDIA is using Samsung's 8nm process, which has about 60 million transistors per square millimetre (MTr/mm^2).

That's not cutting edge! The crown is currently held by TSCM's 5nm process, at 173 MTr/mm^2.

Some time next year, TSMC is starting "risk production" of their 3 nm process, which is expected to hit about 300 MTr/mm^2. That's a solid FIVE TIMES higher density than the process used for the RTX 30xx series.

Unlike general-purpose CPUs, where transistor density does not linearly translate to real-world performance, GPUs are designed for embarrassingly parallel problems and have nearly linear scaling. More transistors equals more "CUDA cores" equals more performance.

The only thing holding back GPU performance is memory bandwidth. Current-gen consumer cards are just shy of 1 TB/s of memory bandwidth, but to get 5x performance, they would need 5 TB/s memory throughput to match. That's... difficult. Even with HBM2E, you'd need to stack a bunch of them to get near that.

But yeah. 8K gaming is crazy. Real time raytracing was an utter fantasy just a few years ago, and I just played through Control at 60fps and it was a visual feast.

I grew up in an era where wire frame 3D graphics took seconds to redraw the screen. I used keyboard macros to control a CAD program because it had no hope of keeping up with mouse movements.

My unborn son is going to grow up to play in a world of 8K raytracing as standard, with visuals better than Pixar movies of just a few years ago. That blows my mind.

> Real time raytracing was an utter fantasy just a few years ago

We still don't have real time ray-tracing. Even the demos that only use ray-tracing are throwing the strict minimum of rays and they apply a series of complex filters (using machine learning) to remove the artifacts and the noise.

It’s still pretty cool that these cards have enough oomph to get close enough to real-time for DLSS to work.

As I understand it, the Quake RTX demo is fully ray traced but I could be wrong on that. The FPS isn’t super high but definitely playable.

If anything, that's more impressive in a way. The NVIDIA presentation for the 30xx series was the first time it really "clicked" for me, despite having a 2080 in my PC for a while now.

The RTX cards dedicate something like 30% of the silicon and power "budget" to neural-nets.

This isn't something designed to appease only the ML crowd, it's used for gaming. The graphics you see is 30% ML noise reduction and upscaling.

I used to think of "AI accelerators" as some sort of gimmick, one-trick ponies like Apple's face recognition. Useful for a handful of apps, a few seconds at a time.

But no, in the RTX series of cards, the "AI stuff" is drawing nearly 100 watts and doing real work, making ray tracing viable and making 1080p look better than 4K.

And? Everything is an approximation so if you can fake it 'til you make it does it matter?

I assume by the end of the century we will end up with some kind of physically based rendering at a near photonic level of detail.

By this logic, we basically still don't even have offline ray-tracing.

Both Renderman and Hyperion have denoisers that Pixar and Disney use on feature films.

> And because we could not afford to render images to convergence, we needed to develop a robust denoising solution

> The denoiser is used on most production shots, and is run automatically unless disabled

https://www.yiningkarlli.com/projects/hyperiondesign/hyperio...

(The fact that Hyperion uses a denoiser does not mean that it isn't rendering via path tracing. Similarly, the fact that real-time rendering uses a denoiser does not mean it isn't rendering via path tracing. dealing with noise is the name of the game, and machine learning isn't somehow "out of bounds")

Well we are still talking about few million rays per second. Without filtering you will end up with too much noise and blobs. Raytracing without noise filters is even for prerendered scenes unpractical and too expensive.

Pretty much every raytracer uses denoising. Every "industry-strength" raytracer anyway.

The challenge is heat (and cost) for the latest gen. GPUs are already prone to heat challenges, I can see the latest process requiring liquid cooling with their current design(s).

Is it a problem though? Enthusiasts have been using liquid cooling for years. Sure, hot computer, especially in warm climate is not the best thing to have around, but, I guess, that's not the end of the world. Air conditioners do exist after all.

> What's really freaky is that the RTX 30xx series of cards aren't even being manufactured on the current-gen process!

Exactly. This is why I'm not too worried about Intel not being on the smallest current-gen process, even though this AMD fans are jumping up and down about this.

Something noteworthy is the higher nm tend to be a bit faster than the smaller nm, so Samsung's 8nm isn't going to be slower than TSMC's 7nm.

The reason lower nm is better, beyond cost savings, is heat output and power consumption. If heat becomes a problem, the chip has to limit itself, as we're seeing with laptops. Nvidia's new cooling solution seems to fit the bill just fine, so 8nm is no problem.

I suspect the next generation is going to be on 7nm, is going to be a bit faster and will consume a fair bit less power, which will be nice, especially if you plan on training neural nets all day.

Faster how? Newer process nodes tend to offer more clock frequency at isopower, or lower power at isofrequency.

Since Radeon VII's HBM provides 1TBs of bandwidth with a 4096 bus just up it to 20,480 bits and bam 5TBs.

Not sure how you'd fit 20 stacks on an interposer. I can't solve all your problems.

> The only thing holding back GPU performance is memory bandwidth.

Cooling and getting enough power to the chips is going to very challenging. The 3080 already needed a redesign of its cooling solution and power delivery mechanism. At 5nm or 3nm, things are going to be a lot more difficult.

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