The NVIDIA Turing GPU Architecture Deep Dive: Prelude to GeForce RTX
by Nate Oh on September 14, 2018 12:30 PM ESTClosing Thoughts
With a tagline like ‘Graphics Reinvented’, NVIDIA is certainly not straying from putting Turing in the most revolutionary limelight as possible. In that sense, NVIDIA is choosing to compare Turing to Pascal rather than Volta for every possible circumstance, especially for gaming. This decision is certainly not unfounded because for consumers, the Turing-based GeForce 20-series succeeds the Pascal-based GeForce 10-series. However, this can give the impression that because Turing is so different from Pascal, it warrants dissimilar comparisons like RTX-OPS metrics or gaming performance uplifts with DLSS or raytracing enabled.
The situation becomes a little more muddled because of several reasons:
- The pricing and availability of the RTX 20-series means that on a purely market segmentation level, it does not directly replace Pascal gaming products
- As gaming-focused cards, the major new features (RT cores, tensor cores, advanced shading) of the RTX 20-series do not operate out-of-the-box in games, are specific to select games, and
- The burden of communication is on the developers to educate consumers on the details of specific raytracing effects or use of AI-accelerated denoisers
These aren’t points that necessarily need to define Turing, except that NVIDIA has pushed the envelope by going all-in with marketing and branding. For their part, NVIDIA will have an continously updated list of games with RTX platform support.
On one hand, Turing seems like a possible solution to the gaming/compute architecture divergence. It seems less likely now that NVIDIA would backtrack into a more standard design for maximum rasterization performance, though obviously that remains to be seen with how the product fares. In any case, as most silicon design firms hvae leapfrogging design teams, the major decisions are likely not to move too far to the fixed function side, if only because the greatest strength of GPUs in compute is its programmability and versatility.
Looking back at ray tracing, it seems that even if it isn't immediately practical, there would still be a seeding effect to be gained via enthusiasts and certain gamers, which would work well with higher-profile AAA games. As we move into next week, it appears that the GeForce RTX 20-series is definitely one of the more nuanced graphics products, with both caveats and potential.
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Tamz_msc - Saturday, September 15, 2018 - link
"Besides, what you said isn't true even limiting the discussion to what was covered in this article. The Turing Tensor cores allow for a greater range of precisions."You mean lower precision, right? INT8 and INT4 are lower range. From a higher-level view Volta is very similar to Turing, just like the OP described.
Yojimbo - Saturday, September 15, 2018 - link
"greater range of precisions"INT8, INT4, FP16, etc., are precisions. The range of precisions an architecture can handle is the set of all precisions it can handle. Turing Tensor Cores can handle INT4, INT8, and FP16, whereas Volta Tensor Cores can handle FP16. So Turing can handle a greater range of precisions.
Bulat Ziganshin - Friday, September 14, 2018 - link
I would pray for 2060 w/o all this RT/FP16 stuffSpunjji - Monday, September 17, 2018 - link
Seems likely given how nutso these die sizes are. I expect we won't see it until after Pascal inventory is cleared, though.Da W - Friday, September 14, 2018 - link
Well still playing on my 3-screen Haswell + GTX780 rig, and being pretty satisfied of it, i'll probably just get a cheap GTX 1070 or 1080 for my new Ryzen rig and wait if ray tracing really gets adopted in 1 or 2 years. Seems to me lots of transistors invested for not many games. If history told us anything, it's not because a technology is great that it will get adopted, especially if it asks LOADS more developper time for the game companies.Not sure AMD won't come up with something either down the line. They've been given for dead for over 2 decades, guess where they are now!
Holliday75 - Monday, September 17, 2018 - link
I am waiting as well. This is the first attempt to change the game. Next gen or two is where it will be fined tuned and worth purchasing. This feels like a 4k TV purchase. Waste of money.abufrejoval - Friday, September 14, 2018 - link
I wonder how much Turing is about staking out territorial claims vs. dark silicon also coming to GPUs...Obviously Nvidia wants to protect its CUDA machine learning and HPC empire against custom ASIC competitors which finally also include Intel with their Configurable Spatial Accellerator, as well as Cambricon, Google's TPU ASICs and far too many others for comfort.
But while many seem to bemoan that tensor core or rasterizing real-estate is a waste for gaming and just about raising the purchase prices with overhyped features nobody needs, I wonder if apart from the partial truth in that the other motivating driver is simply that the inability to translate additional transistors into additional performance as additional bandwidth requires step changes in GDDR6 lanes (with unshrinkable pad areas and amplifiers) and hits foundry reticle sizes.
So they had transistors left over (wonder where those came from without a die shrink: I/O voltage reduction, layout optimizations, really bigger chips?), that could not be turned into direct DX1x performance gains due to bandwidth and TDP constraints and going to a richer functional base with Tensor Cores and raytrace assists would eat alternate bandwidth or TDP budgets, not additional ones.
Any truth in those assumptions?
abufrejoval - Friday, September 14, 2018 - link
ok, much bigger chips...And no rip-off: They are worth what they are charging if only for the inference accelleration.
Yojimbo - Saturday, September 15, 2018 - link
I am not convinced the Tensor Cores take up a lot of real estate. And they are tightly integrated into NVIDIA's SMs. Designing two SMs, one with Tensor Cores and one without Tensor Cores would be a lot more expensive than leaving them in. Plus, NVIDIA sees deep learning as important for gaming.Your argument about FLOPS per bandwidth does have validity. It's just that neither Tensor Cores nor RT cores were just thrown in there because they had transistors left over. Look at the die sizes of these new GPUs compared to Pascal GPUs. If they built a smaller chip that performed the same in legacy games then they could sell them more cheaply, and so sell more of them, while making the same profit on each one. That would mean higher margins and greater profits.
The RTX and Tensor Cores are a strategic initiative. I think in making the decision to include them NVIDIA judged that those two technologies would have a positive impact on the future of gaming. The reason they made that judgment may include the dwindling FLOPS/memory bandwidth trend.
bernstein - Friday, September 14, 2018 - link
really interesting time in gpu's right now... remember a decade ago when intel teased a x86-gpu that promised to do real-time raytracing?yet turing may turn out to provide an abysmal price/perf ratio.
- about half the transistors will only be used in a few upcoming games, they could be used to possibly double performance in rasterization-only games (7nm amd navi anyone?)
- but if (hybrid-)raytracing takes off quickly, turing will be crushed by 7nm gpu's dedicating way more transistors to the task, as it's performance is still skewed heavily towards rasterization
- ai inferencing seems like a safe bet, again i'd wager that DLSS will only ever work with the vast minority of games released each day on steam, so it's usefulness will depends on whether developers make other use of the available silicon... (better AI opponents anyone?)