Unpacking 'RTX', 'NGX', and Game Support

One of the more complicated aspects of GeForce RTX and Turing is not only the 'RTX' branding, but how all of Turing's features are collectively called the NVIDIA RTX platform. To recap, here is a quick list of the separate but similarly named groupings:

  • NVIDIA RTX Platform - general platform encompassing all Turing features, including advanced shaders
  • NVIDIA RTX Raytracing technology - name for ray tracing technology under RTX platform
  • GameWorks Raytracing - raytracing denoiser module for GameWorks SDK
  • GeForce RTX - the brand connected with games using NVIDIA RTX real time ray tracing
  • GeForce RTX - the brand for graphics cards

For NGX, it technically falls under the RTX platform, and includes Deep Learning Super Sampling (DLSS). Using a deep neural network (DNN) specific to the game and trained on super high quality 64x supersampled images, or 'ground truth' images, DLSS uses tensor cores to infer high quality antialiased results. In the standard mode, DLSS renders at a lower input sample count, typically 2x less but may depend on the game, and then infers a result, which at target resolution is similar quality to TAA result. A DLSS 2X mode exists, where the input is rendered at the final target resolution and then combined with a larger DLSS network.

Fortunately, GFE is not required for NGX features to work, and all the necessary NGX files will be available via the standard Game Ready drivers, though it's not clear how often DNNs for particular games would be updated.

In the case of RTX-OPS, it describes a workload for a frame where both RT and Tensor Cores are utilized; currently, the classic scenario would be with a game with real time ray tracing and DLSS. So by definition, it only accurately measures that type of workload. However, this metric currently does not apply to any game, as DXR has not yet released. For the time being, the metric does not describe performance any publicly available game.

In sum, then the upcoming game support aligns with the following table.

Planned NVIDIA Turing Feature Support for Games
Game Real Time Raytracing Deep Learning Supersampling (DLSS) Turing Advanced Shading
Ark: Survival Evolved   Yes  
Assetto Corsa Competizione Yes    
Atomic Heart Yes Yes  
Battlefield V Yes    
Control Yes    
Dauntless   Yes  
Darksiders III   Yes  
Deliver Us The Moon: Fortuna   Yes  
Enlisted Yes    
Fear The Wolves   Yes  
Final Fantasy XV   Yes  
Fractured Lands   Yes  
Hellblade: Senua's Sacrifice   Yes  
Hitman 2   Yes  
In Death     Yes
Islands of Nyne   Yes  
Justice Yes Yes  
JX3 Yes Yes  
KINETIK   Yes  
MechWarrior 5: Mercenaries Yes Yes  
Metro Exodus Yes    
Outpost Zero   Yes  
Overkill's The Walking Dead   Yes  
PlayerUnknown Battlegrounds   Yes  
ProjectDH Yes    
Remnant: From the Ashes   Yes  
SCUM   Yes  
Serious Sam 4: Planet Badass   Yes  
Shadow of the Tomb Raider Yes    
Stormdivers   Yes  
The Forge Arena   Yes  
We Happy Few   Yes  
Wolfenstein II     Yes
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  • xXx][Zenith - Friday, September 14, 2018 - link

    Nice write-up! With 25% of the chip area dedicated to Tensor Cores and other 25% to RT Cores NVIDIA is betting big on DLSS and RTX for gaming usecases. With all the architectural improvements, better memory compression ... AMD is out of the game, quite frankly.

    Btw, for the fans of GigaRays/Sec, aka CEO metric, here is a Optix-RTX benchmark for Volta, Pascal and Maxwell GPUs: https://www.youtube.com/watch?v=ULtXYzjGogg

    OptiX 5.1 API will work with Turing GPUs but will not take advantage of the new RT Cores, so older-gen NV GPUs can be directly compared to Turing. Application devs need to rebuild with Optix 5.2 to get access to HW accelarated ray tracing. Imho, RTX cards will have nice speedup with Turing RT Cores using GPU renderers (Octane, VRay, ...) but the available RAM will limit the scene complexity big time.
    Reply
  • blode - Friday, September 14, 2018 - link

    hate when i lose a game before my opponent arrives Reply
  • eddman - Friday, September 14, 2018 - link

    As far as I can tell, GigaRays/Sec is not an nvidia made term. It's been used before by others too, like imagination tech.

    The nvidia made up term is RTX-ops.
    Reply
  • xXx][Zenith - Friday, September 14, 2018 - link

    Ray tracing metric without scene complexity, viewport placement is just smoke and mirrors ...

    From whitepaper: "Turing ray tracing performance with RT Cores is significantly faster than ray tracing in Pascal GPUs. Turing can deliver far more Giga Rays/Sec than Pascal on different workloads, as shown in Figure 19. Pascal is spending approximately 1.1 Giga Rays/Sec, or 10 TFLOPS / Giga Ray to do ray tracing in software, whereas Turing can do 10+ Giga Rays/Sec using RT Cores, and run ray tracing 10 times faster."
    Reply
  • eddman - Saturday, September 15, 2018 - link

    I don't know the technical details of ray tracing, but how is that nvidia statement related to scene complexity, etc?

    From my understanding of that statement, they are simply saying that turing is able to deliver far more rays/sec than pascal, because it is basically hardware-accelerating the operations through RT cores but pascal has to do all those operations in software through regular shader cores.
    Reply
  • niva - Wednesday, September 19, 2018 - link

    If you hold scene complexity constant (take the same environment/angle) and run a ray tracing experiment, the new hardware will be that much faster at cranking out frames. At least that's how I'm interpreting the article and the statement above, I'm not really sure if that's accurate though... Reply
  • Yojimbo - Saturday, September 15, 2018 - link

    When did Imgtec use gigarays? As far as I remember they didn't have hardware capable of a gigaray. They measured in hundreds of millions of rays per second, and I don't remember them using the term "megaray", either. Just something along the lines of "200 million rays/sec". Reply
  • eddman - Saturday, September 15, 2018 - link

    Why fixate on the "giga" part? I obviously meant rays/sec; forgot top remove the giga part after copy/paste. A measuring method doesn't change with quantity. Reply
  • Yojimbo - Saturday, September 15, 2018 - link

    Because the prefix is the whole point. The point is the terminology, not the measuring method. Rays per second is pretty obvious and has probably been around since the 70s. The "CEO metric" the OP was talking about was specifically about "gigarays per second". Jensen Huang said it during his SIGGRAPH presentation. Something like "Here's something you probably haven't heard before. Gigarays. We have gigarays." Reply
  • eddman - Saturday, September 15, 2018 - link

    What are you on about? He meant "giga" as in "billion". It's so simple. He said it that way to make it sound impressive. Reply

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