Nvidia’s DLSS 2.0 aims to prove the technology is essential


Nvidia's DLSS 2.0 aims to prove the technology is essential

Deep Learning Super Sampling (DLSS) is one of the marquee features for Nvidia’s RTX video cards, but it’s also one people tend to overlook or outright dismiss. The reason for that is because many people equate the technology to something like a sharpening filter that can sometimes reduce the jagged look of lower-resolution images. But DLSS uses a completely different method with much more potential for improving visual quality, and Nvidia is ready to prove that with DLSS 2.0.

Nvidia built the second-generation DLSS to address all of the concerns with the technology. It looks better, gives players much more control, and should support a lot more games. But at its core, DLSS 2.0 is still about using machine learning to intelligently upscale a game to a higher resolution. The idea is to give you a game that, for example, looks like it is running at 4K while actually rendering at 1080p or 1440p. This drastically improves performance. And, in certain games, it can even produce frames that contain more detail than native rendering.

For DLSS, Nvidia inputs a game into a training algorithm to determine what the visuals are supposed to look like at the sharpest possible fidelity. And this is one of the areas where DLSS 2.0 is a significant leap forward. Nvidia originally needed a bespoke training model for every game. DLSS 2.0, however, uses neural network for every game. This means Nvidia can add DLSS support to more games at a more rapid pace.

Then using that deep-learning data, DLSS can then use the Tensor GPU cores on Nvidia’s RTX cards to process what a 1080p frame should look like at 4K. And this method is so much more powerful than sharpening because it is rebuilding from data that isn’t even necessarily present in each frame. Here’s the result:

How DLSS 2.0 is faster and more customizable

MechWarrior 5: Mercenaries and Control are the first two games to support DLSS 2.0. They will get the benefit of the more efficient AI network. This version of the tech is twice as fast on the Tensor cores already available in RTX cards like the RTX 2060 up to the RTX 2080 Ti.

Nvidia has also added temporal feedback to its DLSS system. This enables the super-sampling method to get information about how objects and environments change over time. DLSS 2.0 can then use that temporal feedback to improve the sharpness and stability from one frame to the next.

But the advantages go beyond improved processing. DLSS 2.0 also turns over more control to the player. One of the disadvantages of DLSS in many games is that it was often a binary choice. Either it was on or off, and developers got to decide how DLSS behaved.

DLSS 2.0 flips that by giving three presets: Quality, Balanced, and Performance. In Performance mode, DLSS 2.0 can take a 1080p frame and upscale it all the way up to 2160p (4K). Quality mode, meanwhile, may upscale 1440p to 2160p.

But you don’t necessarily need a 4K display to get the advantages of DLSS 2.0. You can use the tech on a 1080p or 1440p display, and it will often provide better results than native rendering.

Again, this is possible because DLSS 2.0 is working from more data than a native 1080p frame. And all of this is going to result in higher frame rates and playable games even when using ray tracing.

DLSS 2.0 is rolling out soon as part of a driver update for RTX cards.


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