It’s been roughly a month since NVIDIA’s Turing architecture was revealed, and if the GeForce RTX 20-series announcement a few weeks ago has clued us in on anything, is that real time raytracing was important enough for NVIDIA to drop “GeForce GTX” for “GeForce RTX” and completely change the tenor of how they talk about gaming video cards. Since then, it’s become clear that Turing and the GeForce RTX 20-series have a lot of moving parts: RT Cores, real time raytracing, Tensor Cores, AI features (i.e. DLSS), raytracing APIs. All of it coming together for a future direction of both game development and GeForce cards.
In a significant departure from past launches, NVIDIA has broken up the embargos around the unveiling of their latest cards into two parts: architecture and performance. For the first part, today NVIDIA has finally lifted the veil on much of the Turing architecture details, and there are many. So many that there are some interesting aspects that have yet to be explained, and some that we’ll need to dig into alongside objective data. But it also gives us an opportunity to pick apart the namesake of GeForce RTX: raytracing.
AnandTech’s deep dive into NVIDIA’s new Turing architecture – the only one you really need.
I think what I found most interesting about the RTX boards was the primary use of the neural nets: they replace the traditional anti-aliasing calculations. With a neural net properly trained for your particular game, they claim to be able to infer a “similar” output with half the data.