For me the problem is technology and not raw performance
DLSS and RT are massive for someone with a 4k screen but now 4k gaming hardware outside league of legends lol
Sure, you can see the difference if you're carefully looking for it in comparison videos. But when you're actually playing it's usually not noticeable to any meaningful degree. You're gonna get occasional artefacts with both.
As for ray tracing - to be honest, playing at 4k with an RTX 3070 there's very few games where I can turn it on without the game running unacceptably slow even with DLSS.
Ray traced shadows and AO are nice but hardly a deal breaker.
I think it's more the desire to have the latest and greatest tech that makes Nvidia cards desirable, rather than any material difference that you'll actually notice while gaming.
Some good comparison shots of DLSS 2 and FSR 2 in this video.
You can do any comparison you want, but it won't help you when your software won't make use of the library your GPU supports.
(Also, we're at DLSS 3.0 now with frame generation which moves the bar higher.)
FSR2 needs game specific integration (IIRC because it needs access to motion vectors) and cannot be applied globally.
- the overwhelming conclusion is DLSS is the superior upscaling technology with near universally better results
- it was a brutal result for AMD
- DLSS gives NVIDIA a clear selling point
I'm not sure if it backs your suggestion...
Meanwhile AMD only supports FSR and if the game looks better with DLSS then there's nothing you can do.
AMD cards also aren't that much cheaper so it doesn't make much sense to buy worse tech that you'll be using for years every day to save a few euros.
NVIDIA said as much, released a 16GB version, and lo-and-behold it's absolutely pointless, even performing worse than the 8GB at times: https://www.tomshardware.com/reviews/nvidia-geforce-rtx-4060...
Most graphics cards are still under 8GB of VRAM, and raw numbers of memory storage mean nothing for performance in isolation.
DLSS isn't "NVIDIA flavored FSR", it's a more advanced pipeline that requires significantly more architectural alignment. FSR 3 was going to be the closest thing to an equivalent and won't run everywhere FSR 2 does.
Whether or not this is just a marketing gimmick is up to you and your own conclusions on the matter, but AMD doesn't seem to have an equivalent hardware tech for this yet. It seems to be taking steps in the right direction with the WMMA instruction for accelerating matrix multiplication in a similar fashion, but performance so far head-to-head seems lacking, and I haven't seen anything definitive out of AMD suggesting this for gaming purposes.
FSR may one day get much better, but in my personal preferences and tastes, I greatly prefer DLSS for upscaling. It tends to be sharper, better at fine details at long distances, and tends to do better with certain (literal) edge cases.
https://www.google.com/search?q=why%20is%20nvidia%20better%2...
(To be fair, Nvidia were at the forefront of this GPGPU thing since before there were dedicated APIs for it, so they certainly deserve some credit, but at this point they seem in desperate need for someone to finally knock them down.)
The second big problem is that AMD has a history of abandoning APIs. While Nvidia has been focusing on CUDA from the start, AMD is on its third or fourth API. A lot of developers got burned early on by putting in a lot of effort into supporting AMD cards, only to have their work become useless as AMD dropped old API.
So if you wanted to support AMD today you have to choose between using their latest API which is currently only supported on a handful of their latest top end cards, or using their previous API, which is much worse and may or may not be supported in 2 years time.
While there's very few cards that are officially supported, I've enabled most RDNA 1 and RDNA 2 GPUs in the OS-provided packages on Debian Unstable and Ubuntu 23.10. I haven't tested all of them, but my experience has been that they generally work quite well. The version of HIP packaged for Debian is still a few versions behind, so we haven't been able to enable RDNA 3 yet, but it shouldn't be too long before that is resolved.
As you have described, it has been a very long road to get to this point (with a lot of mistakes along the way), but I think things are getting better. That said, I work on ROCm, so my evaluation may be unintentionally biased.
Hopefully. Although I haven't programmed with it yet, the latest ROCm looks nice (at least from reading the docs). Now all you have to do is actually get to a point where it's actually supported on hardware people actually own and convince people that it's worth investing their time in, and then AMD can start making progress.
AMD has been a lot less consistent with their support changing their mind almost every 3 years. ROCm was initially released in 2016 (that's 9 years of headstart for NVIDIA). If you look at https://docs.amd.com/en/latest/release/gpu_os_support.html on Linux only the enterprise server cards are supported. Situation slightly different on windows https://docs.amd.com/en/latest/release/windows_support.html where they support last 2 generations of consumer cards (partially). I remember there were also a few years with even more bizarre situation where they supported GPUs that are couple of generations old but not their latest cards.
Not hard to see how developers are hesitant to spend time adding support for AMD if large portion of AMD users won't be able to use it and there is a high chance that after few years AMD will change their mind again coming out with new API or dropping support for cards that are only couple of years old.
This disparity is due to that fumble.
But since Rocm for windows finally released. The situation may finally change. We can probably just wait and see what will go on.
- people had lots of time to get used to it
- hobbyists and smaller research outfits/labs could make use of it on the cheap and less powerful hardware (where even a cheap GPGPU beats computing in software), driving:
- mind share (compare: Photoshop/Microsoft's tolerance to piracy)
- sales of hardware when the users decided to upgrade, buying more and/or and/or more modern and/or better cards
In contrast, the range of AMD hardware supporting ROCm was narrow and unstable (AFAIK one card was only supported for a couple of years). This would of course make ROCm unattractive for building with, especially for the hobbyists and smaller outfits that would otherwise drive mindshare but couldn't afford datacenter grade hardware that was supported.
No idea if AMD will drop whole list like it previously done this time though.
ML hardware sales are being driven by a 'Renaissance' of rapid model development and commercial offerings, primarily by the FAANG, but several others too. This is neat, but beyond the initial waves, OpenGPT isn't exactly the digital messiah many suggested it was, and running these models is expensive (both in HW and power for it). Time will tell, but I am skeptical this will be more than a craze for most applications (except digital art, which is awesome and has already been proven effective; just not maybe as marketable to the masses).
Edit: of course I am talking about gaming here since you mentioned consoles