Discussion RDNA 5 / UDNA (CDNA Next) speculation

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ToTTenTranz

Senior member
Feb 4, 2021
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They killed Xbox with their own dumb moves.
They killed xbox with their crass inability to manage 1st party studios.

They demand their studios to apply for competitive public financing which screws up deadlines, and too much outsourcing which prevents talent and knowledge from staying in the company. Everything takes way too long and they need to constantly reinvent the wheel.


The funny part is Phil Spencer has been sinking the platform/brand for over a decade now, but xbox fans still blame Don Mattrick for its state nowadays.


Even the "day one gamepass" concept is completely moronic, as it screws up people's perception of a game's value (not that their games have that much value at release though).
 

Tuna-Fish

Golden Member
Mar 4, 2011
1,601
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RDNA5? dev kit for next Xbox is already in wild?

The early dev kits are not usually some unreleased stuff that's far away, they are just a pc with components that roughly match the performance target. Quite possibly it's just a 9700X and a 9070XT. Or it might even have an NVidia GPU, iirc the first PS4 dev kit did.

There will be "higher fidelity" dev kits that have actual real hardware once the first chips start coming off the line.
 

SolidQ

Golden Member
Jul 13, 2023
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From Mark Cerny quotes




So that seems RDNA5 is targeting more ML/RT/PT perf, also Neural denoising
 

ToTTenTranz

Senior member
Feb 4, 2021
380
726
136
From Mark Cerny quotes




So that seems RDNA5 is targeting more ML/RT/PT perf, also Neural denoising


Honestly, this says very little about post-RDNA4.

Amethyst so far is basically a joint venture between AMD and Sony to develop a ML-based upscaler.
AMD makes no software but makes GPUs and Sony vice versa, so they're using Sony's dataset to train a ML model optimized for AMD's latest compute units.

Which means PSSR is probably a percursor to FSR4, and it seems likely to me that PSSR will eventually be upgraded to whatever the latest version of FSR4 Sony's QA engineers decide to validate. Even if both companies do decide to keep the naming separate for marketing reasons.
 
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adroc_thurston

Diamond Member
Jul 2, 2023
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soresu

Diamond Member
Dec 19, 2014
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AMD makes no software
Take a quick look at the Mesa/Gallium3D codebase for Linux and tell me with a straight face that drivers do not count as hella complex software development.

That's not even counting all the other stuff AMD have been up to over the years on the software side like Tress FX and various other things GPUOpen deals with.
 
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ToTTenTranz

Senior member
Feb 4, 2021
380
726
136
Take a quick look at the Mesa/Gallium3D codebase for Linux and tell me with a straight face that drivers do not count as hella complex software development.


I meant videogame development, obviously.
Driver development isn't going to help much if what you need is a huge dataset of rendered frames using sky-high quality settings for training a CNN.



Yes AMD trains stuff on their own hardware for their own hardware.
Of course they do.
It's the dataset that is coming from people who make games. Sony's dev teams own the original, uncompressed textures and can dial IQ settings above the commercial game's settings in order to produce very high quality frames.


Yes they're completely separate, unrelated products.
Dude, Mark Cerny literally said they're not.

"The neural network (and training recipe) in FSR 4's upscaler are the first results of the Amethyst collaboration," Cerny told us.
(...)
Our target is to have something very similar to FSR 4's upscaler available on PS5 Pro for 2026 titles as the next evolution of PSSR; it should take the same inputs and produce essentially the same outputs.

They're using the same inputs, i.e. the same dataset.
 

blackangus

Senior member
Aug 5, 2022
214
356
106
Anyone who's meddled in ML training knows that producing the dataset is >90% of the work.

All the current ML developments are squarely related to model architecture and training recipes.

So you are both kinda right here.
In some industries building the dataset is difficult, there is alot to making sure your data is of high quality and the information is being presented appropriately.
Then there is still alot of scientific development going on with the mechanics, traceability, accountability, data formatting, and data ingesting areas. Lots of feature and optimization work to do in many areas based on where we are today.

I get to see both sides of the house in my current position.
 
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