[mpreda]

And the splitting into CDNA and RDNA comes from the same direction: market segmentation, to allow much higher prices for the CDNA data-center GPUs, while keeping the gamer-focused RDNA GPUs affordable for mere mortals. Of coures this backfires by making the powerful GPUs not available for mostly anybody anymore to experiment on.

For example this blog post, about how great MI300X is. Really, what do I care -- I'm not a billionaire.

[dragontamer]

> And the splitting into CDNA and RDNA comes from the same direction: market segmentation

Not really.

Wave64 on CDNA is provably more throughput. But with most video game code written for NVidia's Wave32, RDNA being reworked to be more NVidia-like and Wave32 is how you reach better practical video game performance.

HPC will prefer the wider execute, 64-bit execution, and other benefits.

Video Gamers will prefer massive amounts of 32MB+ of "Infinity cache", which is used in practice for all kinds of screen-space calculations. But this would NEVER be used for fluid dynamics.

[markstock]

Maybe never by the big players, but RDNA and even fp32 are perfectly fine for a number of CFD algorithms and uses; Stable Fluids-like algorithms and Lagrangian Vortex Particle Methods to name two.

[tormeh]

They’re unifying the architectures. AMD will move to UDNA for both gaming and data center. The next graphics cards after RDNA4 will be UDNA. Makes sense given how ML-heavy graphics has become.

[kouteiheika]

The point is they shouldn't have done it in the first place. It was obvious right from the start it's a bad idea, except maybe for temporarily boosting short term profits.

The whole AMD AI/ML strategy feels like this - prioritize short term profits and completely shoot themselves in the foot in the long term.