[kkielhofner]

Jensen has said for years that 30% of their R&D spend is on software. Needless to say as they continue to crush it financially this number continues to completely race past AMD.

Turns out people don’t actually want GPUs, they want solutions that happen to run best on GPUs. Nvidia understands that, AMD doesn’t.

Lisa Su keeps talking about “chips chips chips” and MAYBE “Oh btw here’s a minor ROCm update”. Meanwhile, Nvidia continues to masterfully execute deeper and wider into overall solutions and ecosystems - a substantial portion of which is software.

Nvidia is at the point where they’re eating the entire stack. They do a lot of work on their own models and then package them up nice and tight for you with NIM and Nvidia AI Enterprise. On top of stuff like Metropolis, RIVA, countless things. They even have a ton of frameworks to ingest/handle data, finetune/train, and then deploy via NIM.

Enterprise customers can be 100% Nvidia for a solution. When Nvidia is the #1-#2 most valuable company in the world “no one ever got fired for buying Nvidia” hits hard.

The people who say “AMD and Nvidia are equal - it’s all PyTorch anyway” have no view of the larger picture.

With x86_64, day one you could take a drive out of an Intel system, put it in an AMD system, and it would boot and run perfectly. You can still do that today unless you build something for REALLY specific/obscure CPU instructions.

Needless to say that’s not the case with GPUs and a lot of people that make the AMD vs Intel comparison don’t seem to understand that.

[pjmlp]

Back when Khronos was still trying to push OpenCL 2.0, I attended one IOCWL webminar where an attendee asked about Fortran support for SPIR.

No one on the panel provided a meaningful answer, and some were even puzzled why someone would want that.

NVidia knew pretty well not only why someone would want Fortran on the GPU, they bought PGI before someone else though about doing the same.

Meanwhile Khronos and AMD still haven't got it.

At least Intel Fortran now also does GPU, and like NVidia are having Python GPU JIT efforts.

And then there is the whole tooling, libraries and additional compilers with PTX backends.

[takinola]

> Needless to say that’s not the case with GPUs and a lot of people that make the AMD vs Intel comparison don’t seem to understand that.

What needs to happen for GPUs to become as interchangeable as CPUs? What are the leading signs that this is becoming possible?

[_aavaa_]

What kind of interchangeable are you talking about? Vulkan and OpenCl exist.

The CPU analogy for the GPU case isn't AMD and Intel, it's x86 and ARM.