Basic Facts about GPUs

Good article summarizing good chunk of information that people should have some idea about. I just want to comment that the title is a little bit misleading because this is talking about the very choices that NVIDIA follows in developing their GPU archs which is not what always what others do.

For example, the arithmetic intensity break-even point (ridge-point) is very different once you leave the NVIDIA-land. If we take AMD Instinct MI300, it has up to 160 TFLOPS FP32 paired with ~6 TB/s of HBM3/3E bandwidth gives a ridge-point near 27 FLOPs/byte which is about double that of the A100’s 13 FLOPs/byte. The larger on-package HBM (128 – 256 GB) GPU memory also shifts the practical trade-offs between tiling depth and occupancy. Although this is very expensive and does not have CUDA (which can be good and bad at the same time).

Unfortunately Nvidia GPUs are the only ones that matter until AMD starts taking their computer software seriously.

They are. It's just not at the consumer hardware level.

This misconception is repeated time and time again; software support of their datacenter-grade hardware is just as bad. I've had the displeasure of using MI50, MI100 (a lot), MI210 (very briefly.) All three are supposedly enterprise-grade computing hardware, and yet, it was a pathetic experience with a myriad of disconnected components which had to be patched, & married with a very specific kernel version to get ANY kind of LLM inference going.

Now, the last of it I bothered with was 9 months ago; enough is enough.

this hardware is ancient history. mi250 and mi300 are much better supported

What a load of nonsense. MI210 effectively hit the market in 2023, similarly to H100. We're talking about datacenter-grade, two-year out of date card, and it's already "ancient history?"

No wonder nobody on this site trusts AMD.

Unless you're, you know, using GPUs for graphics...

Xbox, Playstation, and Steam Deck seem to be doing pretty nicely with AMD.

The quantity of people on this site now that care about GPUs all of a sudden because of the explosion of LLMs, who fail to understand that GPUs are _graphics_ processors that are designed for _graphics_ workloads is insane. It almost feels like the popular opinion here is that graphics is just dead and AMD and NVIDIA should throw everything else they do in the bin to chase the LLM bag.

AMD make excellent graphics hardware, and the graphics tools are also fantastic. AMD's pricing and market positioning can be questionable but the hardware is great. They're not as strong with machine learning tasks, and they're in a follower position for tensor acceleration, but for graphics they are very solid.

The quantity of people on this site now that think they understand modern GPUs because back in the day they wrote some opengl...

1. Both AMD and NVIDIA have "tensorcore" ISA instructions (ie real silicon/data-path, not emulation) which have zero use case in graphics

2. Ain't no one playing video games on MI300/H100 etc and the ISA/architecture reflects that

> but for graphics they are very solid.

Hmmm I wonder if AMD's overfit-to-graphics architectural design choices are a source of friction as they now transition to serving the ML compute market... Hmmm I wonder if they're actively undoing some of these choices...