Does it seems silly to anybody else to even call these GPUs? That's a GPU minus the G.

Agreed. I guess it's because of the architectural heritage but at this point GPU is something of a misnomer.

Very much absurd. A user above posted GPGPU, which I guess stands for General Purpose Graphics Processing Unit.

In the beginnings of computation these kinds of cards were called accelerators. Dedicated consumer sound cards were a thing, the venerable SoundBlaster. I really would like an AI-Blaster coming out.

There is actually ML hardware that is not based on GPU technology: it's called TPU (Tensor processing unit) but only Google uses it. I guess it is easier to repurpose existing technology even if a specialized approach is more efficient in theory.

> They do not have any graphics rendering circuitry.

What? Not having a display output is not the same as not having graphics rendering circuitry. Here's vulkaninfo from an A100 box: https://gist.github.com/eiz/c1c3e1bd99341e11e8a4acdee7ae4cb4

This may not contradict what I said. Do you know for a fact these things are implemented using dedicated hardware?

Fair enough. In the GH100 architecture doc https://resources.nvidia.com/en-us-tensor-core/gtc22-whitepa... (page 18) they do mention retaining 2 graphics-capable TPCs but it's clearly not the focus.

They do have graphics rendering circuitry, but e.g. fewer shading units and more graphics memory, or support for faster interconnects. You can look up the specs and compare. The differences are varied, but IMO not enough to claim they're not GPUs anymore. Even gaming focused GPUs are GPGPUs these days: the RTX 4090 has as many Tensor Core units as the A100. And you can still use e.g. DirectX, OpenGL with a datacenter grade GPU.

> fewer shading units

This is incorrect. NVIDIA uses a unified graphics and compute engine. A CUDA core is a shading unit. These datacenter GPUs have a shit ton of these (CUDA cores).

Edit: actually the point I want to make is the A100 only retains those hardware units which can be used for compute. Some of these units may have a (dual) use for graphics processing but that is besides the point (since this is true of all CUDA enabled NVIDIA GPUs).