AI PCs Aren't Good at AI: The CPU Beats the NPU

I thought the purpose of these things was not to be fast, but to be able to run small models with very little power usage? I have a newer AMD laptop with an NPU, and my power usage doesn't change using the video effects that supposedly run on it, but goes up when using the nvidia studio effects.

It seems like the NPUs are for very optimized models that do small tasks, like eye contact, background blur, autocorrect models, transcription, and OCR. In particular, on Windows, I assumed they were running the full screen OCR (and maybe embeddings for search) for the rewind feature.

That's especially true because yours is a Xilinx FPGA. The one that they just attached to the latest gen mobile ryzens is 5x more capable too.

AMD are doing some fantastic work at the moment, they just don't seem to be shouting about it. This one is particularly interesting https://lore.kernel.org/lkml/DM6PR12MB3993D5ECA50B27682AEBE1...

edit: not an FPGA. TIL. :'(

Wait sorry back up a bit here. I can buy a laptop that has a daughter FPGA in it? Does it have GPIO??? Are we seriously building hardware worth buying again in 2024? Do you have a link?

It isn't as fun as you think - they are setup for specific use cases and quite small. Here's a link to the software page: https://ryzenai.docs.amd.com/en/latest/index.html

The teeny-tiny "NPU," which is actually an FPGA, is 10 TOPS.

Edit: I've been corrected, not an FPGA, just an IP block from Xilinx.

It's not a FPGA. It's an NPU IP block from the Xilinx side of the company. It was presumably originally developed to be run on a Xilinx FPGA, but that doesn't mean AMD did the stupid thing and actually fabbed a FPGA fabric instead of properly synthesizing the design for their laptop ASIC. Xilinx involvement does not automatically mean it's an FPGA.

Do you have any more reading on this? How come the XDNA drivers depend on Xilinx' XRT runtime?