[brcmthrowaway]

> The GPUs are bottom-barrel for compute-focused industries. It is mobile-grade hardware that arguably can't even scale to prior Mac Pro workloads.

Surprised Apple didn't create a TPU-like architecture. Another misstep from John Gianneadrea.

[bigyabai]

I'm confused how anyone ever thought the NPU would be a good idea. The GPU is almost always underutilized on Mac and could do the brunt of the work for inference if it embraced GPGPU principles from the start. Creating a dedicated hardware block to alleviate a theoretical congestion issue is... bewildering. That goes for most NPUs I've seen.

Apple had the technology to scale down a GPGPU-focused architecture just like Nvidia did. They had the money to take that risk, and had the chip design chops to take a serious stab at it. On paper, they could have even extended it to iPhone-level edge silicon similar to what Nvidia did with the Jetson and Tegra SOCs.

[easton]

I think they built the NPU with whatever models they needed to run on the iPhone in mind vs trying to build a general purpose chip, and then got lucky it was also useful for LLMs.

(Like “I want to do object detection for cutting people into stickers on device without blowing a hole in the battery, make me a chip for that”.)

[zozbot234]

I'm not sure even Apple thought that, given that they don't officially provide access to ANE internals under macOS (barring unsupported hacks). But if that was fixed, it could then be useful for improving the power efficiency of prefill, where the CPU/GPU hardware is quite weak (especially prior to the M5 Neural Accelerators).