> GPUs (CUDA) are orthogonal to consumer processors (ARM / X86).

We're talking about vector operations. CUDA is not a GPU but a library of hardware-accelerated functions, not necessarily different from OpenCL or even NEON for ARM. You can reimplement everything CUDA does on a CPU, and if you're using a modern CPU you can vectorize it too. x86 handles this well, because it's still got dedicated logic that keeps pace with the SIMD throughput an integrated GPU might offer. ARM leaves out the operations entirely (which is smart for efficiency), and therefore either relies on someone porting CUDA code to an ARM GPU shader (fat chance) or offloading to a remote GPU. It's why ARM is excellent for sustained simple ops but collapses when you benchmark it bruteforcing AI or translating AVX to NEON. SIMD is too much for a base-spec ARM core.

> Maybe we could assume a platonic ideal merged chip, a CPU that acts like a GPU, but there's more differences between those two things than an instruction set for vector ops.

Xeon Phi or Itanium flavored?

Yeah, that’s true. CUDA is in large part for big HPC servers, where ARM historically wasn’t a player and still isn’t dominant. x86 got clobbered for HPC by CUDA.