Earlier quoted context omitted.
Is AVX512 really an advantage though? Intel is infamous for severely downclocking the processor for these and other AVX/SSE family instructions, to a point where sometimes using them makes the program slower than it would be otherwise, especially if you're constantly provoking frequency switches between them and regular instructions. AMD might not have implemented AVX512 specifically yet (there's nothing legally keep…
I personally run AMD at home, but in all the benchmarks I have seen, Intel wins by a large margin in AVX enabled tasks - often double the speed. Downclocking did not seem to be a factor here. I think saying that Intel wins in AVX tasks is absolutely fair. For example, I had a simulation that had to run on the CPU for reasons, but made use of AVX. Intel was consistently faster on any system I tested.
https://www.agner.org/optimize/instruction_tables.pdf
If you want to look at `vmov`s or arithmetic like `vadd` or `vmul`. Particularly glaring is that for moves between memory and (xmm vs ymm) Zen1 has a recirpical throughput of (1 vs 2), ie that on average it is able to complete an xmm-memory move once per cycle, and a 256-bit move one every two cycles. Skylake-X instead has 0.5 for xmm/ymm/zmm-memory. That is, it can move up to 512-bits between a register and memory twice per cycle. That is 8-times the throughput.
Arithmetic isn't as bad, but Zen1's reciprocal throughput goes from 0.5 to 1 on xmm to ymm, while Intel stays at 0.5 independent of vector size.
I haven't seen data on the 7nm Ryzen parts, but their marketing claimed it was supposed to have full width avx2, so I imagine things are different now, and that 7nm Ryzen will do just as well for avx workloads per core and clock as all the Intel parts without avx512.
EDIT: Some instructions on Intel get slower with wider vectors, like vdiv, vsqrtpd, vgather...