Are there any good real-world applications that take heavy advantage of SIMD? I imagine it would be very prolific given the benefits offered but SIMD, but I honestly have no idea.
Discounting their existence is entirely unfair, as one of the whole points of Apple Silicon is to give Apple the opportunity to put whatever hardware into their computer that accelerates the use cases they envision for their computers. Dedicated hardware is way more power efficient that software implementations.
However, what happens if you work in a video codec that Apple didn't build in hardware support for? Software video codecs depend heavily on SIMD instructions to be performant.
FWIW, NVIDIA has made significant improvements to quality for their hardware encoders in each of their last 3 generations, and you definitely saw reviewers and creatives talking about that in particular when it came to purchasing decisions.
Apple's encoder is probably quite good at least, but I don't think it's meaningful to consider it for most benchmarks. The scenarios where you both are willing to use the hardware encoder and care about how fast it is are relatively few and far between - if you're just doing a zoom call all that matters is whether it can pump out 60fps and how good it looks, not whether it uses 3% cpu instead of 5%. I'd rather see quality/bitrate comparisons of their encoder with x264, not benchmarks.
You can read what Google did on Android phones to encrypt drives here for instance: https://lwn.net/Articles/776721/
For esoteric/custom crypto it could play a part though but you have to have good reasons to not want to use standard crypto at higher speed for it to be your use case which is why I say it'd be uncommon.
Modern designs tend to be very SIMD-aware, such as BLAKE3[0] and Gimli[1].
[0]: https://github.com/BLAKE3-team/BLAKE3/blob/master/c/README.m...
[1]: § 5.6 https://gimli.cr.yp.to/gimli-20170627.pdf
ripgrep does the same, except for Intel at least, its memchr is implemented in Rust using SIMD intrinsics explicitly. And it also has a specialized SIMD algorithm (taken from Hyperscan mostly) for dealing with multiple patterns: https://github.com/BurntSushi/aho-corasick/tree/8b479a60906d...
Hyperscan takes this to a different level though. It has oodles more SIMD. I should have mentioned it in my original comment.
I was curious mostly because I never recalled any SIMD intrinsics in GNU code (ok, probably GIMP has them, so maybe I should say GNU utilities), so that would be a first.
It's interesting how much stuff leans on memchr, shame there aren't systematic wider versions taking more bytes to avoid false positives for longer literals (ignoring wmemchr): these could be nice and fast with SIMD.
And then of course there's PCMPESTRI (and its variants), but that has largely been a failure because of its high latency. :-( That's a shame, because that instruction does accept substrings up to 16 bytes.
You have to understand that current software exists because it solved a goal. If you have to first have your algorithm implimented in hardware then nobody can make anything. Without SIMD these projects simply wouldn't be able to exist. That's the hard math of it.
The tradeoff with using it is basically between instruction density, power (AVX-512), and latency (GPUs are seriously powerful, but getting the data going takes time and a lot of driver bullying).
These instructions can be beneficial when leveraged providing significant speed ups for larger transfers.
(And PyTorch can be and often is run on pure CPU.)