In the article, Mitchel mentions how this doesn’t always work. In fact, as someone who’s worked in compiler development, I can say it’s a small miracle when it does work.

Most scalar-to-SIMD conversion requires changing the design of data structures and algorithms to be effective. Compilers are required to exactly reproduce the specified data structures in a deterministic way for obvious reasons.

Even if compilers were clever enough to transform your data structures and algorithms for SIMD (they're not), the data structures are a contract that can't be unilaterally modified.

auto-vectorization is not nearly as good as you would hope it to be.

The best SIMD optimizations likely require changing your data format from AoS to SoA.

I have no idea why you're being downvoted. HN has a fetish for SIMD, but if you are hand-rolling SIMD and you aren't writing an explicit acceleration library, you're doing it wrong. Like, 100% of the time.

Every modern language has a vectorization optimizing compiler, and through some fairly straightforward techniques this is automagic. And contrary to the various replies, unless you screwed something up compilers are really good at vectorizing on whatever hardware you're targeting, including SVE.