[neonsunset]

Here's the tracking issue for Go if you're interested: https://github.com/golang/go/issues/67520

I wouldn't be holding my breath though - proper support of high-level portable SIMD abstraction requires quite a lot of compiler complexity due to how wide (heh) the API surface of SIMD extensions is in most ISAs, and because of details necessary to get right to keep data in appropriate (vector and/or mask) registers. This, naturally, goes in the complete opposite direction to the design philosophy of Go's compiler. Instead, you are supposed to write a custom Go ASM syntax, with byte literals used to encode opcodes if they are not natively supported (which is common).

If you're interested in what high-effort SIMD implementation in this kind of language looks like, take a look at C#'s cross-platform Vector API: https://github.com/dotnet/runtime/blob/main/docs/coding-guid...

https://lemire.me/blog/2024/07/05/scan-html-faster-with-simd... (uses platform intrisics, but showcases that you can go one abstraction level lower, retaining the same Vector128<T> type if you need to specialize a particular part of your algorithm for a platform, without having to maintain separate copy for each one)

Here's high-effort vectorized CRC64 implementation that uses these: https://github.com/dotnet/runtime/blob/283de5b5adf08c42d4945... (performs as fast as C++-based mnemonic variant)

[ziofill]

Mojo should get a mention since we are in topic of SIMD.

[neonsunset]

Corrective upvote from me :)

Mojo's effort in bringing portable SIMD abstraction to Python audience is commendable. I'm looking forward to open-sourcing of it to try it out!

For anyone's curious, the reason I'm mostly talking about C# above is that its Vector API is the most accessible and mature portable SIMD abstraction that is part of standard library / comes out of box among most other options - you really only need to install SDK and `dotnet new console` to start working with it over more complex alternatives.