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This feature opens many doors for optimizing low-level performance in Go projects, that are already running multicore. IIRC there aren’t a lot of languages with built-in std lib support for SIMD and variants. Love the way Go is trying new stuff lately.
Vectorizing computations has been Matlabs secret sauce.
Julia does that too.
Does matlab these days do stuff like JIT operator fusing to avoid memory roundtrips and take advantage of FMAs?
Yes: https://www.mathworks.com/help/fixedpoint/ref/half.fma.html
I'm grateful that Go a non-proprietary language offers these features.
Besides the usual C and C++, we have Java, .NET, D, Zig, Julia, Swift, Rust.
So yeah, also appreciate having Go in the group instead of manually having to write Assembly.
However not many languages adopt ways to manually write SIMD, because most of us have no idea how to write good SIMD code in first place, I surely don't.
Even with languages that adopt ways to manually write SIMD, it’s mostly left to library maintainers rather than application developers.
I work for a C++ timeseries database startup that leverages SIMD about as much as we possibly can, and except for some extremely rare places we just use libraries.
Yeah, that is what I have heard from some NVidia folks as well, like Bryce Adelstein, use the libraries as much as possible, and leave the kernels for experts.
However even then, it depends on how the libraries API surface looks like.
With AI I'm pretty sure SIMD will be easier to integrate when necessary.
With AI, I expect it to eventually be good enough for us to finally have 5 GLs, so it won't really matter.
"CGO 2022 Keynote: Compiler 2.0"
https://www.youtube.com/watch?v=w_sX9aZoZxg
But it’s not necessary at all, the whole point is that these utility libraries bring you more elegant code that work on all platforms without having to pollute your codebase with SIMD intrinsics.
Unless this was tongue in cheek, because this is in fact a problem with AI that it degrades your codebase in these types of ways.
In 2026 if you are not doing A with AI you are doing it wrong /s
Oh this is great, it was one of my biggest bugbears about Go since you almost always have to link C/C++ code to get the appropriate performance.
The one negative I'd say is that often autovectorisation is 'good enough' and this doesn't really tackle that gap.
As a first step, it might be possible to write a linter rule that rewrites suitable numeric loops to SIMD. There are already rules to rewrite several loop types, so that should be doable.
The poor Assembler and the unsafe package forgotten in the corner.
While reaching out to CGO is the easier way, it doesn't mean it is the only tool available in Go.
FWIW, there is some pretty substantial autovectorization work that is already in-flight for the Go compiler.
There's a CL stack here:
https://go.dev/cl/791740
It's hard to make predictions with an open source project, but my personal guess is some flavor of it will land (including it is already demonstrating good results without an enormous level of code complexity in the compiler and without overly slowing down compile speeds), but I guess we'll see.
It's being driven by an external contributor who has landed some good changes in the past to the Go compiler. (I think the autovectorization work might be part of their PhD or other academic research, but not sure.)
The problem with Go isn't performance but with the C/C++ interop overhead, even with the "30% less overhead" from a few updates ago which isnt true for 99% of cases, it isnt enough
Why is that the case? I don’t know low level programming so why is Go limited in interop with C?
its not limited but it has overhead because of the memory model of go doesnt match the C one so there has to be some sort of rerodering being done, that's what i understood atleast, and theres also the go concurrency
Already using this for foreground estimation of cutouts in my project, around 30% speedup over non-SIMD, but the algorithm is probably not very optimised yet.
This is why I love Go. Nobody was asking for this, but they took the time to do it right and continue to Push go as a memory safe, high-level systems language.
go data races aren't memory safe
That does not make sense to me. Go is memory-safe, but it does not guarantee data-race freedom.
So whats your point here? Haskell?
Go is in no way automatically memory safe. It's up to the programmer to write memory safe code with it.
Go is broadly considered to be a memory safe language.
See for example comments from tptacek like:
https://news.ycombinator.com/item?id=43335748
https://news.ycombinator.com/item?id=46028232
https://news.ycombinator.com/item?id=44672371
(The gist: memory safety is a term of art coined by security practitioners. Go, Python, Rust, Java, others: memory safe. C/C++: memory unsafe. Periodically, people in different slices of industry or academia come up with new definitions of memory safety that declare Rust or Go or other languages to be memory unsafe, but that is not by the broadly accepted definition across industry.)
Rust does allow you to overflow buffers, confuse types, and duplicate mutable pointers in safe code. See cve-rs.
No idea why you're getting downvoted for true statement. Without a ? like in C# you're always at risk of a nil pointer being dereferenced
That throws a NullReferenceException
Cool, very clever. But at least the compiler warns me of a potential exception, whereas in Go no such op even exists.
you can dereference nil in Go and it panics
You can write unsafe code in Go (import unsafe), but then, you can do the same in Rust. Unsafe code is not the default, and in day to day Go i rarely see the use of the unsafe package.
I don’t understand this - how is it able to if the same go binary might run on unknown types? I’m assuming what it means is that the switch is implemented efficiently due to CPU branch prediction? I know fearless SIMD is doing cool stuff with static dispatch so that the feature set is checked just once at program start - is that what it means it’s doing under the hood? Very unclear.
It creates multiple versions of functions referencing SIMD and lifts the dispatch switching cost to their callers.
You'd think these people would know the meaning of API, no?
One wonders what overly-narrow definition of API you're stuck on.
This will welcome more database/warehouses to be written in Go.
Personally I will implement it in https://github.com/viggy28/streambed
C++ is getting std::simd in the latest version and I am all aboard writing the vectorization with the least amount of intrinsic builtins I am able to. Even if not optimal, it's far better than the scalar ops.
https://imjasonh.github.io/playground/palette-swap/ swaps colors in a provided image in wasm, entirely locally in your browser, to benchmark portable SIMD vs non-portable archsimd vs non-SIMD.
Portable SIMD is ~11% slower than non-portable SIMD in this case, but both are ~5x faster than non-SIMD.