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Macro(s) for vectorizing loops.

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Now if I run the following I get an error: ```julia a = collect(1:100) items = rand(20) indices = collect(1:20) @avx a[indices] .= items ``` ```julia ERROR: MethodError: no method...

This is a powerful and welcome tool. I would like to apply it to more packages. I have run into a limitation on supported types that seems more narrow than...

How would I multiply 2 16-bit integers and accumulate to 32-bit integer? Something like `_mm_madd_epi16` So far the result of the multiplication seems to be done in 16-bit: ```julia a...

Using `@turbo` loops gives incredible performance gains (10x) over the `LogExpFunctions` library for arrays of `Float64`s. However, the `@turbo` doesn't seem to play well with `FowardDiff.Dual` arrays and prints the...

When I compile my project with PackageCompiler.jl in Ubuntu or Windows, it fails with the following error related to LoopVectorization. It compiles in MacOS though. ``` - PackageCompiler: compiling nonincremental...

Hey all, I am eager to switch from `@inbounds @simd` to `@turbo` in the evaluation loops of [SymbolicRegression.jl](https://github.com/MilesCranmer/SymbolicRegression.jl), which is the backend for [PySR](https://github.com/MilesCranmer/PySR). You can see my initial pull...

Please see this issue, https://github.com/mcabbott/Tullio.jl/issues/155#issuecomment-1237286119

I have a reimplementation of `Linearlagebra.qr` in my codebase which uses `@turbo`. In it there is ```julia using LinearAlgebra, LoopVectorization, BenchmarkTools function reflectorApply!(x::AbstractVector{

vmapreduce_bugreport.jl: ``` using LoopVectorization f(a) = (a, a) g(a, b) = let (q, w) = a, (e, r) = b (min(q, e), max(w, r)) end myminmax_mapreduce(x) = mapreduce(f, g, x)...

### Discussed in https://github.com/JuliaSIMD/LoopVectorization.jl/discussions/421 Originally posted by **matthias314** August 16, 2022 It seems that destructuring assignments inside a loop may lead to wrong results. The example ``` function swap(v, w)...