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Memo to self:
* update version number in `stdlib/OpenBLAS_jll/Project.toml`
* update version number and sha in `deps/openblas.version`
* refresh checksums with `make -f contrib/refresh_checksums.mk -j
openblas`
In the [release notes of
v0.3.26](https://github.com/OpenMathLib/OpenBLAS/releases/tag/v0.3.26)
one of the more interesting point is perhaps
> included support for Apple M1 and newer targets in DYNAMIC_ARCH builds
Quoting from
JuliaPackaging/Yggdrasil#7911 (comment)
> Some quick benchmarks on M1: with OpenBLAS 0.3.25:
> ```julia
> julia> using LinearAlgebra, BenchmarkTools
>
> julia> peakflops()
> 1.7049262964078418e11
>
> julia> x = randn(1_000); y = randn(size(x));
>
> julia> @Btime dot($x, $y);
> 402.705 ns (0 allocations: 0 bytes)
> ```
> with OpenBLAS v0.3.26:
> ```julia
> julia> using LinearAlgebra, BenchmarkTools
>
> julia> peakflops()
> 1.8042546290642157e11
>
> julia> x = randn(1_000); y = randn(size(x));
>
> julia> @Btime dot($x, $y);
> 143.777 ns (0 allocations: 0 bytes)
> ```
> Up to OpenBLAS v0.3.25 you can get similar performance on Apple
Silicon by exporting the environment variable
> ```sh
> OPENBLAS_CORETYPE=NEOVERSEN1
> ```
(cherry picked from commit b682592)
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