# \[ANN\]: PaddedMatrices.jl, Julia BLAS and partially sized arrays

**URL:** https://discourse.julialang.org/t/ann-paddedmatrices-jl-julia-blas-and-partially-sized-arrays/38215
**Category:** Package Announcements
**Tags:** performance, blas
**Created:** [April 26, 2020, 3:11am UTC](https://discourse.julialang.org/t/ann-paddedmatrices-jl-julia-blas-and-partially-sized-arrays/38215 "2020-04-26T03:11:06Z")
**Posts on this page:** 1
**Showing post:** 30

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### Author: ![Elrod](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/elrod/32/22461_2.png) [@Elrod](https://discourse.julialang.org/u/Elrod)
#### Post date: [June 27, 2020, 6:52pm UTC](https://discourse.julialang.org/t/ann-paddedmatrices-jl-julia-blas-and-partially-sized-arrays/38215/30 "2020-06-27T18:52:14Z")

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> [@Mason](#):
>
> @Elrod’s work on PaddedMatrices.jl is strictly more promising than Gaius.jl, even if it’s multi-threading isn’t as good as Gaius.jl (last I checked, maybe this changed?)

It’s changed…in that PaddedMatrices no longer supports multi-threading.  
I may add multithreaded support again, but that would probably be motivated by the same “proof of concept” desire of seeing how efficient I could get it, with gold standards to optimize against.

MKL’s multithreading is extremely efficient, and also kicks in at a very small size. Importantly, it also helps when it does, unlike OpenBLAS which [tends to trip over its own threads](https://discourse.julialang.org/t/ann-recursivefactorization-jl/39213).

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