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A Julia package for describing array layouts and more general fast linear algebra

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It turns out that the definition outside of the scope of the macro doesn't work properly.

```julia julia> @time using ArrayLayouts 2.144474 seconds (4.45 M allocations: 381.961 MiB, 17.67% compilation time) ``` ```julia julia> @time_imports using ArrayLayouts 231.6 ms FillArrays 1527.5 ms ArrayLayouts ``` Maybe the...

```julia julia> B = BandedMatrix(-3=> 2ones(2), -1=>ones(4), 0=>2ones(5)); Buplo = :L; SB = Symmetric(B, Buplo); julia> cholesky(Matrix(SB), check = false) Failed factorization of type Cholesky{Float64, Matrix{Float64}} julia> cholesky(SB, check =...

Hi there. I'm keen to use ArrayLayouts in some upcoming sparse ecosystem stuff. Not so much for the generic linalg but just for the traits. In light of that would...

Any chance of seeing `SparseRowMajor` and `SparseColumnMajor` layout support?

```julia julia> A = zeros(1,1) * BandedMatrix(0=>Zeros(∞))[1:1,1:1] * zeros(1,1) (1×1 Array{Float64,2}) * (1×1 BandedMatrix{Float64} with bandwidths (0, 0) with data (1×0 view(::Array{Float64,2}, 1:1, 1:0) with eltype Float64) * (0×1 view(::LazyArrays.ApplyArray{Float64,2,typeof(vcat),Tuple{Zeros{Float64,2,Tuple{Base.OneTo{Int64},InfiniteArrays.OneToInf{Int64}}}}},...

Hello, I open this issue to discuss the implementation of `TrapezoidalLayout`, see (https://discourse.julialang.org/t/view-of-lowermatrix-is-not-working-with-ldiv-and-mul/44046/2). This will be helpful to perform `ldiv!, mul!` on views of triangular matrices for instance.

Following is wrong: ```julia julia> n = 5; c = randn(n); ArrayLayouts.mul(c',randn(n,n)) 1×5 Array{Float64,2}: -0.938636 -0.342143 -2.26487 0.425856 0.777063 ``` This fix takes some care as we don't have a...

Hi @dlfivefifty, Just opening an issue to have a place to discuss this. Would this package make it easy to deal with different storage backends as well? In CuArrays we...