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A luxury sparse matrix package for Julia

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the 3-arg and 5-arg `mul!` is quite useful for ODE solvers, e.g the 5-arg `mul!` can be used in ODE solver directly and has no allocation comparing to `apply!` in...

I think now Julia broadcast uses a StructuredMatrix style to promote it to `SparseMatrixCSC`, no need to overload it anymore https://github.com/QuantumBFS/LuxurySparse.jl/blob/cc2d19a368b1107e9119efda90b0110c4b009c2a/src/arraymath.jl#L41

```julia julia> coo1 = SparseMatrixCOO( [1, 4, 2, 3, 3, 3], [1, 1, 2, 4, 3, 4], [0.1, 0.2, 0.4im, 0.5, 0.3, 0.5im], 4, 4, ) 4×4 SparseMatrixCOO{Complex{Float64},Int64}: 0.1+0.0im 0.0+0.0im...

bug

Right now, I'm working on in-place, CPU versions of `kronsum(A,B) = kron(A, oneunit(B)) + kron(oneunit(A), B)` So far, this works for dense arrays: ```julia function kronsum!(C::AbstractMatrix, A::AbstractMatrix, B::AbstractMatrix) Base.require_one_based_indexing(A, B)...

This package contains a lot workarounds which contains type piracy, need to check if they are in Base already or PR to upstream.

bug
high priority
upstream

need to wait for https://github.com/JuliaCI/PkgBenchmark.jl/pull/68

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