Implement Butterfly Factorization method using RecursiveFactorization.jl #785
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@oscardssmith does this look good? |
ChrisRackauckas
requested changes
Sep 28, 2025
| B, U, V = cache.cacheval[2], cache.cacheval[3], cache.cacheval[4] | ||
| if cache.isfresh | ||
| @assert M==N "A must be square" | ||
| U, V, F, out = RecursiveFactorization.🦋workspace(A, b, B, U, V, alg.thread) |
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Why is this not just a struct and ! operation? It would be much easier to read. I assume this is all just in-place and non-allocating.
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as in make U, V, F, out a struct?
| end | ||
| end | ||
| A, B, U, V, F = cache.cacheval | ||
| sol = V * (F \ (U * b)) |
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This is allocating and not using TriangularSolve.jl?
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I think we found that TriangularSolve.jl was slower than this method, so we left it as is
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Checklist
contributor guidelines, in particular the SciML Style Guide and
COLPRAC.
Additional context
Implements a new
ButterflyFactorization()algorithm