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Build the GPU lu_instance directly instead of calling lu #502

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Merged
ChrisRackauckas merged 1 commit into from
Aug 18, 2026
+10 −2
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Build the GPU lu_instance directly instead of calling lu #502

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12 changes: 10 additions & 2 deletions ext/ArrayInterfaceGPUArraysCoreExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ module ArrayInterfaceGPUArraysCoreExt

using Adapt
using ArrayInterface
using LinearAlgebra: lu
import LinearAlgebra
import GPUArraysCore

ArrayInterface.fast_scalar_indexing(::Type{<:GPUArraysCore.AbstractGPUArray}) = false
Expand All @@ -19,8 +19,16 @@ function ArrayInterface.restructure(x::GPUArraysCore.AbstractGPUArray, y)
reshape(Adapt.adapt(ArrayInterface.parameterless_type(x), y), Base.size(x)...)
end

# Build the `LU` directly rather than calling `lu` on an adapted array, matching the CPU
# methods in ArrayInterface.jl. Going through `lu` only works for backends that define their
# own, so it breaks on JLArrays (which downstream packages use to test GPU paths without a
# GPU) and on Metal, see #501 and #467.
function ArrayInterface.lu_instance(A::GPUArraysCore.AbstractGPUMatrix{T}) where {T}
lu(Adapt.adapt(ArrayInterface.parameterless_type(A), ones(T, 0, 0)))
noUnitT = typeof(zero(T))
luT = LinearAlgebra.lutype(noUnitT)
ipiv = similar(A, LinearAlgebra.BlasInt, 0)
info = zero(LinearAlgebra.BlasInt)
return LinearAlgebra.LU{luT}(similar(A, 0, 0), ipiv, info)
end

# Doesn't do much, but makes a gigantic change to the dependency chain.
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