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remove copy-allocation on accessing cholesky factors (.L, .U) #1186

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merged 4 commits into from
Feb 5, 2025
Merged

remove copy-allocation on accessing cholesky factors (.L, .U) #1186

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35e8d2e
remove copy on property access
st-- Jan 29, 2025
b85c6d6
Merge branch 'master' into st/remove_chol_copy
ViralBShah Feb 2, 2025
15249bf
test fixes
st-- Feb 3, 2025
cb2e5c7
Merge branch 'st/remove_chol_copy' of github.com:st--/LinearAlgebra.j…
st-- Feb 3, 2025
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8 changes: 4 additions & 4 deletions src/cholesky.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,7 @@ julia> C.U
⋅ ⋅ 3.0

julia> C.L
3×3 LowerTriangular{Float64, Matrix{Float64}}:
3×3 LowerTriangular{Float64, Adjoint{Matrix{Float64}}}:
2.0 ⋅ ⋅
6.0 1.0 ⋅
-8.0 5.0 3.0
Expand Down Expand Up @@ -530,7 +530,7 @@ julia> C.U
⋅ ⋅ 3.0

julia> C.L
3×3 LowerTriangular{Float64, Matrix{Float64}}:
3×3 LowerTriangular{Float64, Adjoint{Matrix{Float64}}}:
2.0 ⋅ ⋅
6.0 1.0 ⋅
-8.0 5.0 3.0
Expand Down Expand Up @@ -668,14 +668,14 @@ function _choleskyUfactor(Cfactors, Cuplo)
if Cuplo === 'U'
return UpperTriangular(Cfactors)
else
return copy(LowerTriangular(Cfactors)')
return LowerTriangular(Cfactors)'
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@devmotion devmotion Feb 5, 2025 •
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I was slightly confused when reading this the first time, IMO from

Suggested change
return LowerTriangular(Cfactors)'
return UpperTriangular(Cfactors')

it would have been more obvious that in both branches an UpperTriangular is returned.

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Yes, we can do that as well.

end
end
function _choleskyLfactor(Cfactors, Cuplo)
if Cuplo === 'L'
return LowerTriangular(Cfactors)
else
return copy(UpperTriangular(Cfactors)')
return UpperTriangular(Cfactors)'
end
end

Expand Down
30 changes: 24 additions & 6 deletions test/cholesky.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -595,18 +595,18 @@ end
B = cholesky(A)
B32 = cholesky(Float32.(A))
@test B isa Cholesky{Float16, Matrix{Float16}}
@test B.U isa UpperTriangular{Float16, Matrix{Float16}}
@test B.L isa LowerTriangular{Float16, Matrix{Float16}}
@test B.UL isa UpperTriangular{Float16, Matrix{Float16}}
@test B.U isa UpperTriangular{Float16, <:AbstractMatrix{Float16}}
@test B.L isa LowerTriangular{Float16, <:AbstractMatrix{Float16}}
@test B.UL isa UpperTriangular{Float16, <:AbstractMatrix{Float16}}
@test B.U ≈ B32.U
@test B.L ≈ B32.L
@test B.UL ≈ B32.UL
@test Matrix(B) ≈ A
B = cholesky(A, RowMaximum())
B32 = cholesky(Float32.(A), RowMaximum())
@test B isa CholeskyPivoted{Float16,Matrix{Float16}}
@test B.U isa UpperTriangular{Float16, Matrix{Float16}}
@test B.L isa LowerTriangular{Float16, Matrix{Float16}}
@test B isa CholeskyPivoted{Float16, <:AbstractMatrix{Float16}}
@test B.U isa UpperTriangular{Float16, <:AbstractMatrix{Float16}}
@test B.L isa LowerTriangular{Float16, <:AbstractMatrix{Float16}}
@test B.U ≈ B32.U
@test B.L ≈ B32.L
@test Matrix(B) ≈ A
Expand Down Expand Up @@ -658,4 +658,22 @@ end
end
end

@testset "accessing both L and U factors should avoid allocations" begin
n = 30
A = rand(n, n)
Apd = A'A
allowed_cost_of_overhead = 32
@assert sizeof(Apd) > 4allowed_cost_of_overhead # ensure that we could positively identify extra copies

for uplo in (:L, :U)
C = Symmetric(Apd, uplo)
for val in (NoPivot(), RowMaximum())
B = cholesky(C, val)
B.L, B.U # access once to ensure the accessor is compiled already
@test (@allocated B.L) <= allowed_cost_of_overhead
@test (@allocated B.U) <= allowed_cost_of_overhead
end
end
end

end # module TestCholesky