Skip to content

Fix sparse CSC matrix multiplication #602

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
michel2323 merged 2 commits into from
Aug 2, 2026
Merged

Fix sparse CSC matrix multiplication #602

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
442b087
Fix transposed result from sparse CSC matrix multiplication
michel2323 Aug 2, 2026
1f20d19
Support complex element types in sparse CSC multiplication
michel2323 Aug 2, 2026
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 6 additions & 4 deletions lib/mkl/interfaces.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,8 +17,9 @@ function LinearAlgebra.generic_matvecmul!(C::oneVector{T}, tA::AbstractChar, A::
return sparse_gemv!(tA, alpha, A, B, beta, C)
end

function LinearAlgebra.generic_matvecmul!(C::oneVector{T}, tA::AbstractChar, A::oneSparseMatrixCSC{T}, B::oneVector{T}, alpha::Number, beta::Number) where {T <: BlasReal}
tA = tA in ('S', 's', 'H', 'h') ? 'T' : flip_trans(tA)
function LinearAlgebra.generic_matvecmul!(C::oneVector{T}, tA::AbstractChar, A::oneSparseMatrixCSC{T}, B::oneVector{T}, alpha::Number, beta::Number) where {T <: BlasFloat}
# sparse_gemv! already maps op(A) onto the transposed CSR handle, so tA is passed through
tA = tA in ('S', 's', 'H', 'h') ? 'N' : tA
return sparse_gemv!(tA, alpha, A, B, beta, C)
end

Expand All @@ -28,8 +29,9 @@ function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseM
return sparse_gemm!(tA, tB, alpha, A, B, beta, C)
end

function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseMatrixCSC{T}, B::oneMatrix{T}, alpha::Number, beta::Number) where {T <: BlasReal}
tA = tA in ('S', 's', 'H', 'h') ? 'T' : flip_trans(tA)
function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseMatrixCSC{T}, B::oneMatrix{T}, alpha::Number, beta::Number) where {T <: BlasFloat}
# sparse_gemm! already maps op(A) onto the transposed CSR handle, so tA is passed through
tA = tA in ('S', 's', 'H', 'h') ? 'N' : tA
tB = tB in ('S', 's', 'H', 'h') ? 'N' : tB
return sparse_gemm!(tA, tB, alpha, A, B, beta, C)
end
Expand Down
26 changes: 26 additions & 0 deletions test/onemkl.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1175,6 +1175,32 @@ end
end
end

# `*` and `mul!` reach oneMKL through generic_matvecmul!/generic_matmatmul!, which is
# a separate mapping from the sparse_gemv!/sparse_gemm! calls exercised above
@testset "sparse LinearAlgebra mul" begin
@testset "$SparseMatrix" for SparseMatrix in csr_csc_matrices
A = sprand(T, 10, 10, 0.5)
x = rand(T, 10)
y = rand(T, 10)
B = rand(T, 10, 2)
C = rand(T, 10, 2)

dA = SparseMatrix(A)
dx = oneVector{T}(x)
dB = oneMatrix{T}(B)

@testset "opa = $(nameof(opa))" for opa in (identity, transpose, adjoint)
@test opa(A) * x ≈ collect(opa(dA) * dx)
@test opa(A) * B ≈ collect(opa(dA) * dB)
end

alpha = rand(T)
beta = rand(T)
@test alpha * A * x + beta * y ≈ collect(mul!(oneVector{T}(y), dA, dx, alpha, beta))
@test alpha * A * B + beta * C ≈ collect(mul!(oneMatrix{T}(C), dA, dB, alpha, beta))
end
end

@testset "sparse symv" begin
@testset "$SparseMatrix" for SparseMatrix in csr_csc_matrices
@testset "uplo = $uplo" for uplo in ('L', 'U')
Expand Down
Loading