[oneMKL] Add support for oneSparseMatrixCSC#526
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Your PR requires formatting changes to meet the project's style guidelines. Click here to view the suggested changes.diff --git a/lib/mkl/array.jl b/lib/mkl/array.jl
index 0db254e..1931d4d 100644
--- a/lib/mkl/array.jl
+++ b/lib/mkl/array.jl
@@ -18,7 +18,7 @@ mutable struct oneSparseMatrixCSC{Tv, Ti} <: oneAbstractSparseMatrix{Tv, Ti}
colPtr::oneVector{Ti}
rowVal::oneVector{Ti}
nzVal::oneVector{Tv}
- dims::NTuple{2,Int}
+ dims::NTuple{2, Int}
nnz::Ti
end
@@ -46,7 +46,7 @@ SparseArrays.nnz(A::oneAbstractSparseMatrix) = A.nnz
SparseArrays.nonzeros(A::oneAbstractSparseMatrix) = A.nzVal
for (gpu, cpu) in [:oneSparseMatrixCSR => :SparseMatrixCSC,
- :oneSparseMatrixCSC => :SparseMatrixCSC,
+ :oneSparseMatrixCSC => :SparseMatrixCSC,
:oneSparseMatrixCOO => :SparseMatrixCSC]
@eval Base.show(io::IOContext, x::$gpu) =
show(io, $cpu(x))
diff --git a/lib/mkl/interfaces.jl b/lib/mkl/interfaces.jl
index 343131d..7ccc57e 100644
--- a/lib/mkl/interfaces.jl
+++ b/lib/mkl/interfaces.jl
@@ -7,9 +7,9 @@ function LinearAlgebra.generic_matvecmul!(C::oneVector{T}, tA::AbstractChar, A::
sparse_gemv!(tA, _add.alpha, A, B, _add.beta, C)
end
-function LinearAlgebra.generic_matvecmul!(C::oneVector{T}, tA::AbstractChar, A::oneSparseMatrixCSC{T}, B::oneVector{T}, _add::MulAddMul) where T <: BlasReal
+function LinearAlgebra.generic_matvecmul!(C::oneVector{T}, tA::AbstractChar, A::oneSparseMatrixCSC{T}, B::oneVector{T}, _add::MulAddMul) where {T <: BlasReal}
tA = tA in ('S', 's', 'H', 'h') ? 'T' : flip_trans(tA)
- sparse_gemv!(tA, _add.alpha, A, B, _add.beta, C)
+ return sparse_gemv!(tA, _add.alpha, A, B, _add.beta, C)
end
function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseMatrixCSR{T}, B::oneMatrix{T}, _add::MulAddMul) where T <: BlasFloat
@@ -18,16 +18,16 @@ function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseM
sparse_gemm!(tA, tB, _add.alpha, A, B, _add.beta, C)
end
-function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseMatrixCSC{T}, B::oneMatrix{T}, _add::MulAddMul) where T <: BlasReal
+function LinearAlgebra.generic_matmatmul!(C::oneMatrix{T}, tA, tB, A::oneSparseMatrixCSC{T}, B::oneMatrix{T}, _add::MulAddMul) where {T <: BlasReal}
tA = tA in ('S', 's', 'H', 'h') ? 'T' : flip_trans(tA)
tB = tB in ('S', 's', 'H', 'h') ? 'N' : tB
- sparse_gemm!(tA, tB, _add.alpha, A, B, _add.beta, C)
+ return sparse_gemm!(tA, tB, _add.alpha, A, B, _add.beta, C)
end
-function LinearAlgebra.generic_trimatdiv!(C::oneVector{T}, uploc, isunitc, tfun::Function, A::oneSparseMatrixCSR{T}, B::oneVector{T}) where T <: BlasFloat
- sparse_trsv!(uploc, tfun === identity ? 'N' : tfun === transpose ? 'T' : 'C', isunitc, one(T), A, B, C)
+function LinearAlgebra.generic_trimatdiv!(C::oneVector{T}, uploc, isunitc, tfun::Function, A::oneSparseMatrixCSR{T}, B::oneVector{T}) where {T <: BlasFloat}
+ return sparse_trsv!(uploc, tfun === identity ? 'N' : tfun === transpose ? 'T' : 'C', isunitc, one(T), A, B, C)
end
-function LinearAlgebra.generic_trimatdiv!(C::oneMatrix{T}, uploc, isunitc, tfun::Function, A::oneSparseMatrixCSR{T}, B::oneMatrix{T}) where T <: BlasFloat
- sparse_trsm!(uploc, tfun === identity ? 'N' : tfun === transpose ? 'T' : 'C', 'N', isunitc, one(T), A, B, C)
+function LinearAlgebra.generic_trimatdiv!(C::oneMatrix{T}, uploc, isunitc, tfun::Function, A::oneSparseMatrixCSR{T}, B::oneMatrix{T}) where {T <: BlasFloat}
+ return sparse_trsm!(uploc, tfun === identity ? 'N' : tfun === transpose ? 'T' : 'C', 'N', isunitc, one(T), A, B, C)
end
diff --git a/lib/mkl/wrappers_sparse.jl b/lib/mkl/wrappers_sparse.jl
index 360c00b..bb9df18 100644
--- a/lib/mkl/wrappers_sparse.jl
+++ b/lib/mkl/wrappers_sparse.jl
@@ -46,7 +46,7 @@ for (fname, elty, intty) in ((:onemklSsparse_set_csr_data , :Float32 , :Int3
nnzA = length(A.nzval)
queue = global_queue(context(nzVal), device())
$fname(sycl_queue(queue), handle_ptr[], n, m, 'O', colPtr, rowVal, nzVal) # CSC of A is CSR of Aᵀ
- dA = oneSparseMatrixCSC{$elty, $intty}(handle_ptr[], colPtr, rowVal, nzVal, (m,n), nnzA)
+ dA = oneSparseMatrixCSC{$elty, $intty}(handle_ptr[], colPtr, rowVal, nzVal, (m, n), nnzA)
finalizer(sparse_release_matrix_handle, dA)
return dA
end
@@ -122,19 +122,23 @@ for SparseMatrix in (:oneSparseMatrixCSR, :oneSparseMatrixCOO)
end
for SparseMatrix in (:oneSparseMatrixCSC,)
- for (fname, elty) in ((:onemklSsparse_gemv, :Float32),
- (:onemklDsparse_gemv, :Float64))
+ for (fname, elty) in (
+ (:onemklSsparse_gemv, :Float32),
+ (:onemklDsparse_gemv, :Float64),
+ )
@eval begin
- function sparse_gemv!(trans::Char,
- alpha::Number,
- A::$SparseMatrix{$elty},
- x::oneStridedVector{$elty},
- beta::Number,
- y::oneStridedVector{$elty})
+ function sparse_gemv!(
+ trans::Char,
+ alpha::Number,
+ A::$SparseMatrix{$elty},
+ x::oneStridedVector{$elty},
+ beta::Number,
+ y::oneStridedVector{$elty}
+ )
queue = global_queue(context(x), device())
$fname(sycl_queue(queue), flip_trans(trans), alpha, A.handle, x, beta, y)
- y
+ return y
end
end
end
@@ -187,27 +191,31 @@ function sparse_optimize_gemm!(trans::Char, transB::Char, nrhs::Int, A::oneSpars
return A
end
-for (fname, elty) in ((:onemklSsparse_gemm, :Float32),
- (:onemklDsparse_gemm, :Float64))
+for (fname, elty) in (
+ (:onemklSsparse_gemm, :Float32),
+ (:onemklDsparse_gemm, :Float64),
+ )
@eval begin
- function sparse_gemm!(transa::Char,
- transb::Char,
- alpha::Number,
- A::oneSparseMatrixCSC{$elty},
- B::oneStridedMatrix{$elty},
- beta::Number,
- C::oneStridedMatrix{$elty})
+ function sparse_gemm!(
+ transa::Char,
+ transb::Char,
+ alpha::Number,
+ A::oneSparseMatrixCSC{$elty},
+ B::oneStridedMatrix{$elty},
+ beta::Number,
+ C::oneStridedMatrix{$elty}
+ )
mB, nB = size(B)
mC, nC = size(C)
(nB != nC) && (transb == 'N') && throw(ArgumentError("B and C must have the same number of columns."))
(mB != nC) && (transb != 'N') && throw(ArgumentError("Bᵀ and C must have the same number of columns."))
nrhs = size(B, 2)
- ldb = max(1,stride(B,2))
- ldc = max(1,stride(C,2))
+ ldb = max(1, stride(B, 2))
+ ldc = max(1, stride(C, 2))
queue = global_queue(context(C), device())
$fname(sycl_queue(queue), 'C', flip_trans(transa), transb, alpha, A.handle, B, nrhs, ldb, beta, C, ldc)
- C
+ return C
end
end
end
@@ -243,19 +251,23 @@ for (fname, elty) in ((:onemklSsparse_symv, :Float32),
end
end
-for (fname, elty) in ((:onemklSsparse_symv, :Float32),
- (:onemklDsparse_symv, :Float64))
+for (fname, elty) in (
+ (:onemklSsparse_symv, :Float32),
+ (:onemklDsparse_symv, :Float64),
+ )
@eval begin
- function sparse_symv!(uplo::Char,
- alpha::Number,
- A::oneSparseMatrixCSC{$elty},
- x::oneStridedVector{$elty},
- beta::Number,
- y::oneStridedVector{$elty})
+ function sparse_symv!(
+ uplo::Char,
+ alpha::Number,
+ A::oneSparseMatrixCSC{$elty},
+ x::oneStridedVector{$elty},
+ beta::Number,
+ y::oneStridedVector{$elty}
+ )
queue = global_queue(context(y), device())
$fname(sycl_queue(queue), flip_uplo(uplo), alpha, A.handle, x, beta, y)
- y
+ return y
end
end
end
diff --git a/test/onemkl.jl b/test/onemkl.jl
index 95c0ed3..ef668dd 100644
--- a/test/onemkl.jl
+++ b/test/onemkl.jl
@@ -3,7 +3,7 @@ if Sys.iswindows()
else
using oneAPI
-using oneAPI.oneMKL: band, bandex, oneSparseMatrixCSR, oneSparseMatrixCOO, oneSparseMatrixCSC
+ using oneAPI.oneMKL: band, bandex, oneSparseMatrixCSR, oneSparseMatrixCOO, oneSparseMatrixCSC
using SparseArrays
using LinearAlgebra
@@ -1078,7 +1078,7 @@ end
@testset "SPARSE" begin
@testset "$T" for T in intersect(eltypes, [Float32, Float64, ComplexF32, ComplexF64])
- ε = sqrt(eps(real(T)))
+ ε = sqrt(eps(real(T)))
@testset "oneSparseMatrixCSR" begin
for S in (Int32, Int64)
@@ -1090,16 +1090,16 @@ end
end
end
- @testset "oneSparseMatrixCSC" begin
- (T isa Complex) && continue
- for S in (Int32, Int64)
- A = sprand(T, 20, 10, 0.5)
- A = SparseMatrixCSC{T, S}(A)
- B = oneSparseMatrixCSC(A)
- A2 = SparseMatrixCSC(B)
- @test A == A2
+ @testset "oneSparseMatrixCSC" begin
+ (T isa Complex) && continue
+ for S in (Int32, Int64)
+ A = sprand(T, 20, 10, 0.5)
+ A = SparseMatrixCSC{T, S}(A)
+ B = oneSparseMatrixCSC(A)
+ A2 = SparseMatrixCSC(B)
+ @test A == A2
+ end
end
- end
@testset "oneSparseMatrixCOO" begin
for S in (Int32, Int64)
@@ -1112,9 +1112,9 @@ end
end
@testset "sparse gemv" begin
- @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCOO, oneSparseMatrixCSR, oneSparseMatrixCSC)
+ @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCOO, oneSparseMatrixCSR, oneSparseMatrixCSC)
@testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
- (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
+ (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
A = sprand(T, 20, 10, 0.5)
x = transa == 'N' ? rand(T, 10) : rand(T, 20)
y = transa == 'N' ? rand(T, 20) : rand(T, 10)
@@ -1127,142 +1127,146 @@ end
beta = rand(T)
oneMKL.sparse_optimize_gemv!(transa, dA)
oneMKL.sparse_gemv!(transa, alpha, dA, dx, beta, dy)
- @test isapprox(alpha * opa(A) * x + beta * y, collect(dy), atol=ε)
+ @test isapprox(alpha * opa(A) * x + beta * y, collect(dy), atol = ε)
end
end
end
@testset "sparse gemm" begin
- @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR, oneSparseMatrixCSC)
- @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
- @testset "transb = $transb" for (transb, opb) in [('N', identity), ('T', transpose), ('C', adjoint)]
- (transb == 'N') || continue
- (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
- A = sprand(T, 10, 10, 0.5)
- B = transb == 'N' ? rand(T, 10, 2) : rand(T, 2, 10)
- C = rand(T, 10, 2)
+ @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR, oneSparseMatrixCSC)
+ @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
+ @testset "transb = $transb" for (transb, opb) in [('N', identity), ('T', transpose), ('C', adjoint)]
+ (transb == 'N') || continue
+ (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
+ A = sprand(T, 10, 10, 0.5)
+ B = transb == 'N' ? rand(T, 10, 2) : rand(T, 2, 10)
+ C = rand(T, 10, 2)
- dA = SparseMatrix(A)
- dB = oneMatrix{T}(B)
- dC = oneMatrix{T}(C)
+ dA = SparseMatrix(A)
+ dB = oneMatrix{T}(B)
+ dC = oneMatrix{T}(C)
- alpha = rand(T)
- beta = rand(T)
- oneMKL.sparse_optimize_gemm!(transa, dA)
- oneMKL.sparse_gemm!(transa, transb, alpha, dA, dB, beta, dC)
- @test isapprox(alpha * opa(A) * opb(B) + beta * C, collect(dC), atol=ε)
+ alpha = rand(T)
+ beta = rand(T)
+ oneMKL.sparse_optimize_gemm!(transa, dA)
+ oneMKL.sparse_gemm!(transa, transb, alpha, dA, dB, beta, dC)
+ @test isapprox(alpha * opa(A) * opb(B) + beta * C, collect(dC), atol = ε)
- oneMKL.sparse_optimize_gemm!(transa, transb, 2, dA)
- end
+ oneMKL.sparse_optimize_gemm!(transa, transb, 2, dA)
+ end
end
end
end
@testset "sparse symv" begin
- @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR, oneSparseMatrixCSC)
- @testset "uplo = $uplo" for uplo in ('L', 'U')
- (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
+ @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR, oneSparseMatrixCSC)
+ @testset "uplo = $uplo" for uplo in ('L', 'U')
+ (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
A = sprand(T, 10, 10, 0.5)
- A = A + transpose(A)
+ A = A + transpose(A)
x = rand(T, 10)
y = rand(T, 10)
- dA = uplo == 'L' ? SparseMatrix(A |> tril) : SparseMatrix(A |> triu)
+ dA = uplo == 'L' ? SparseMatrix(A |> tril) : SparseMatrix(A |> triu)
dx = oneVector{T}(x)
dy = oneVector{T}(y)
alpha = rand(T)
beta = rand(T)
- oneMKL.sparse_symv!(uplo, alpha, dA, dx, beta, dy)
- @test isapprox(alpha * A * x + beta * y, collect(dy), atol=ε)
+ oneMKL.sparse_symv!(uplo, alpha, dA, dx, beta, dy)
+ @test isapprox(alpha * A * x + beta * y, collect(dy), atol = ε)
end
end
end
- @testset "sparse trmv" begin
- @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR,)
- @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
- for (uplo, diag, wrapper) in [('L', 'N', LowerTriangular), ('L', 'U', UnitLowerTriangular),
- ('U', 'N', UpperTriangular), ('U', 'U', UnitUpperTriangular)]
- (transa == 'N') || continue
- (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
- A = sprand(T, 10, 10, 0.5)
- x = rand(T, 10)
- y = rand(T, 10)
+ @testset "sparse trmv" begin
+ @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR,)
+ @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
+ for (uplo, diag, wrapper) in [
+ ('L', 'N', LowerTriangular), ('L', 'U', UnitLowerTriangular),
+ ('U', 'N', UpperTriangular), ('U', 'U', UnitUpperTriangular),
+ ]
+ (transa == 'N') || continue
+ (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
+ A = sprand(T, 10, 10, 0.5)
+ x = rand(T, 10)
+ y = rand(T, 10)
- B = uplo == 'L' ? tril(A) : triu(A)
- B = diag == 'U' ? B - Diagonal(B) + I : B
- dA = SparseMatrix(B)
- dx = oneVector{T}(x)
- dy = oneVector{T}(y)
+ B = uplo == 'L' ? tril(A) : triu(A)
+ B = diag == 'U' ? B - Diagonal(B) + I : B
+ dA = SparseMatrix(B)
+ dx = oneVector{T}(x)
+ dy = oneVector{T}(y)
- alpha = rand(T)
- beta = rand(T)
+ alpha = rand(T)
+ beta = rand(T)
- oneMKL.sparse_optimize_trmv!(uplo, transa, diag, dA)
- oneMKL.sparse_trmv!(uplo, transa, diag, alpha, dA, dx, beta, dy)
- @test isapprox(alpha * wrapper(opa(A)) * x + beta * y, collect(dy), atol=ε)
- end
+ oneMKL.sparse_optimize_trmv!(uplo, transa, diag, dA)
+ oneMKL.sparse_trmv!(uplo, transa, diag, alpha, dA, dx, beta, dy)
+ @test isapprox(alpha * wrapper(opa(A)) * x + beta * y, collect(dy), atol = ε)
+ end
end
end
end
- @testset "sparse trsv" begin
- @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR,)
- @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
+ @testset "sparse trsv" begin
+ @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR,)
+ @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
for (uplo, diag, wrapper) in [('L', 'N', LowerTriangular), ('L', 'U', UnitLowerTriangular),
('U', 'N', UpperTriangular), ('U', 'U', UnitUpperTriangular)]
(transa == 'N') || continue
- (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
+ (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
alpha = rand(T)
A = rand(T, 10, 10) + I
A = sparse(A)
- x = rand(T, 10)
- y = rand(T, 10)
+ x = rand(T, 10)
+ y = rand(T, 10)
B = uplo == 'L' ? tril(A) : triu(A)
B = diag == 'U' ? B - Diagonal(B) + I : B
- dA = SparseMatrix(B)
- dx = oneVector{T}(x)
- dy = oneVector{T}(y)
-
- oneMKL.sparse_optimize_trsv!(uplo, transa, diag, dA)
- oneMKL.sparse_trsv!(uplo, transa, diag, alpha, dA, dx, dy)
- y = wrapper(opa(A)) \ (alpha * x)
- @test isapprox(y, collect(dy), atol=ε)
+ dA = SparseMatrix(B)
+ dx = oneVector{T}(x)
+ dy = oneVector{T}(y)
+
+ oneMKL.sparse_optimize_trsv!(uplo, transa, diag, dA)
+ oneMKL.sparse_trsv!(uplo, transa, diag, alpha, dA, dx, dy)
+ y = wrapper(opa(A)) \ (alpha * x)
+ @test isapprox(y, collect(dy), atol = ε)
+ end
end
end
end
- end
-
- @testset "sparse trsm" begin
- @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR,)
- @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
- @testset "transx = $transx" for (transx, opx) in [('N', identity), ('T', transpose), ('C', adjoint)]
- (transx != 'N') && continue
- for (uplo, diag, wrapper) in [('L', 'N', LowerTriangular), ('L', 'U', UnitLowerTriangular),
- ('U', 'N', UpperTriangular), ('U', 'U', UnitUpperTriangular)]
- (transa == 'N') || continue
- (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
- alpha = rand(T)
- A = rand(T, 10, 10) + I
- A = sparse(A)
- X = transx == 'N' ? rand(T, 10, 4) : rand(T, 4, 10)
- Y = rand(T, 10, 4)
- B = uplo == 'L' ? tril(A) : triu(A)
- B = diag == 'U' ? B - Diagonal(B) + I : B
- dA = SparseMatrix(B)
- dX = oneMatrix{T}(X)
- dY = oneMatrix{T}(Y)
-
- oneMKL.sparse_optimize_trsm!(uplo, transa, diag, dA)
- oneMKL.sparse_trsm!(uplo, transa, transx, diag, alpha, dA, dX, dY)
- Y = wrapper(opa(A)) \ (alpha * opx(X))
- @test isapprox(Y, collect(dY), atol=ε)
-
- oneMKL.sparse_optimize_trsm!(uplo, transa, diag, 4, dA)
- end
+ @testset "sparse trsm" begin
+ @testset "$SparseMatrix" for SparseMatrix in (oneSparseMatrixCSR,)
+ @testset "transa = $transa" for (transa, opa) in [('N', identity), ('T', transpose), ('C', adjoint)]
+ @testset "transx = $transx" for (transx, opx) in [('N', identity), ('T', transpose), ('C', adjoint)]
+ (transx != 'N') && continue
+ for (uplo, diag, wrapper) in [
+ ('L', 'N', LowerTriangular), ('L', 'U', UnitLowerTriangular),
+ ('U', 'N', UpperTriangular), ('U', 'U', UnitUpperTriangular),
+ ]
+ (transa == 'N') || continue
+ (T <: Complex) && (SparseMatrix == oneSparseMatrixCSC) && continue
+ alpha = rand(T)
+ A = rand(T, 10, 10) + I
+ A = sparse(A)
+ X = transx == 'N' ? rand(T, 10, 4) : rand(T, 4, 10)
+ Y = rand(T, 10, 4)
+
+ B = uplo == 'L' ? tril(A) : triu(A)
+ B = diag == 'U' ? B - Diagonal(B) + I : B
+ dA = SparseMatrix(B)
+ dX = oneMatrix{T}(X)
+ dY = oneMatrix{T}(Y)
+
+ oneMKL.sparse_optimize_trsm!(uplo, transa, diag, dA)
+ oneMKL.sparse_trsm!(uplo, transa, transx, diag, alpha, dA, dX, dY)
+ Y = wrapper(opa(A)) \ (alpha * opx(X))
+ @test isapprox(Y, collect(dY), atol = ε)
+
+ oneMKL.sparse_optimize_trsm!(uplo, transa, diag, 4, dA)
+ end
end
end
end |
Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #526 +/- ##
==========================================
+ Coverage 79.70% 79.95% +0.24%
==========================================
Files 45 45
Lines 2818 2878 +60
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Can we support the complex case too? Actually, I was working yesterday on it too 🙂 . I got the complex case for gemv and gemm working. Maybe we can merge somehow. I'll check. |
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We can support the complex case for |
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@michel2323 I started to work on the support of
oneSparseMatrixCSC.We can work on it together if you want.