Implementation of spdiagm for CUSPARSE (#2458)

Co-authored-by: Alexis Montoison <35051714+amontoison@users.noreply.github.com>

Author: walexaindre

lib/cusparse/array.jl

@@ -322,6 +322,16 @@ function SparseArrays.sparsevec(I::CuArray{Ti}, V::CuArray{Tv}, n::Integer) wher
     CuSparseVector(I, V, n)
 end
 
+function SparseArrays.spdiagm(v::CuVector{Tv}) where {Tv}
+    nzVal = v
+    N = Int32(length(nzVal))
+    
+    colPtr = CuArray(one(Int32):(N + one(Int32)))
+    rowVal = CuArray(one(Int32):N)
+    dims = (N, N)
+    CuSparseMatrixCSC(colPtr, rowVal, nzVal, dims)
+end
+
 LinearAlgebra.issymmetric(M::Union{CuSparseMatrixCSC,CuSparseMatrixCSR}) = size(M, 1) == size(M, 2) ? norm(M - transpose(M), Inf) == 0 : false
 LinearAlgebra.ishermitian(M::Union{CuSparseMatrixCSC,CuSparseMatrixCSR}) = size(M, 1) == size(M, 2) ? norm(M - adjoint(M), Inf) == 0 : false
 LinearAlgebra.issymmetric(M::Symmetric{CuSparseMatrixCSC}) = true

test/libraries/cusparse/interfaces.jl

@@ -538,3 +538,21 @@ using LinearAlgebra, SparseArrays
         end
     end
 end
+
+@testset "SparseArrays" begin
+    @testset "spdiagm(CuVector{$elty})" for elty in [Float32, Float64, ComplexF32, ComplexF64]
+        ref_vec = collect(elty, 100:121)
+        cuda_vec = CuVector(ref_vec)
+
+        ref_spdiagm = spdiagm(ref_vec) # SparseArrays
+        cuda_spdiagm = spdiagm(cuda_vec) # CuSparseMatrixCSC
+
+        ref_cuda_sparse = CuSparseMatrixCSC(ref_spdiagm)
+
+        @test ref_cuda_sparse.rowVal == cuda_spdiagm.rowVal
+
+        @test ref_cuda_sparse.nzVal == cuda_spdiagm.nzVal
+
+        @test ref_cuda_sparse.colPtr == cuda_spdiagm.colPtr
+    end
+end