ArgumentError: cannot take the CPU address of a CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}

[zipeilee]

I have tried to solve a log() & eigvals() with a CuArray and I got

julia> d = rand(10,10) |> cu

julia> log(d)
ERROR: ArgumentError: cannot take the CPU address of a CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}
Stacktrace:
 [1] unsafe_convert(#unused#::Type{Ptr{Float32}}, x::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ CUDA ~/.julia/packages/CUDA/pCcGc/src/array.jl:370
 [2] gees!(jobvs::Char, A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra.LAPACK ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/lapack.jl:5926
 [3] schur!(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/schur.jl:103
 [4] schur(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/schur.jl:155
 [5] log(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/dense.jl:806
 [6] top-level scope
   @ REPL[4]:1
 [7] top-level scope
   @ ~/.julia/packages/CUDA/pCcGc/src/initialization.jl:171

julia> eigvals(d)
ERROR: ArgumentError: cannot take the CPU address of a CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}
Stacktrace:
 [1] unsafe_convert(#unused#::Type{Ptr{Float32}}, x::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ CUDA ~/.julia/packages/CUDA/pCcGc/src/array.jl:370
 [2] geevx!(balanc::Char, jobvl::Char, jobvr::Char, sense::Char, A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra.LAPACK ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/lapack.jl:2093
 [3] eigvals!(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}; permute::Bool, scale::Bool, sortby::typeof(LinearAlgebra.eigsortby))
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/eigen.jl:306
 [4] eigvals!(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/eigen.jl:304
 [5] eigvals(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer}; kws::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/eigen.jl:339
 [6] eigvals(A::CuArray{Float32, 2, CUDA.Mem.DeviceBuffer})
   @ LinearAlgebra ~/packages/julias/julia-1.9/share/julia/stdlib/v1.9/LinearAlgebra/src/eigen.jl:339
 [7] top-level scope
   @ REPL[9]:1
 [8] top-level scope
   @ ~/.julia/packages/CUDA/pCcGc/src/initialization.jl:171

Did I do something wrong?How can I correct it

[maleadt]

You're triggering CPU functionality, because those operations have not been implemented in CUDA.jl. There's some functionality regarding eigenvalues,

CUDA.jl/lib/cusolver/linalg.jl

Lines 113 to 134 in e531eab

	# eigenvalues
	function LinearAlgebra.eigen(A::Symmetric{T,<:CuMatrix}) where {T<:BlasReal}
	A2 = copy(A.data)
	Eigen(syevd!('V', 'U', A2)...)
	end
	function LinearAlgebra.eigen(A::Hermitian{T,<:CuMatrix}) where {T<:BlasComplex}
	A2 = copy(A.data)
	Eigen(heevd!('V', 'U', A2)...)
	end
	function LinearAlgebra.eigen(A::Hermitian{T,<:CuMatrix}) where {T<:BlasReal}
	eigen(Symmetric(A))
	end
	function LinearAlgebra.eigen(A::CuMatrix{T}) where {T<:BlasReal}
	A2 = copy(A)
	issymmetric(A) ? Eigen(syevd!('V', 'U', A2)...) : error("GPU eigensolver supports only Hermitian or Symmetric matrices.")
	end
	function LinearAlgebra.eigen(A::CuMatrix{T}) where {T<:BlasComplex}
	A2 = copy(A)
	ishermitian(A) ? Eigen(heevd!('V', 'U', A2)...) : error("GPU eigensolver supports only Hermitian or Symmetric matrices.")
	end

, but that only seems to work for symmetric/hermitian inputs.

[zipeilee]

Thanks, I got it