Skip to content

Add correct storage_type for lazy wrapped GPU arrays (adjoint, transpose, Diagonal) #365

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
merged 5 commits into from
Apr 9, 2025
Merged

Add correct storage_type for lazy wrapped GPU arrays (adjoint, transpose, Diagonal) #365

Show file tree
Hide file tree
Changes from 4 commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
612e56f
Add storage_type for adjoint, tranpose and Diagonal s.t. they work fo…
Feb 6, 2025
8c1037b
Make lazy wrapper tests for GPUs more consistent
nHackel Feb 18, 2025
7c4924a
Update test/gpu/nvidia.jl
dpo Apr 9, 2025
ad2a141
Update test/gpu/nvidia.jl
dpo Apr 9, 2025
4fa6e9f
Update test/gpu/amdgpu.jl
dpo Apr 9, 2025
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
5 changes: 5 additions & 0 deletions src/abstract.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -174,6 +174,11 @@ storage_type(op::AbstractLinearOperator) = error("please implement storage_type
storage_type(op::LinearOperator) = typeof(op.Mv5)
storage_type(M::AbstractMatrix{T}) where {T} = Vector{T}

# Lazy wrappers
storage_type(op::Adjoint) = storage_type(parent(op))
storage_type(op::Transpose) = storage_type(parent(op))
storage_type(op::Diagonal) = typeof(parent(op))

"""
reset!(op)

Expand Down
6 changes: 6 additions & 0 deletions test/gpu/amdgpu.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,5 +11,11 @@ using LinearOperators, AMDGPU
y = M * v
@test y isa ROCArray{Float32}

@test LinearOperators.storage_type(A) == LinearOperators.storage_type(adjoint(A))
@test LinearOperators.storage_type(A) == LinearOperators.storage_type(transpose(A))
@test LinearOperators.storage_type(A) == LinearOperators.storage_type(adjoint(A))
@test LinearOperators.storage_type(Diagonal(v)) == typeof(v)


@testset "AMDGPU S kwarg" test_S_kwarg(arrayType = ROCArray)
end
6 changes: 6 additions & 0 deletions test/gpu/nvidia.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,5 +13,11 @@ using LinearOperators, CUDA, CUDA.CUSPARSE, CUDA.CUSOLVER
v = CUDA.rand(35)
y = M * v
@test y isa CuVector{Float32}

@test LinearOperators.storage_type(A) == LinearOperators.storage_type(adjoint(A))
@test LinearOperators.storage_type(A) == LinearOperators.storage_type(transpose(A))
@test LinearOperators.storage_type(A) == LinearOperators.storage_type(adjoint(A))
@test LinearOperators.storage_type(Diagonal(v)) == typeof(v)

@testset "Nvidia S kwarg" test_S_kwarg(arrayType = CuArray)
end