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Fix for sparse-to-sparse matrix broadcast #686

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Merged
kshyatt merged 6 commits into from
Feb 17, 2026
Merged

Fix for sparse-to-sparse matrix broadcast #686

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2804988
Fix for sparse-to-sparse matrix broadcast
kshyatt Feb 17, 2026
d277f66
Add test
kshyatt Feb 17, 2026
325497d
Fix test
kshyatt Feb 17, 2026
cdb4193
Fix again
kshyatt Feb 17, 2026
631d1c3
stupid fix
kshyatt Feb 17, 2026
6e2f7fd
Let int types work too
kshyatt Feb 17, 2026
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10 changes: 7 additions & 3 deletions src/host/sparse.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -670,7 +670,6 @@ end
if leading_dim ≤ leading_dim_size
iter = @inbounds iter_type(T, Ti)(leading_dim, args...)


output_ptrs = output isa GPUSparseDeviceMatrixCSR ? output.rowPtr : output.colPtr
output_ivals = output isa GPUSparseDeviceMatrixCSR ? output.colVal : output.rowVal
# fetch the row offset, and write it to the output
Expand All @@ -691,7 +690,6 @@ end
ptr = @inbounds ptrs[i]
_getindex(arg, I, ptr)
end

@inbounds output_ivals[output_ptr] = sub_leading_dim
@inbounds output.nzVal[output_ptr] = f(vals...)
output_ptr += one(Ti)
Expand Down Expand Up @@ -903,7 +901,13 @@ function Broadcast.copy(bc::Broadcasted{<:Union{GPUSparseVecStyle,GPUSparseMatSt
if output isa AbstractGPUSparseArray
args = (bc.f, output, offsets, bc.args...)
kernel = sparse_to_sparse_broadcast_kernel(get_backend(bc.args[first(sparse_args)]))
ndrange = output.nnz
ndrange = if sparse_typ <: AbstractGPUSparseVector
output.nnz
elseif sparse_typ <: AbstractGPUSparseMatrixCSC
size(output, 2)
else
size(output, 1)
end
else
args = sparse_typ <: AbstractGPUSparseVector ? (sparse_typ, bc.f, output, offsets, bc.args...) :
(sparse_typ, bc.f, output, bc.args...)
Expand Down
13 changes: 13 additions & 0 deletions test/testsuite/sparse.jl
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Expand Up @@ -283,6 +283,19 @@ function broadcasting_matrix(AT, eltypes)
dz = dx .* dy .* dw
@test dz isa AT{ET}
@test z == SparseMatrixCSC(dz)

# create a matrix with nnz < leading_dim
x = spdiagm(m, m, 2=>rand(ET, m - 2))
dx = AT(x)
y = ET(3) * x
dy = ET(3) * dx
@test y == SparseMatrixCSC(dy)

x = spdiagm(m, m, -2=>rand(ET, m - 2))
dx = AT(x)
y = ET(3) * x
dy = ET(3) * dx
@test y == SparseMatrixCSC(dy)
end
end
end
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