# Use GPU to generate known sparse matrix

**URL:** <https://discourse.julialang.org/t/use-gpu-to-generate-known-sparse-matrix/33023>\
**Category:** GPU\
**Created:** [January 6, 2020, 11:34am UTC](https://discourse.julialang.org/t/use-gpu-to-generate-known-sparse-matrix/33023 "2020-01-06T11:34:16Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![FujiwaraTakumiEH](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/fujiwaratakumieh/32/37975_2.png) [@FujiwaraTakumiEH](https://discourse.julialang.org/u/FujiwaraTakumiEH)\
**Post date:** [January 6, 2020, 11:34am UTC](https://discourse.julialang.org/t/use-gpu-to-generate-known-sparse-matrix/33023/1 "2020-01-06T11:34:16Z")

</div>

Suppose we have a known matrix A:

\begin{equation} A=\left[\begin{array}{lll} {1} & {0} & {0} \\ {0} & {2} & {4} \\ {0} & {0} & {3} \end{array}\right] \end{equation}

At this point, I want to express A as a sparse matrix only by using `SparseArrays` in Julia. The code is as follows:

```julia
using SparseArrays

I = [1, 2, 2, 3]
J = [1, 2, 3, 3]
V = [1, 2, 4, 3]

A = sparse(I, J, V)

```

Result:

```julia
3×3 SparseMatrixCSC{Int64,Int64} with 4 stored entries:
  [1, 1] = 1
  [2, 2] = 2
  [2, 3] = 4
  [3, 3] = 3

```

Now I also have known `I`, `J`, and `V`. I want to generate sparse matrix in `CSR` or `CSC` format in GPU. The code is as follows:

```julia
using CuArrays

D_I = CuArray{Int64,1}(I)
D_J = CuArray{Int64,1}(J)
D_V = CuArray{Float32,1}(V)

CUSPARSE.sparse(D_I, D_J, D_V)

```

Result:

```julia
┌ Warning: Performing scalar operations on GPU arrays: This is very slow, consider disallowing these operations with `allowscalar(false)`
└ @ GPUArrays C:\Users\zenan\.julia\packages\GPUArrays\1wgPO\src\indexing.jl:16
3×3 SparseMatrixCSC{Float32,Int64} with 4 stored entries:
  [1, 1] = 1.0
  [2, 2] = 2.0
  [2, 3] = 4.0
  [3, 3] = 3.0

```

The way to generate sparse matrix in `CSC` format is very slow as shown in the result. Did I do something wrong? 😅

---

<div class="post-metadata">

**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [January 6, 2020, 12:17pm UTC](https://discourse.julialang.org/t/use-gpu-to-generate-known-sparse-matrix/33023/2 "2020-01-06T12:17:46Z")

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> [@FujiwaraTakumiEH](#):
>
> CUSPARSE.sparse(D\_I, D\_J, D\_V)

This function does not exist in CUSPARSE, and falls back to Base where scalar iteration happens:

```julia
julia> @which CUSPARSE.sparse(D_I, D_J, D_V)
sparse(I, J, V::AbstractArray{T,1} where T) in SparseArrays at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.3/SparseArrays/src/sparsematrix.jl:845

julia> CuArrays.allowscalar(false)

julia> CUSPARSE.sparse(D_I, D_J, D_V)
ERROR: scalar getindex is disallowed
Stacktrace:
 [1] error(::String) at ./error.jl:33
 [2] assertscalar(::String) at /home/tim/Julia/pkg/GPUArrays/src/indexing.jl:14
 [3] getindex at /home/tim/Julia/pkg/GPUArrays/src/indexing.jl:54 [inlined]
 [4] sparse!(::CuArray{Int64,1,Nothing}, ::CuArray{Int64,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::Int64, ::Int64, ::typeof(+), ::Array{Int64,1}, ::Array{Int64,1}, ::Array{Int64,1}, ::Array{Float32,1}, ::Array{Int64,1}, ::Array{Int64,1}, ::Array{Float32,1}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.3/SparseArrays/src/sparsematrix.jl:730
 [5] sparse(::CuArray{Int64,1,Nothing}, ::CuArray{Int64,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::Int64, ::Int64, ::Function) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.3/SparseArrays/src/sparsematrix.jl:660
 [6] sparse(::CuArray{Int64,1,Nothing}, ::CuArray{Int64,1,Nothing}, ::CuArray{Float32,1,Nothing}, ::Int64, ::Int64) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.3/SparseArrays/src/sparsematrix.jl:849
 [7] sparse(::CuArray{Int64,1,Nothing}, ::CuArray{Int64,1,Nothing}, ::CuArray{Float32,1,Nothing}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.3/SparseArrays/src/sparsematrix.jl:845
 [8] top-level scope at REPL[28]:1

```

You can however just call the `CuSparseMatrixCSC` constructor on your CPU `SparseMatrixCSC`, but that would reveal another nasty error:

```julia
julia> using CuArrays.CUSPARSE

julia> CuSparseMatrixCSC(A)
ERROR: MethodError: no method matching CuSparseMatrixCSC(::Array{Int64,1}, ::Array{Int64,1}, ::Array{Int64,1}, ::Tuple{Int64,Int64})

```

The problem here is that CUSPARSE [does not support](https://docs.nvidia.com/cuda/cusparse/index.html#cusparse-types-reference) sparse matrices with integer types. Using Float32 (or any other supported type) fixes that:

```julia
julia> A = sparse(Float32.(I), Float32.(J), Float32.(V))
3×3 SparseMatrixCSC{Float32,Int64} with 4 stored entries:
  [1, 1] = 1.0
  [2, 2] = 2.0
  [2, 3] = 4.0
  [3, 3] = 3.0

julia> CuSparseMatrixCSC(A)
3×3 CuSparseMatrixCSC{Float32}:
Error showing value of type CuSparseMatrixCSC{Float32}

```

Everything works now, except displaying the sparse matrix. This is a known issue: [Showing sparse arrays goes wrong · Issue #146 · JuliaGPU/CUDA.jl · GitHub](https://github.com/JuliaGPU/CuArrays.jl/issues/291) (the sparse functionality has not been getting as much love as the rest of the package).

---

<div class="post-metadata">

**Author:** ![FujiwaraTakumiEH](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/fujiwaratakumieh/32/37975_2.png) [@FujiwaraTakumiEH](https://discourse.julialang.org/u/FujiwaraTakumiEH)\
**Post date:** [January 6, 2020, 12:51pm UTC](https://discourse.julialang.org/t/use-gpu-to-generate-known-sparse-matrix/33023/3 "2020-01-06T12:51:19Z")

</div>

Thank you very much. 😀 I think I know what to do.