# Problem with GPU programming

**URL:** <https://discourse.julialang.org/t/problem-with-gpu-programming/28704>\
**Category:** GPU\
**Tags:** cudanative, cuda\
**Created:** [September 13, 2019, 12:49am UTC](https://discourse.julialang.org/t/problem-with-gpu-programming/28704 "2019-09-13T00:49:46Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![sergevic](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sergevic/32/9958_2.png) [@sergevic](https://discourse.julialang.org/u/sergevic)\
**Post date:** [September 13, 2019, 12:49am UTC](https://discourse.julialang.org/t/problem-with-gpu-programming/28704/1 "2019-09-13T00:49:46Z")

</div>

I have the following code that I can run on Julia v.1.1:

```julia
using LinearAlgebra

L=Symmetric(rand(Float32,10000,10000))
C=zeros(Float32,size(L,1),size(L,2))
D=zeros(Float32,size(L,1),size(L,2))
D[1,1]=1
k=750

function Lapprox!(C::Array{Float32,2},D::Array{Float32,2},i)
    m=min((i-1),k)
    N=Int32.(partialsortperm(L[i,1:(i-1)],1:m,rev=true))
    C[i,N]=L[N,N]\L[N,i]
    D[i,i]=L[i,i] - transpose(L[i,N])*C[i,N]
end

for i=2:size(C,1) Lapprox!(C,D,i) end

```

I want to take advantage of GPU programming, but I am starting with this type of programming… So far, I tried the following code:

```julia
using LinearAlgebra
using CuArrays
using CUDAnative

L=cu(Symmetric(rand(10000,10000)))
C=CuArray{Float32}(undef, size(L,1),size(L,2))
D=CuArray{Float32}(undef, size(L,1),size(L,2))
D[1,1]=1
k=750

function Lapprox!(C,D,i)
    m=min((i-1),k)
    N=Int32.(partialsortperm(L[i,1:(i-1)],1:m,rev=true))
    C[i,N]=L[N,N]\L[N,i]
    D[i,i]=L[i,i] - transpose(L[i,N])*C[i,N]
end

@cuda for i=2:size(C,1) Lapprox!(C,D,i) end

```

but it doesn’t work… Can anyone give me some insights for the function `Lapprox!` and `@cuda` macro line, please? Thank you!

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<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:** [September 13, 2019, 5:44am UTC](https://discourse.julialang.org/t/problem-with-gpu-programming/28704/2 "2019-09-13T05:44:29Z")

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That’s not now GPU programming works. Either you write a kernel function, not a for loop as you’re using here, and launch that with `@cuda`, or you write a function that you broadcast over an array, which you can run on the GPU by using CuArrays instead.

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<div class="post-metadata">

**Author:** ![sergevic](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sergevic/32/9958_2.png) [@sergevic](https://discourse.julialang.org/u/sergevic)\
**Post date:** [September 13, 2019, 3:57pm UTC](https://discourse.julialang.org/t/problem-with-gpu-programming/28704/3 "2019-09-13T15:57:19Z")

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Ok, thanks 🙂 I tried the function

```julia
function Lapprox!(C,D)
    i = (blockIdx().x-1) * blockDim().x + threadIdx().x
    m=min(i,k)
    N=Int32.(partialsortperm(L[i+1,1:i],1:m,rev=true))
    C[i+1,N]=L[N,N]\L[N,i+1]
    D[i+1,i+1]=L[i+1,i+1] - transpose(L[i+1,N])*C[i+1,N]
    return nothing
end

```

and `@cuda threads=12 Lapprox!(C,D)` but it doesn’t work.

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<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:** [September 13, 2019, 4:04pm UTC](https://discourse.julialang.org/t/problem-with-gpu-programming/28704/4 "2019-09-13T16:04:38Z")

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Those heavyweight functions (`transpose`, `partialsortperm`) are probably not GPU compatible. Furthermore, you need to be using GPU memory, i.e. `CuArray`s, for `C` and `D`. You’ll need to get some CUDA experience, using CUDAnative in Julia works at a similar abstraction level. Have a look at this tutorial: [https://juliagpu.gitlab.io/CuArrays.jl/tutorials/generated/intro/](https://juliagpu.gitlab.io/CuArrays.jl/tutorials/generated/intro/)

For a more high-level abstraction level, you can use the broadcasting functionality from CuArrays (similar to broadcasting on regular Arrays), but you’ll also need to take care about not calling GPU incompatible functionality.

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<div class="post-metadata">

**Author:** ![sergevic](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sergevic/32/9958_2.png) [@sergevic](https://discourse.julialang.org/u/sergevic)\
**Post date:** [September 13, 2019, 4:09pm UTC](https://discourse.julialang.org/t/problem-with-gpu-programming/28704/5 "2019-09-13T16:09:20Z")

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Yes, I think the problem is with the non-compatible functions. I think I saw something like this in the error message. Thanks for your suggestion 🙂 Will try to deal with it. CUDA seems interesting but if I’m not able to do it, I will go back to my regular code 🙂 As you said, it requires experience and I’m still new in GPU programming.