# Passing array of pointers to CUDA kernel

**URL:** <https://discourse.julialang.org/t/passing-array-of-pointers-to-cuda-kernel/33570>\
**Category:** GPU\
**Tags:** question, cudanative, memory-allocation\
**Created:** [January 20, 2020, 6:18am UTC](https://discourse.julialang.org/t/passing-array-of-pointers-to-cuda-kernel/33570 "2020-01-20T06:18:26Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![Michael\_Benton](https://avatars.discourse-cdn.com/v4/letter/m/e68b1a/32.png) [@Michael\_Benton](https://discourse.julialang.org/u/Michael_Benton)\
**Post date:** [January 20, 2020, 6:18am UTC](https://discourse.julialang.org/t/passing-array-of-pointers-to-cuda-kernel/33570/1 "2020-01-20T06:18:26Z")

</div>

I need to be able to stack arbitrarily sized cuarrays and CuTextures as a single input to a kernel, so I can do operations in the kernel that loop over the data like so:

(get [GitHub - cdsousa/CuTextures.jl: [DEPRECATED, moved into CUDA.jl] CUDA textures ("CUDA arrays") interface for native Julia](https://github.com/cdsousa/CuTextures.jl) to run example)

```julia
using CuTextures, CuArrays, CUDAnative, CUDAdrv
myImages = [CuTexture(CuTextureArray(CuArrays.rand(2,2))) for i = 1:20];
out = CuArrays.rand(1);
function myKernel!(myImages,out)
  for i = 1:length(myImages)
    out += myImages[i](1.3,1.2)
  end
  return nothing
end
@cuda threads=1 blocks=1 myKernel!(myImages,out)

```

The above errors out because “passing and using non-bitstype argument”

Is there a way to do this right now, or will there be?

My application requires n dimensional stacks of 2d images, and the reason I cannot simply concatenate them into three dimensional images, is because of the resulting memory allocation problem when I have to replace only one of many images

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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:** [January 20, 2020, 7:45am UTC](https://discourse.julialang.org/t/passing-array-of-pointers-to-cuda-kernel/33570/2 "2020-01-20T07:45:24Z")

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> [@Michael\_Benton](#):
>
> myImages = [CuTexture(CuTextureArray(CuArrays.rand(2,2))) for i = 1:20];

This is a _CPU_ array of CuTexture objects, which you can’t pass to the GPU. You need a CuArray instead.

You also need to know that GPU objects you instantiate on the CPU (e.g. CuArray, CuTexture) don’t get copied as-is to the GPU. They get converted at the time of `@cuda` to a device-side counterpart (e.g. CuDeviceArray, CuDeviceTexture). This conversion does not automatically happen for the elements of an array, so you will need to call `cudaconvert` explicitly on the `CuTexture` objects. If you were to pass a Tuple instead, the elements would get auto-converted (but using Tuples has other trade-offs, of course).

---

<div class="post-metadata">

**Author:** ![Michael\_Benton](https://avatars.discourse-cdn.com/v4/letter/m/e68b1a/32.png) [@Michael\_Benton](https://discourse.julialang.org/u/Michael_Benton)\
**Post date:** [January 20, 2020, 5:00pm UTC](https://discourse.julialang.org/t/passing-array-of-pointers-to-cuda-kernel/33570/3 "2020-01-20T17:00:09Z")

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ok, for reference the following works, thanks again for the help, Tim

```julia
function krn(im,out)
  val = out[1]
  for i = 1:length(im)
    val += im[i](Float32(1.2),Float32(1.2))
  end
  out[1] = val
  return nothing
end

out = CuArrays.rand(1);

im = CuArray([cudaconvert(CuTexture(CuTextureArray(CuArrays.rand(2,2)))) for i = 1:20]);

@cuda threads=1 blocks=1 krn(im,out)

```