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Re-use device buffer in yuy2 cuda helper #11737

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@attiladoor attiladoor commented Apr 27, 2023

  • add a new device buffer class which only re-allocated on demand
  • make the buffer instances static to preserve them between frames

Related issue: #11692 (comment)

Nsight systems profiling:

realsense_profiling

As we can see, there is no allocation being done at the yuy2 conversion

- add a new device buffer class which only re-allocated on demand
- make the buffer instances static to preserve them between frames

Github issue: IntelRealSense#11692 (comment)
static T* allocateBuffer(std::size_t const reserve_size)
{
T* datatemp{nullptr};
cudaMalloc(&datatemp, reserve_size * sizeof(T));
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maybe i can add an assert to the return value of cudaMalloc and cudaFree above. What do you think?

@@ -284,7 +286,7 @@ void rscuda::unpack_yuy2_cuda_helper(const uint8_t* h_src, uint8_t* h_dst, int n

cudaDeviceSynchronize();
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In my opinion, this is unnecessary, but better to use async copy and use the same stream across the whole function and do a stream syncronization before we return from this function. By that we can avoid extra syncing, however the gain would be probably not very significant.

https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__MEMORY.html#group__CUDART__MEMORY_1g85073372f776b4c4d5f89f7124b7bf79

@Nir-Az
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Nir-Az commented May 2, 2023

Thanks for the PR, we will investigate this issue & fix :)

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2 participants