Skip to content

GPU comutations #120

Description

@hosseinrezaa

Hi
I installed the splishsplash on a machine with Quadro p5000 GPU. But when I am running te code it seems that GPU is not active.
What should I do to perform the calculations with GPU.
Untitled
Regards

Activity

  1. janbender commented on Sep 23, 2021

    @janbender
    Member

    You have to activate the CMake option "USE_GPU_NEIGHBORHOODSEARCH".

  2. hosseinrezaa commented on Sep 23, 2021

    @hosseinrezaa
    Author

    I have activated the option "USE_GPU_NEIGHBORHOODSEARCH". But when I run the program still cannot run by GPU. Is there any adjustment in Visual Studio? or windows?

  3. janbender commented on Sep 24, 2021

    @janbender
    Member

    Did you install Cuda?

  4. hosseinrezaa commented on Sep 24, 2021

    @hosseinrezaa
    Author

    Yes, Cuda toolkit 10.1

  5. janbender commented on Sep 28, 2021

    @janbender
    Member

    Do you see a message "Use cuNSearch for neighborhood search" when you execute CMake?

  6. hosseinrezaa commented on Sep 28, 2021

    @hosseinrezaa
    Author

    Yes. I use cmake and I see this message. But when I try to run the C++ program using Visual studio only it uses the CPU .

    If your CPU does not support AVX, turn off the USE_AVX flag.
    Using Win32 for window creation
    Use cuNSearch for neighborhood search
    The CUDA compiler identification is NVIDIA 11.4.120
    Detecting CUDA compiler ABI info
    Detecting CUDA compiler ABI info - done
    Check for working CUDA compiler: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.4/bin/nvcc.exe - skipped
    Detecting CUDA compile features
    Detecting CUDA compile features - done
    Found CUDA: C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.4 (found suitable version "11.4", minimum required is "9.0")
    Configuring done
    Generating done

  7. janbender commented on Sep 28, 2021

    @janbender
    Member

    That is not possible since cuNSearch is used which does not implement any CPU computation.

  8. janbender commented on Sep 28, 2021

    @janbender
    Member

    Note that most of the work is done in the pressure solver which is not implemented on the GPU. There is one pull request with a Cuda implementation. However, in our tests this was slower than avx.

  9. hosseinrezaa commented on Sep 28, 2021

    @hosseinrezaa
    Author

    I am now running the code

    image

  10. hosseinrezaa commented on Sep 28, 2021

    @hosseinrezaa
    Author

    So it is using the GPU and if I need faster runs should I try with better devices?

  11. janbender commented on Sep 28, 2021

    @janbender
    Member

    The most time consuming part is typically the pressure solver. The fastest one is DFSPH with AVX support. As far as I can see you are also using an implicit viscosity solver. This means that another linear system has to be solved which is also time consuming.

    More CPU cores will help to make the simulation faster.

  12. hosseinrezaa commented on Sep 28, 2021

    @hosseinrezaa
    Author

    Thank you so much

  13. nobane commented on Jan 8, 2022

    @nobane

    The correct option to pass to cmake is -DUSE_GPU_NEIGHBORHOOD_SEARCH=On.

  14. chunleili commented on Mar 29, 2022

    @chunleili

    I am now running the code

    image

    I have the same problem with you. The usage of GPU is really low, so I dont know whether the GPU is used. And I dont feel the simulation become faster.

  15. locked and limited conversation to collaborators on Mar 29, 2022
  16. converted this issue into a discussion #164 on Mar 29, 2022
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Type

    No type

    Projects

    No projects

      Milestone

      No milestone

      Relationships

      None yet

      Development

      No branches or pull requests

      Issue actions