RTX 4060 TI - MapSMtoCores for SM 8.9 is undefined

[Newbie-omvs]

Describe the bug
i can't build Openmvs for my new graphic card

To Reproduce
I am an absolutely Newbie on cmake, VS 2019 and these things. also on Win 10.

1. Installed all the dependencies , Cuda 12.4.1 Visual Studio 2019 as in build.md

2. in cmake-gui changed the CMAKE_CUDA_ARCHITECTURES to 89 and start configure. The log shows a red "Compiling with C++20" and the red lined "... policy CMP0146" FINDCUDA module is removed. After generate and open project in VS 2019 in the Project settings is no change from compute_52 sm_52 to compute_89 sm_89. Build Debug and Release runs without any error but the MapSMtoCores 8.9 is undefined.

3. I'm tested it with selected max cuda comatibility - same Problem

4. set compute_89 sm_89 by hand in VS 2019 - same Problem

5. in cmake i have 4 DIR-NOTFOUND: BREAKPAD, CUDA_SDK_ROOT_DIR, Tiff_DIR and Z_VCPKG_PWSH_PATH
   Breakpad is not installed,
   Tiff_DIR is set to C:\src\vcpkg\installed\x64-windows\share\tiff
   Z_VCPKG_PWSH_PATH is set to C:\Windows\System32\WindowsPowerShell\v1.0
   CUDA_SDK_ROOT_DIR I'm don't know, set it for testing to C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.4

6. See error

Expected behavior
A clear and concise description of what you expected to happen.

Screenshots
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Desktop (please complete the following information):

• MP 7.1 Bootcamp
• win 10 on USB-SSD
• CUDA 12.4.1 (updated this mornnig)
• MS Visual Studio 16 (2019)
• Nvidia Geforce RTX 4060 Ti 16GB
• AMD Radeon Pro W5700X 16GB
  Additional context
  Can someone give me the settings to build OpenMVS or tell me what I'm doing wrong

Thanks

[ElHouas]

Hey @Newbie-omvs ,

I am facing the same problem. Have you been able to find a solution?

Thanks!

[Newbie-omvs]

Hello ElHouas
No i can‘t find a solution. But, when I‘m understanding the infos right, the only part using cuda is RefineMesh. All other modules using cpu. In this case the Question for me: is it nessesary for speeding up only on part or wasting time.

Grettings

[cdcseacave]

in fact the part that benefits most on using the GPU is the densification step
feel free to use the docker image with GPU support if your system does not allow you to build with GPU support