Ah, sorry, I misread your question. I think the difference might be that CUDA 11 will support more GPU architectures; there are corresponding kernels for the newer architectures with the newer CUDA version e.g.,
  
    
    
    [NEED HELP] Trouble with CUDA capability sm_86 
  
  
    NIT: TORCH_CUDA_ARCH_LIST will be used while building from source and won’t change the shipped compute capabilities in the binaries, which you can get via print(torch.cuda.get_arch_list()). 

That’s expected, since Ampere GPUs need CUDA>=11.0 

No, the 3070 uses sm_86, which is natively supported in CUDA>=11.1 and is binary compatible to sm_80, so would already work in CUDA=11.0. 
In any case, good to hear it’s working now 
  


As far as the file split, I think that might be just an artifact of a tweak to the build process, but I’m not very knowledgeable on the details here.
  

      github.com
  

  
    pytorch/pytorch/blob/9ae3f3945b519c04ef0aa4f9e441be6401292f86/CMakeLists.txt#L181 1



      
      
          option(BUILD_JNI "Build JNI bindings" OFF)
          option(BUILD_MOBILE_AUTOGRAD "Build autograd function in mobile build (in development)" OFF)
          cmake_dependent_option(
              INSTALL_TEST "Install test binaries if BUILD_TEST is on" ON
              "BUILD_TEST" OFF)
          option(USE_CPP_CODE_COVERAGE "Compile C/C++ with code coverage flags" OFF)
          option(COLORIZE_OUTPUT "Colorize output during compilation" ON)
          option(USE_ASAN "Use Address Sanitizer" OFF)
          option(USE_TSAN "Use Thread Sanitizer" OFF)
          option(USE_CUDA "Use CUDA" ON)
          # BUILD_SPLIT_CUDA must also be exported as an environment variable before building, with
          # `export BUILD_SPLIT_CUDA=1` because cpp_extension.py can only work properly if this variable
          # also exists in the environment.
          # This option is incompatible with CUDA_SEPARABLE_COMPILATION.
          cmake_dependent_option(
              BUILD_SPLIT_CUDA "Split torch_cuda library into torch_cuda_cu and torch_cuda_cpp" OFF
              "USE_CUDA AND NOT CUDA_SEPARABLE_COMPILATION" OFF)
          option(USE_FAST_NVCC "Use parallel NVCC build" OFF)
          option(USE_ROCM "Use ROCm" ON)
          option(CAFFE2_STATIC_LINK_CUDA "Statically link CUDA libraries" OFF)
          cmake_dependent_option(