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| -rw-r--r-- | llvm/docs/CompileCudaWithLLVM.rst | 28 |
1 files changed, 28 insertions, 0 deletions
diff --git a/llvm/docs/CompileCudaWithLLVM.rst b/llvm/docs/CompileCudaWithLLVM.rst index 159e0c0e5b3..bb1ce041e51 100644 --- a/llvm/docs/CompileCudaWithLLVM.rst +++ b/llvm/docs/CompileCudaWithLLVM.rst @@ -119,6 +119,34 @@ your GPU <https://developer.nvidia.com/cuda-gpus>`_. For example, if you want to run your program on a GPU with compute capability of 3.5, you should specify ``--cuda-gpu-arch=sm_35``. +Detecting clang vs NVCC +======================= + +Although clang's CUDA implementation is largely compatible with NVCC's, you may +still want to detect when you're compiling CUDA code specifically with clang. + +This is tricky, because clang defines the ``__NVCC__`` macro, and because NVCC +may invoke clang as part of its own compilation process! For example, NVCC +uses the host compiler's preprocessor when compiling for device code, and that +host compiler may in fact be clang. + +When clang is actually compiling CUDA code -- rather than being used as a +subtool of NVCC's -- it defines the ``__CUDA__`` macro. ``__CUDA_ARCH__`` is +defined only in device mode (but will be defined if NVCC is using clang as a +preprocessor). So you can use the following incantations to detect clang CUDA +compilation, in host and device modes: + +.. code-block:: c++ + + #if defined(__clang__) && defined(__CUDA__) && !defined(__CUDA_ARCH__) + // clang compiling CUDA code, host mode. + #endif + + #if defined(__clang__) && defined(__CUDA__) && defined(__CUDA_ARCH__) + // clang compiling CUDA code, device mode. + #endif + + Optimizations ============= |
