Question

I am trying to integrate CUDA and openCV in a project. Problem is openCV won t compile when NVCC is used, while a normal c++ project compiles just fine. This seems odd to me, as I thought NVCC passed all host code to the c/c++ compiler, in this case the visual studio compiler.

The errors I get are?

c:opencv2.0includeopencvcxoperations.hpp(1137): error: no operator "=" matches these operands operand types are: const cv::Range = cv::Range

c:opencv2.0includeopencvcxoperations.hpp(2469): error: more than one instance of overloaded function "std::abs" matches the argument list: function "abs(long double)" function "abs(float)" function "abs(double)" function "abs(long)" function "abs(int)" argument types are: (ptrdiff_t)

So my question is why the difference considering the same compiler (should be) is being used and secondly how I could remedy this.

Answer 1

In general I would recommend keeping separation between host code and CUDA code, only using nvcc for the kernels and host "wrappers". This is particularly easy with Visual Studio, create your project as normal (e.g. a Console application) and then implement your application in .cpp files. When you want to run a CUDA function, create the kernel and a wrapper in one or more .cu files. The Cuda.rules file provided with the SDK will automatically enable VS to compile the .cu files and link the result with the rest of the .cpp files.

Answer 2

NVCC passes C++ code through to the host compiler, but it has to first parse and understand the code. Unfortunately, NVCC has troubles with STL. If at all possible, separate code that makes use of STL into .cpp files and have those compiled with Visual Studio (without passing them first through NVCC).

Answer 3

Compile the .cu code as a library and then link it to the main program. I suggest to use cmake as it makes the process a breeze

Answer 4

There s a project hosted at cuda-grayscale that shows how to integrate OpenCV + CUDA together. If you download the sources check the Makefile:

g++ $(CFLAGS) -c main.cpp -o Debug/main.o
nvcc $(CUDAFLAGS) -c kernel_gpu.cu -o Debug/kernel_gpu.o
g++ $(LDFLAGS) Debug/main.o Debug/kernel_gpu.o -o Debug/grayscale

It s a very simple project that demonstrates how to separate regular C++ code (OpenCV and stuff) from the CUDA code and compile them.

Answer 5

So there s no easy way to use nvcc to compile your current C++ code, you have to write wrappers and compile them using nvcc, while you compile the rest of your code using g++ or what-have-you?

友情链接