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Getting CUDA error “declaration is incompatible wi

2019-09-20 11:54发布

问题:

I'm trying to compile a program including a kernel with MSVS 2012 and CUDA. I use shared memory, but unlike in this question regarding the same problem, I only use my variable name for this kernel's shared memory once, so there's no issue of redefinition. With code like this:

template<typename T>
__global__ void mykernel(
    const T* __restrict__ data,
    T*       __restrict__ results) 
{
    extern __shared__ T warp_partial_results[];
    /* ... */
    warp_partial_results[lane_id] = something;
    /* ... */
    results[something_else] = warp_partial_results[something_else];
    /* ... */
}

which is instantiated for several types (e.g. float, int, unsigned int), I get the dreaded

declaration is incompatible with previous "warp_partial_results"

message. What could cause this?

回答1:

CUDA doesn't immediately 'support' dynamically-allocated shared memory arrays in templated functions, as it (apparently) generates actual definitions of those extern's. If you instantiate a templated function for multiple types, the definitions would conflict.

A workaround is available in the form of template specialization via classes. See:

http://www.ecse.rpi.edu/~wrf/wiki/ParallelComputingSpring2015/cuda/nvidia/samples/0_Simple/simpleTemplates/sharedmem.cuh

You use the workaround as follows:

template<class T> __global__ void foo( T* g_idata, T* g_odata)
{
    // shared memory
    // the size is determined by the host application

    SharedMem<T> shared;
    T* sdata = shared.getPointer();

    // .. the rest of the code remains unchanged!
}

the getPointer() has* a specialized implementation for every type, which returns a different pointer, e.g. extern __shared__ float* shared_mem_float or extern __shared__ int* shared_mem_int etc.

(*) - Not really. in NVidia's supplied header file they specialize for some basic types and that's that.