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To enclose a CUDA kernel function within a template, you can use the template keyword before the function name, followed by the template parameter list within angle brackets <>.

Here's an example:

template<typename T>
__global__ void addKernel(T a, T b, T *c)
{
    int i = threadIdx.x;
    c[i] = a[i] + b[i];
}

In this example, the template parameter typename T specifies the data type of the input arrays a and b, as well as the output array c. The kernel function computes the element-wise sum of a and b, and stores the result in c.

To call this kernel function in your code, you would need to specify the data type parameter T explicitly, like so:

int main()
{
    // Define input arrays
    float a[N], b[N];
    // Define output array
    float *c;
    cudaMalloc(&c, N * sizeof(float));

    // Call kernel function
    addKernel<float><<<1,N>>>(a, b, c);

    // Check for errors and clean up resources
    cudaFree(c);
    return 0;
}

In this example, we pass the data type parameter float to the addKernel template function, since we're using floating-point arrays a, b, and c. You would need to instantiate the template function separately for each data type you want to use.