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.
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Asked: 2023-05-06 06:16:05 +0000
Seen: 13 times
Last updated: May 06 '23
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