CudaSumArray.cu

#include "CudaKernels.cuh"

__global__ void cudaSumArray(DevicePixelType* arrayIn, double* arrayOut, size_t n)
{
	//This algorithm was used from a this website:
	// http://developer.download.nvidia.com/compute/cuda/1.1-Beta/x86_website/projects/reduction/doc/reduction.pdf
	// accessed 4/28/2013

	extern __shared__ double sdata[];

	size_t tid = threadIdx.x;
	size_t i = blockIdx.x*blockDim.x + tid;
	size_t gridSize = blockDim.x*gridDim.x;
	sdata[tid] = (double)(arrayIn[i]);

	do
	{
		if (i+blockDim.x<n)
			sdata[tid] += (double)(arrayIn[i+blockDim.x]);

		i += gridSize;
	}while (i<n);
	__syncthreads();


	if (blockDim.x >= 2048)
	{
		if (tid < 1024) 
			sdata[tid] += sdata[tid + 1024];
		__syncthreads();
	}

	if (blockDim.x >= 1024)
	{
		if (tid < 512) 
			sdata[tid] += sdata[tid + 512];
		__syncthreads();
	}
	
	if (blockDim.x >= 512)
	{
		if (tid < 256) 
			sdata[tid] += sdata[tid + 256];
		__syncthreads();
	}
	
	if (blockDim.x >= 256) {
		if (tid < 128)
			sdata[tid] += sdata[tid + 128];
		__syncthreads(); 
	}
	
	if (blockDim.x >= 128) 
	{
		if (tid < 64)
			sdata[tid] += sdata[tid + 64];
		__syncthreads(); 
	}

	if (tid < 32) {
		if (blockDim.x >= 64) 
		{
			sdata[tid] += sdata[tid + 32];
			__syncthreads(); 
		}
		if (blockDim.x >= 32)
		{
			sdata[tid] += sdata[tid + 16];
			__syncthreads(); 
		}
		if (blockDim.x >= 16)
		{
			sdata[tid] += sdata[tid + 8];
			__syncthreads(); 
		}
		if (blockDim.x >= 8)
		{
			sdata[tid] += sdata[tid + 4];
			__syncthreads(); 
		}
		if (blockDim.x >= 4)
		{
			sdata[tid] += sdata[tid + 2];
			__syncthreads(); 
		}
		if (blockDim.x >= 2)
		{
			sdata[tid] += sdata[tid + 1];
			__syncthreads(); 
		}
	}

	if (tid==0)
		arrayOut[blockIdx.x] = sdata[0];
}