source: CIVL/examples/cuda/dot_orig.cu

/*
 * Copyright 1993-2010 NVIDIA Corporation.  All rights reserved.
 *
 * NVIDIA Corporation and its licensors retain all intellectual property and
 * proprietary rights in and to this software and related documentation.
 * Any use, reproduction, disclosure, or distribution of this software
 * and related documentation without an express license agreement from
 * NVIDIA Corporation is strictly prohibited.
 *
 * Please refer to the applicable NVIDIA end user license agreement (EULA)
 * associated with this source code for terms and conditions that govern
 * your use of this NVIDIA software.
 *
 */


//#include "../common/book.h"

#define imin(a,b) (a<b?a:b)

const int N = 33 * 1024;
const int threadsPerBlock = 256;
const int blocksPerGrid =
            imin(32, (N+threadsPerBlock-1) / threadsPerBlock );

__global__ void dot( float *a, float *b, float *c ) {
    __shared__ float cache[threadsPerBlock];
    int tid = threadIdx.x + blockIdx.x * blockDim.x;
    int cacheIndex = threadIdx.x;
    float   temp = 0;
    
    while (tid < N) {
        temp += a[tid] * b[tid];
        tid += blockDim.x * gridDim.x;
    }
    // set the cache values
    cache[cacheIndex] = temp;
    // synchronize threads in this block
    __syncthreads();
    // for reductions, threadsPerBlock must be a power of 2
    // because of the following code
    int i = blockDim.x/2;
    while (i != 0) {
        if (cacheIndex < i)
            cache[cacheIndex] += cache[cacheIndex + i];
        __syncthreads();
        i /= 2;
    }

    if (cacheIndex == 0)
        c[blockIdx.x] = cache[0];
}


int main( void ) {
    float   *a, *b, c, *partial_c;
    float   *dev_a, *dev_b, *dev_partial_c;

    // allocate memory on the cpu side
    a = (float*)malloc( N*sizeof(float) );
    b = (float*)malloc( N*sizeof(float) );
    partial_c = (float*)malloc( blocksPerGrid*sizeof(float) );

    // allocate the memory on the GPU
    HANDLE_ERROR( cudaMalloc( (void**)&dev_a,
                              N*sizeof(float) ) );
    HANDLE_ERROR( cudaMalloc( (void**)&dev_b,
                              N*sizeof(float) ) );
    HANDLE_ERROR( cudaMalloc( (void**)&dev_partial_c,
                              blocksPerGrid*sizeof(float) ) );

    // fill in the host memory with data
    for (int i=0; i<N; i++) {
        a[i] = i;
        b[i] = i*2;
    }

    // copy the arrays 'a' and 'b' to the GPU
    HANDLE_ERROR( cudaMemcpy( dev_a, a, N*sizeof(float),
                              cudaMemcpyHostToDevice ) );
    HANDLE_ERROR( cudaMemcpy( dev_b, b, N*sizeof(float),
                              cudaMemcpyHostToDevice ) );

    dot<<<blocksPerGrid,threadsPerBlock>>>( dev_a, dev_b,
                                            dev_partial_c );

    // copy the array 'c' back from the GPU to the CPU
    HANDLE_ERROR( cudaMemcpy( partial_c, dev_partial_c,
                              blocksPerGrid*sizeof(float),
                              cudaMemcpyDeviceToHost ) );

    // finish up on the CPU side
    c = 0;
    for (int i=0; i<blocksPerGrid; i++) {
        c += partial_c[i];
    }

    #define sum_squares(x)  (x*(x+1)*(2*x+1)/6)
    printf( "Does GPU value %.6g = %.6g?\n", c,
             2 * sum_squares( (float)(N - 1) ) );

    // free memory on the gpu side
    HANDLE_ERROR( cudaFree( dev_a ) );
    HANDLE_ERROR( cudaFree( dev_b ) );
    HANDLE_ERROR( cudaFree( dev_partial_c ) );

    // free memory on the cpu side
    free( a );
    free( b );
    free( partial_c );
}