| 1 | /*
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| 2 | * Copyright 1993-2010 NVIDIA Corporation. All rights reserved.
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| 3 | *
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| 4 | * NVIDIA Corporation and its licensors retain all intellectual property and
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| 5 | * proprietary rights in and to this software and related documentation.
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| 6 | * Any use, reproduction, disclosure, or distribution of this software
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| 7 | * and related documentation without an express license agreement from
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| 8 | * NVIDIA Corporation is strictly prohibited.
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| 9 | *
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| 10 | * Please refer to the applicable NVIDIA end user license agreement (EULA)
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| 11 | * associated with this source code for terms and conditions that govern
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| 12 | * your use of this NVIDIA software.
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| 13 | *
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| 14 | */
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| 15 |
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| 16 |
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| 17 | //#include "../common/book.h"
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| 18 | #include <stdio.h>
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| 19 | #include <stdlib.h>
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| 20 | #include <cuda.h>
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| 21 |
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| 22 | #define HANDLE_ERROR(x) x
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| 23 |
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| 24 | #define imin(a,b) (a<b?a:b)
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| 25 |
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| 26 | _Bool isPowerOfTwo(int x) {
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| 27 | if (x == 1) {
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| 28 | return $true;
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| 29 | } else {
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| 30 | return x % 2 == 0 && isPowerOfTwo(x / 2);
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| 31 | }
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| 32 | }
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| 33 |
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| 34 |
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| 35 | // the length of the vectors to dot product
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| 36 | $input int LENGTH;
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| 37 | // upper bound on LENGTH
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| 38 | $input int B;
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| 39 | //$assume(0 <= LENGTH && LENGTH <= B);
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| 40 | $assume(0 < LENGTH && LENGTH <= B);
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| 41 | $input int THREADS_PER_BLOCK; // thread number per block: must be a power of 2, due to the while loop at the end of gpuThread();
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| 42 | $input int THREADS_B;
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| 43 | $assume(1 <= THREADS_PER_BLOCK && THREADS_PER_BLOCK <= THREADS_B);
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| 44 |
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| 45 |
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| 46 |
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| 47 | const int N = LENGTH;
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| 48 | const int threadsPerBlock = THREADS_PER_BLOCK;
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| 49 | //const int blocksPerGrid =
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| 50 | // imin(32, (N+threadsPerBlock-1) / threadsPerBlock );
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| 51 | const int blocksPerGrid = (N+threadsPerBlock-1) / threadsPerBlock;
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| 52 |
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| 53 | __global__ void dot( float *a, float *b, float *c ) {
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| 54 | __shared__ float cache[threadsPerBlock];
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| 55 | int tid = threadIdx.x + blockIdx.x * blockDim.x;
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| 56 | int cacheIndex = threadIdx.x;
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| 57 | float temp = 0;
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| 58 |
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| 59 | while (tid < N) {
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| 60 | temp += a[tid] * b[tid];
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| 61 | tid += blockDim.x * gridDim.x;
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| 62 | }
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| 63 | // set the cache values
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| 64 | cache[cacheIndex] = temp;
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| 65 | // synchronize threads in this block
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| 66 | __syncthreads();
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| 67 | // for reductions, threadsPerBlock must be a power of 2
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| 68 | // because of the following code
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| 69 | int i = blockDim.x/2;
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| 70 | while (i != 0) {
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| 71 | if (cacheIndex < i)
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| 72 | cache[cacheIndex] += cache[cacheIndex + i];
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| 73 | __syncthreads();
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| 74 | i /= 2;
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| 75 | }
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| 76 |
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| 77 | if (cacheIndex == 0)
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| 78 | c[blockIdx.x] = cache[0];
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| 79 | }
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| 80 |
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| 81 |
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| 82 | int main( void ) {
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| 83 | elaborate(N);
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| 84 | //_Bool validThreadsPerBlock = isPowerOfTwo(THREADS_PER_BLOCK);
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| 85 | //$assume(validThreadsPerBlock);
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| 86 | //$assume(isPowerOfTwo(THREADS_PER_BLOCK));
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| 87 | float *a, *b, c, *partial_c;
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| 88 | float *dev_a, *dev_b, *dev_partial_c;
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| 89 |
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| 90 | // allocate memory on the cpu side
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| 91 | a = (float*)malloc( N*sizeof(float) );
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| 92 | b = (float*)malloc( N*sizeof(float) );
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| 93 | partial_c = (float*)malloc( blocksPerGrid*sizeof(float) );
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| 94 |
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| 95 | // allocate the memory on the GPU
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| 96 | HANDLE_ERROR( cudaMalloc( (void**)&dev_a,
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| 97 | N*sizeof(float) ) );
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| 98 | HANDLE_ERROR( cudaMalloc( (void**)&dev_b,
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| 99 | N*sizeof(float) ) );
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| 100 | HANDLE_ERROR( cudaMalloc( (void**)&dev_partial_c,
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| 101 | blocksPerGrid*sizeof(float) ) );
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| 102 |
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| 103 | // fill in the host memory with data
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| 104 | for (int i=0; i<N; i++) {
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| 105 | a[i] = i;
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| 106 | b[i] = i*2;
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| 107 | }
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| 108 |
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| 109 | // copy the arrays 'a' and 'b' to the GPU
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| 110 | HANDLE_ERROR( cudaMemcpy( dev_a, a, N*sizeof(float),
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| 111 | cudaMemcpyHostToDevice ) );
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| 112 | HANDLE_ERROR( cudaMemcpy( dev_b, b, N*sizeof(float),
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| 113 | cudaMemcpyHostToDevice ) );
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| 114 |
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| 115 | dot<<<blocksPerGrid,threadsPerBlock>>>( dev_a, dev_b,
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| 116 | dev_partial_c );
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| 117 |
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| 118 | // copy the array 'c' back from the GPU to the CPU
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| 119 | HANDLE_ERROR( cudaMemcpy( partial_c, dev_partial_c,
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| 120 | blocksPerGrid*sizeof(float),
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| 121 | cudaMemcpyDeviceToHost ) );
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| 122 |
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| 123 | // finish up on the CPU side
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| 124 | c = 0;
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| 125 | for (int i=0; i<blocksPerGrid; i++) {
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| 126 | c += partial_c[i];
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| 127 | }
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| 128 |
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| 129 | #define sum_squares(x) (x*(x+1)*(2*x+1)/6)
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| 130 | printf( "Does GPU value %.6g = %.6g?\n", c,
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| 131 | 2 * sum_squares( (float)(N - 1) ) );
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| 132 | $assert(c == 2 * sum_squares( (float)(N - 1) ) );
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| 133 |
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| 134 | // free memory on the gpu side
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| 135 | HANDLE_ERROR( cudaFree( dev_a ) );
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| 136 | HANDLE_ERROR( cudaFree( dev_b ) );
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| 137 | HANDLE_ERROR( cudaFree( dev_partial_c ) );
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| 138 |
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| 139 | // free memory on the cpu side
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| 140 | free( a );
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| 141 | free( b );
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| 142 | free( partial_c );
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| 143 | }
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