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Sample Code Segment (pg. 41 & 42)

Sample Code Segment (pg. 41 & 42). 1. #include "../common/book.h" 2. #define N 10 3. int main( void ) { 4. int a[N], b[N], c[N]; 5. int *dev_a, *dev_b, *dev_c; 6. // allocate the memory on the GPU 7. HANDLE_ERROR( cudaMalloc( (void**)&dev_a, N * sizeof(int) ) );

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Sample Code Segment (pg. 41 & 42)

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  1. Sample Code Segment (pg. 41 & 42) • 1. #include "../common/book.h" • 2. #define N 10 • 3. int main( void ) { • 4. int a[N], b[N], c[N]; • 5. int *dev_a, *dev_b, *dev_c; • 6. // allocate the memory on the GPU • 7. HANDLE_ERROR( cudaMalloc( (void**)&dev_a, N * sizeof(int) ) ); • 8. HANDLE_ERROR( cudaMalloc( (void**)&dev_b, N * sizeof(int) ) ); • 9. HANDLE_ERROR( cudaMalloc( (void**)&dev_c, N * sizeof(int) ) ); • // fill the arrays 'a' and 'b' on the CPU • 10. for (int i=0; i<N; i++) { • 11. a[i] = -i; • 12. b[i] = i * i; • 13.} • // copy the arrays 'a' and 'b' to the GPU • 14. HANDLE_ERROR( cudaMemcpy( dev_a, a, N * sizeof(int), cudaMemcpyHostToDevice ) ); • 15. HANDLE_ERROR( cudaMemcpy( dev_b, b, N * sizeof(int), cudaMemcpyHostToDevice ) ); • 16. add<<<N,1>>>( dev_a, dev_b, dev_c ); • // copy the array 'c' back from the GPU to the CPU • 17. HANDLE_ERROR( cudaMemcpy( c, dev_c, N * sizeof(int), • cudaMemcpyDeviceToHost ) ); • // display the results • 18. for (int i=0; i<N; i++) { • 19. printf( "%d + %d = %d\n", a[i], b[i], c[i] ); } • // free the memory allocated on the GPU • 20. cudaFree( dev_a ); • 21.cudaFree( dev_b ); • 22. cudaFree( dev_c ); • 23. return 0; • }

  2. Sample Code Illustration – time t1 3. Int main (void) { 4. int a[N], b[N], c[N]; 5. int *dev_a, *dev_b, *dev_c; 2. define N 10 B C A Idle *dev_a *dev_c *dev_b

  3. Sample Code Illustration – time t1 7. HANDLE_ERROR( cudaMalloc( (void**)&dev_a, N * sizeof(int) ) ); 8. HANDLE_ERROR( cudaMalloc( (void**)&dev_b, N * sizeof(int) ) ); 9. HANDLE_ERROR( cudaMalloc( (void**)&dev_c, N * sizeof(int) ) ); &dev_c &dev_a Idle &dev_b

  4. Sample Code Illustration – time t2 • 14. HANDLE_ERROR( cudaMemcpy( dev_a, a, N * sizeof(int), cudaMemcpyHostToDevice ) ); • 15. HANDLE_ERROR( cudaMemcpy( dev_b, b, N * sizeof(int), cudaMemcpyHostToDevice ) ); 10. for (int i=0; i<N; i++) { 11. a[i] = -i; 12. b[i] = i * i; &dev_a i = 0 i = 1 i = 2 i = 3 i = N a[0] 0 a[1] -1 a[2] -2 a[3] -3 a[n] 9 … a[2] -2 a[1] -1 a[0] 0 b[0] 0 * 0 b[1] 1 * 1 b[2] 2* 2 b[3] 3* 3 b[n] 9 * 9 … … a[3] -3 a[9] -9 &dev_b c[0] c[1] c[2] c[3] c[9] … Array c, currently unused b[1] 1 * 1 b[0] 0 * 0 b[2] 2 * 2 … b[3] 3 * 3 b[9] 9 * 9

  5. Sample Code Illustration – time t3 16. add<<<N,1>>>( dev_a, dev_b, dev_c ); &dev_a &dev_b &dev_a elements, added to &dev_b elements by each thread … … a[2] -2 a[1] -1 a[0] 0 a[3] -3 a[9] -9 -9+81 -1+1 -3+9 -2+4 0 + 0 … Idle a[9] + b[9] a[3] + b[3] a[0] + b[0] a[1] + b[1] a[2] + b[2] 10 total threads, one thread per operation &dev_c b[1] 1 * 1 b[0] 0 * 0 b[2] 2 * 2 c[2] 2 c[1] 0 c[0] 0 c[3] 6 c[9] 72 b[3] 3 * 3 b[9] 9 * 9 …

  6. Sample Code Illustration – time t4 17. HANDLE_ERROR( cudaMemcpy( c, dev_c, N * sizeof(int), cudaMemcpyDeviceToHost ) ); dev_c c[0] c[1] c[2] c[3] c[9] … … c[0] 0 c[2] 2 c[1] 0 c[3] 6 c[9] 72

  7. o Sample Code Illustration – time t5 18. for (inti=0; i<N; i++) { 19. printf( "%d + %d = %d\n", a[i], b[i], c[i] ); } For i, being 0 through 9, since it is n large, which is 10. a[i] Added with b[i] Equals c[i] a[0] 0 a[1] -1 a[2] -2 a[3] -3 a[n] -9 … a[n] a[3] a[2] a[1] a[0] b[1] 1 b[2] 4 b[3] 9 b[n] 81 b[0] 0 … b[n] b[3] b[2] b[1] b[0] c[3] 6 a[n] 72 c[1] 0 c[2] 2 c[0] 0 … c[n] c[3] c[2] c[1] c[0]

  8. Sample Code Illustration – time t6 20. cudaFree( dev_a ); 21. cudaFree( dev_b ); 22. cudaFree( dev_c ); dev_b dev_a dev_c 23. return 0;

  9. Diagram Key &dev_c &dev_a CPUGPU Triangle: Represents Array Transparent Oval: Empty Pointer Oval: Represents Pointer Solid Oval: Referenced Pointer Oval [red square]: Individual Array Elements Inverted Triangle: Filled Array Circle [red square]: Pointer Element Size in Bytes Triangle [red square]: Pointer Element Size in Bytes Red Square: One Block Color and Shading Transparent: Empty Blue Tint: Array Color Solid Color: Full Yellow: Dynamic Memory Allocation Parallel Arrays: Identical Colors Dashed Black Border: Pointer ---------------------------------------------------------------------------------------------------------------------------------------------- Red Arrows: Directionality of Memory Transfer Between CPU and GPU, or GPU and CPU Squiggle Arrow: Single Thread … a[2] -2 a[1] -1 a[0] 0 A a[3] -3 a[9] -9 -9+81

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