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@ -8,28 +8,66 @@ |
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#include "meanshift_kernels.h" |
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#include "meanshift_kernels.h" |
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#define OUTPUT_PREFIX "../output/output_" |
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#define OUTPUT_PREFIX "../output/output_" |
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#define BLOCK_SIZE 8 |
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int BLOCK_SIZE = 16; |
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void get_args(int argc, char **argv){ |
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cudaDeviceProp device_properties; |
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if (argc != 6) { |
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printf("Usage: %s h N D Pd Pl\nwhere:\n", argv[0]); |
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void get_args(int argc, char **argv, parameters *params){ |
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printf("\th is the variance\n"); |
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if (argc < 7) { |
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printf("\tN is the the number of points\n"); |
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printf("Usage: %s h e N D Pd Pl\nwhere:\n" |
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printf("\tD is the number of dimensions of each point\n"); |
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"\th is the variance\n" |
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printf("\tPd is the path of the dataset file\n"); |
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"\te is the min distance, between two points, that is taken into account in computations\n" |
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printf("\tPl is the path of the labels file\n"); |
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"\tN is the the number of points\n" |
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"\tD is the number of dimensions of each point\n" |
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"\tPd is the path of the dataset file\n" |
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"\tPl is the path of the labels file\n" |
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"\n\t--verbose | -v is an optional flag to enable execution information output" |
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"\n\t--output | -o is an optional flag to enable points output in each iteration", argv[0]); |
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exit(1); |
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exit(1); |
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} |
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} |
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DEVIATION = atoi(argv[1]); |
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DEVIATION = atoi(argv[1]); |
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NUMBER_OF_POINTS = atoi(argv[2]); |
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params->epsilon = atof(argv[2]); |
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DIMENSIONS = atoi(argv[3]); |
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NUMBER_OF_POINTS = atoi(argv[3]); |
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POINTS_FILENAME = argv[4]; |
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DIMENSIONS = atoi(argv[4]); |
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LABELS_FILENAME = argv[5]; |
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POINTS_FILENAME = argv[5]; |
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LABELS_FILENAME = argv[6]; |
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params->verbose = false; |
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params->display = false; |
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if (argc > 7){ |
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for (int index=7; index<argc; ++index){ |
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if (!strcmp(argv[index], "--verbose") || !strcmp(argv[index], "-v")){ |
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params->verbose = true; |
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} else if (!strcmp(argv[index], "--output") || !strcmp(argv[index], "-o")){ |
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params->display = true; |
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} else { |
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printf("Couldn't parse argument %d: %s\n", index, argv[index]); |
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exit(EXIT_FAILURE); |
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} |
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} |
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} |
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} |
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void init(double ***vectors, char **labels, parameters *params){ |
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/*printf("DEVIATION = %d\n" |
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"epsilon = %f\n" |
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"NUMBER_OF_POINTS = %d\n" |
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"DIMENSIONS = %d\n" |
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"POINTS_FILENAME = %s\n" |
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"LABELS_FILENAME = %s\n" |
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"verbose = %d\n" |
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"display = %d\n", DEVIATION, params->epsilon, NUMBER_OF_POINTS, DIMENSIONS, POINTS_FILENAME |
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, LABELS_FILENAME, params->verbose, params->display);*/ |
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} |
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void init(double ***vectors, char **labels){ |
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int bytes_read = 0; |
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int bytes_read = 0; |
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set_Gpu(); |
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if (params.verbose){ |
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printf("Reading dataset and labels...\n"); |
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} |
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// initializes vectors |
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// initializes vectors |
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FILE *points_file; |
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FILE *points_file; |
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points_file = fopen(POINTS_FILENAME, "rb"); |
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points_file = fopen(POINTS_FILENAME, "rb"); |
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@ -83,10 +121,45 @@ void init(double ***vectors, char **labels, parameters *params){ |
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} |
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} |
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fclose(labels_file); |
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fclose(labels_file); |
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// MEAN SHIFT OPTIONS |
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if (params.verbose){ |
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params->epsilon = 0.0001; |
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printf("Done.\n\n"); |
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params->verbose = false; |
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} |
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params->display = false; |
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} |
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//Based on https://stackoverflow.com/a/28113186 |
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//Poio psagmeno link https://www.cs.virginia.edu/~csadmin/wiki/index.php/CUDA_Support/Choosing_a_GPU |
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void set_Gpu(){ |
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int devices_count = 0, max_multiprocessors = 0, max_device = 0; |
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// gets devices count checking for errors like no devices or no drivers to check for |
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// devices available |
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gpuErrchk( cudaGetDeviceCount(&devices_count) ); |
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for(int device_index = 0; device_index < devices_count; ++device_index){ |
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// gets current index device's properties |
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cudaDeviceProp this_device_properties; |
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gpuErrchk( cudaGetDeviceProperties(&this_device_properties, device_index) ); |
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// stores best available device's index |
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// only devices with compute capability >= 2.0 are able to run the code |
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if (max_multiprocessors < this_device_properties.multiProcessorCount |
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&& this_device_properties.major >= 2 && this_device_properties.minor >= 0){ |
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// stores devices properties for later use |
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device_properties = this_device_properties; |
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max_multiprocessors = this_device_properties.multiProcessorCount; |
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max_device = device_index; |
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} |
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} |
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// sets the device |
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gpuErrchk( cudaSetDevice(max_device) ); |
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BLOCK_SIZE = device_properties.maxThreadsPerBlock; |
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if (params.verbose){ |
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printf("Device chosen is \"%s\"\n" |
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"Device has %d multi processors and compute capability %d.%d\n" |
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"Setting BLOCK_SIZE to max threads per block supported (%d)\n\n" |
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, device_properties.name |
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, device_properties.multiProcessorCount, device_properties.major, device_properties.minor |
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, BLOCK_SIZE); |
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} |
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} |
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} |
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int meanshift(double **original_points, double ***shifted_points, int deviation |
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int meanshift(double **original_points, double ***shifted_points, int deviation |
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@ -157,11 +230,15 @@ int meanshift(double **original_points, double ***shifted_points, int deviation |
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// updates shifted points pointer to the new array address |
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// updates shifted points pointer to the new array address |
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shifted_points = &new_shift; |
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shifted_points = &new_shift; |
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if (params.display){ |
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save_matrix((*shifted_points), iteration); |
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save_matrix((*shifted_points), iteration); |
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} |
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// calculates norm of the new mean shift vector |
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// calculates norm of the new mean shift vector |
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double current_norm = norm(mean_shift_vector, NUMBER_OF_POINTS, DIMENSIONS); |
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double current_norm = norm(mean_shift_vector, NUMBER_OF_POINTS, DIMENSIONS); |
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if (params.verbose){ |
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printf("Iteration n. %d, error %f \n", iteration, current_norm); |
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printf("Iteration n. %d, error %f \n", iteration, current_norm); |
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} |
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/** iterates until convergence **/ |
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/** iterates until convergence **/ |
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if (current_norm > opt->epsilon) { |
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if (current_norm > opt->epsilon) { |
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@ -170,7 +247,7 @@ int meanshift(double **original_points, double ***shifted_points, int deviation |
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} |
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} |
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if (iteration == 0){ |
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if (iteration == 0){ |
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// cleans up this iteration's allocations |
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// cleans up allocations |
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free(mean_shift_vector[0]); |
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free(mean_shift_vector[0]); |
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free(mean_shift_vector); |
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free(mean_shift_vector); |
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free(kernel_matrix[0]); |
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free(kernel_matrix[0]); |
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@ -195,6 +272,8 @@ double norm(double **matrix, int rows, int cols){ |
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} |
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} |
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void multiply(double **kernel_matrix, double **original_points, double ***new_shift){ |
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void multiply(double **kernel_matrix, double **original_points, double ***new_shift){ |
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static bool firstIter = true; |
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// allocates memory for kernel_matrix in GPU and copies the array |
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// allocates memory for kernel_matrix in GPU and copies the array |
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Matrix d_kernel_matrix; |
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Matrix d_kernel_matrix; |
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d_kernel_matrix.width = NUMBER_OF_POINTS; |
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d_kernel_matrix.width = NUMBER_OF_POINTS; |
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@ -220,11 +299,16 @@ void multiply(double **kernel_matrix, double **original_points, double ***new_sh |
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size = NUMBER_OF_POINTS * DIMENSIONS * sizeof(double); |
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size = NUMBER_OF_POINTS * DIMENSIONS * sizeof(double); |
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gpuErrchk( cudaMalloc(&d_new_shift.elements, size) ); |
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gpuErrchk( cudaMalloc(&d_new_shift.elements, size) ); |
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//dim3 dimBlock(16, 16); |
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dim3 dimBlock((d_new_shift.height < sqrt(BLOCK_SIZE)) ? d_new_shift.height : sqrt(BLOCK_SIZE) |
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//dim3 dimGrid(d_original_points.width / dimBlock.x, d_kernel_matrix.height / dimBlock.y); |
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, (d_new_shift.width < sqrt(BLOCK_SIZE)) ? d_new_shift.width : sqrt(BLOCK_SIZE)); |
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dim3 dimGrid((d_new_shift.height + dimBlock.x - 1) / dimBlock.x |
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, (d_new_shift.width + dimBlock.y - 1) / dimBlock.y); |
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dim3 dimBlock(10, 2); |
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if (firstIter && params.verbose){ |
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dim3 dimGrid(60, 1); |
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printf("dimBlock.x = %d, dimBlock.y = %d\n", dimBlock.x, dimBlock.y); |
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printf("dimGrid.x = %d, dimGrid.y = %d\n\n", dimGrid.x, dimGrid.y); |
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firstIter = false; |
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} |
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multiply_kernel<<<dimGrid, dimBlock>>>(d_kernel_matrix, d_original_points, d_new_shift); |
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multiply_kernel<<<dimGrid, dimBlock>>>(d_kernel_matrix, d_original_points, d_new_shift); |
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gpuErrchk( cudaPeekAtLastError() ); |
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gpuErrchk( cudaPeekAtLastError() ); |
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