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Add kernels header and implementation, fix Makefile

master
Apostolos Fanakis 7 years ago
parent
commit
3891fa60aa
  1. 16
      mean_shift_cuda/Makefile
  2. 270
      mean_shift_cuda/meanshift.c
  3. 39
      mean_shift_cuda/meanshift.cu
  4. 66
      mean_shift_cuda/meanshift_declarations.c
  5. 19
      mean_shift_cuda/meanshift_kernels.cu
  6. 13
      mean_shift_cuda/meanshift_kernels.h
  7. 282
      mean_shift_cuda/meanshift_utils.cu
  8. 22
      mean_shift_cuda/meanshift_utils.h

16
mean_shift_cuda/Makefile

@ -3,11 +3,11 @@ SHELL := /bin/bash
# ============================================
# COMMANDS
CC = /usr/local/cuda/bin/nvcc -ccbin gcc
CC = /usr/local/cuda/bin/nvcc
RM = rm -f
CFLAGS=-lm -O3 -I.
OBJ=meanshift.o meanshift_declarations.o
DEPS=meanshift_declarations.h
CFLAGS= -arch=sm_21 -lm -O0 -I.
OBJ=meanshift.o meanshift_utils.o meanshift_kernels.o
DEPS=meanshift_utils.h meanshift_kernels.h
# ==========================================
# TARGETS
@ -21,8 +21,8 @@ all: $(EXECUTABLES)
# ==========================================
# DEPENDENCIES (HEADERS)
%.o: %.c $(DEPS)
$(CC) -c -o $@ $< $(CFLAGS)
%.o: %.cu $(DEPS)
$(CC) -x cu $(CFLAGS) -dc $< -o $@
.PRECIOUS: $(EXECUTABLES) $(OBJ)
@ -30,7 +30,7 @@ all: $(EXECUTABLES)
# EXECUTABLE (MAIN)
$(EXECUTABLES): $(OBJ)
$(CC) -o $@ $^ $(CFLAGS)
$(CC) $(CFLAGS) $(OBJ) -o $@
clean:
$(RM) *.o *~ $(EXECUTABLES)
$(RM) *.o *~ $(EXECUTABLES)

270
mean_shift_cuda/meanshift.c

@ -1,270 +0,0 @@
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#include <math.h>
#include <float.h>
#include <cuda_runtime.h>
#include "meanshift_declarations.h"
#define N 512
int NUMBER_OF_POINTS = 600;
int DIMENSIONS = 2;
char* POINTS_FILENAME = "../data/X.bin";
char* LABELS_FILENAME = "../data/L.bin";
struct timeval startwtime, endwtime;
double seq_time;
__device__ double norm(double **matrix, int rows, int cols){
double sum=0, temp_mul=0;
for (int i=0; i<rows; i++) {
for (int j=0; j<cols; j++) {
temp_mul = matrix[i][j] * matrix[i][j];
sum = sum + temp_mul;
}
}
double norm = sqrt(sum);
return norm;
}
int main(int argc, char **argv){
int h = 1;
//get_args(argc, argv, &h); commented out while in development
FILE *f;
// f = fopen(X, "rb");
// fseek(f, 0L, SEEK_END);
// long int pos = ftell(f);
// fclose(f);
// int elements = pos / sizeof(double); // number of total elements (points*dimension)
// int points = elements/DIMENSIONS;
// //printf("points : %d \n", points);
f = fopen(POINTS_FILENAME, "rb");
double **vectors;
vectors = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
for (int i=0; i<NUMBER_OF_POINTS; i++){
int out = fread(vectors[i], sizeof(double), DIMENSIONS, f);
}
save_matrix(vectors, 0);
// initializing file that will contain the labels (train)
f = fopen(LABELS_FILENAME, "rb");
// NOTE : Labels were classified as <class 'numpy.uint8'>
// variables of type uint8 are stored as 1-byte (8-bit) unsigned integers
fseek(f, 0L, SEEK_END);
long int pos = ftell(f);
rewind(f);
//printf("position : %ld \n", pos);
int label_elements = pos/ sizeof(char);
char *labels = (char*)malloc(label_elements* sizeof(char));
fseek(f, 0L, SEEK_SET);
int out = fread(labels, sizeof(char), label_elements, f);
fclose(f);
// MEAN SHIFT OPTIONS
parameters params;
params.epsilon = 0.0001;
params.verbose = false;
params.display = false;
parameters *opt;
opt = &params;
double **shifted_points;
// tic
gettimeofday (&startwtime, NULL);
int iterations = meanshift(vectors, &shifted_points, h, opt, 1);
// toc
gettimeofday (&endwtime, NULL);
seq_time = (double)((endwtime.tv_usec - startwtime.tv_usec)/1.0e6 + endwtime.tv_sec - startwtime.tv_sec);
printf("%s wall clock time = %f\n","Mean Shift", seq_time);
//TODO write output points to file -> plot later
//save_matrix(shifted_points, iterations);
}
int meanshift(double **original_points, double ***shifted_points, int h
, parameters *opt, int iteration){
// allocates space and copies original points on first iteration
if (iteration == 1){
(*shifted_points) = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
duplicate(original_points, NUMBER_OF_POINTS, DIMENSIONS, shifted_points);
}
// mean shift vector
double **mean_shift_vector;
mean_shift_vector = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
// initialize elements of mean_shift_vector to inf
for (int i=0;i<NUMBER_OF_POINTS;i++){
for (int j=0;j<DIMENSIONS;j++){
mean_shift_vector[i][j] = DBL_MAX;
}
}
/** allocate memory **/
double **kernel_matrix = alloc_2d_double(NUMBER_OF_POINTS, NUMBER_OF_POINTS);
double *denominator = malloc(NUMBER_OF_POINTS * sizeof(double));
// create new y vector
double **new_shift = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
double * d_kernel_matrix;
size_t pitch_kernel_matrix;
cudaMallocPitch(&d_kernel_matrix, &pitch_kernel_matrix,
NUMBER_OF_POINTS * sizeof(double), NUMBER_OF_POINTS);
double * d_denominator;
cudaMalloc(&d_denominator, NUMBER_OF_POINTS * sizeof(double));
double * d_new_shift;
size_t pitch_new_shift;
cudaMallocPitch(&d_new_shift, &pitch_new_shift,
NUMBER_OF_POINTS * sizeof(double), DIMENSIONS);
double * d_shifted_points;
size_t pitch_shifted_points;
cudaMallocPitch(&d_shifted_points, &pitch_shifted_points,
NUMBER_OF_POINTS * sizeof(double), DIMENSIONS);
double * d_mean_shift_vector;
size_t pitch_mean_shift_vector;
cudaMallocPitch(&d_mean_shift_vector, &pitch_mean_shift_vector,
NUMBER_OF_POINTS * sizeof(double), DIMENSIONS);
cudaMemcpy2D(d_shifted_points, NUMBER_OF_POINTS * sizeof(double), *shifted_points,
pitch_shifted_points, NUMBER_OF_POINTS * sizeof(double),
DIMENSIONS, cudaMemcpyHostToDevice);
cudaMemcpy2D(d_mean_shift_vector, NUMBER_OF_POINTS * sizeof(double), *mean_shift_vector,
pitch_mean_shift_vector, NUMBER_OF_POINTS * sizeof(double),
DIMENSIONS, cudaMemcpyHostToDevice);
// TODO REFACTOR AS A KERNEL
for (int i=0; i<NUMBER_OF_POINTS; i++){
double sum = 0;
for (int j=0; j<NUMBER_OF_POINTS; j++){
double dist_sum = 0;
for (int p=0; p<DIMENSIONS; p++){
double dif = ((*shifted_points)[i])[p]-(original_points[j])[p];
dist_sum += dif * dif;
}
double dist = sqrt(dist_sum);
if (dist < h*h){
kernel_matrix[i][j] = dist * dist;
// compute kernel matrix
double pow = ((-1)*(kernel_matrix[i][j]))/(2*(h*h));
kernel_matrix[i][j] = exp(pow);
} else {
kernel_matrix[i][j] = 0;
}
if (i==j){
kernel_matrix[i][j] += 1;
}
sum = sum + kernel_matrix[i][j];
}
denominator[i] = sum;
// build nominator
for (int j=0; j<DIMENSIONS; j++){
new_shift[i][j] = 0;
for (int k=0; k<NUMBER_OF_POINTS; k++){
new_shift[i][j] += kernel_matrix[i][k] * original_points[k][j];
}
// divide element-wise
new_shift[i][j] = new_shift[i][j] / denominator[i];
// calculate mean-shift vector at the same time
mean_shift_vector[i][j] = new_shift[i][j] - (*shifted_points)[i][j];
}
}
// frees previously shifted points, they're now garbage
free((*shifted_points)[0]);
// updates shifted points pointer to the new array address
shifted_points = &new_shift;
save_matrix((*shifted_points), iteration);
double current_norm = norm(mean_shift_vector, NUMBER_OF_POINTS, DIMENSIONS);
printf("Iteration n. %d, error %f \n", iteration, current_norm);
// clean up this iteration's allocates
free(mean_shift_vector[0]);
free(mean_shift_vector);
free(kernel_matrix[0]);
free(kernel_matrix);
free(denominator);
/** iterate until convergence **/
if (current_norm > opt->epsilon) {
return meanshift(original_points, shifted_points, h, opt, ++iteration);
}
return iteration;
}
/**
__global__ int iteration(double * kernel_matrix, double * denominator,
double * new_shift, double *shifted_points, double mean_shift_vector,
int NUMBER_OF_POINTS, int DIMENSIONS, int h){
int i = threadIdx.x + blockIdx.x * blockDim.x;
for (i = 0; i < NUMBER_OF_POINTS; i++) {
double sum = 0;
for (int j = 0; j < NUMBER_OF_POINTS; j++) {
double dist_sum = 0;
for (int p = 0; p < DIMENSIONS; p++) {
double dif = ((*shifted_points)[i])[p] - (original_points[j])[p];
dist_sum += dif * dif;
}
double dist = sqrt(dist_sum);
if (dist < h * h) {
kernel_matrix[i][j] = dist * dist;
// compute kernel matrix
double pow = ((-1) * (kernel_matrix[i][j])) / (2 * (h * h));
kernel_matrix[i][j] = exp(pow);
} else {
kernel_matrix[i][j] = 0;
}
if (i == j) {
kernel_matrix[i][j] += 1;
}
sum = sum + kernel_matrix[i][j];
}
denominator[i] = sum;
// build nominator
for (int j = 0; j < DIMENSIONS; j++) {
new_shift[i][j] = 0;
for (int k = 0; k < NUMBER_OF_POINTS; k++) {
new_shift[i][j] += kernel_matrix[i][k] * original_points[k][j];
}
// divide element-wise
new_shift[i][j] = new_shift[i][j] / denominator[i];
// calculate mean-shift vector at the same time
mean_shift_vector[i][j] = new_shift[i][j] - (*shifted_points)[i][j];
}
}
// frees previously shifted points, they're now garbage
free((*shifted_points)[0]);
// updates shifted points pointer to the new array address
shifted_points = &new_shift;
}
*/

39
mean_shift_cuda/meanshift.cu

@ -0,0 +1,39 @@
#include <stdio.h>
#include <stdlib.h>
#include <sys/time.h>
#include "meanshift_utils.h"
int DEVIATION = 1;
int NUMBER_OF_POINTS = 600;
int DIMENSIONS = 2;
char* POINTS_FILENAME = "../data/X.bin";
char* LABELS_FILENAME = "../data/L.bin";
struct timeval startwtime, endwtime;
double seq_time;
int main(int argc, char **argv){
double **vectors, **shifted_points;
char *labels;
parameters params;
//get_args(argc, argv); commented out while in development
init(&vectors, &labels, &params);
//save_matrix(vectors, 0);
// tic
gettimeofday (&startwtime, NULL);
int iterations = meanshift(vectors, &shifted_points, DEVIATION, &params);
printf("Total iterations = %d\n", iterations);
// toc
gettimeofday (&endwtime, NULL);
seq_time = (double)((endwtime.tv_usec - startwtime.tv_usec)/1.0e6 + endwtime.tv_sec - startwtime.tv_sec);
printf("%s wall clock time = %f\n","Mean Shift", seq_time);
//TODO write output points to file -> plot later
//save_matrix(shifted_points, iterations);
}

66
mean_shift_cuda/meanshift_declarations.c

@ -1,66 +0,0 @@
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include <string.h>
#include "meanshift_declarations.h"
void get_args(int argc, char **argv, int *h){
if (argc != 6) {
printf("Usage: %s h N D Pd Pl\nwhere:\n", argv[0]);
printf("\th is the variance\n");
printf("\tN is the the number of points\n");
printf("\tD is the number of dimensions of each point\n");
printf("\tPd is the path of the dataset file\n");
printf("\tPl is the path of the labels file\n");
exit(1);
}
*h = atoi(argv[1]);
NUMBER_OF_POINTS = atoi(argv[2]);
DIMENSIONS = atoi(argv[3]);
POINTS_FILENAME = argv[4];
LABELS_FILENAME = argv[5];
}
double **alloc_2d_double(int rows, int cols) {
double *data = (double *) malloc(rows*cols*sizeof(double));
double **array = (double **) malloc(rows*sizeof(double*));
for (int i=0; i<rows; i++)
array[i] = &(data[cols*i]);
return array;
}
void duplicate(double **source, int rows, int cols, double ***dest){
for (int i=0; i<rows; i++){
for (int j=0; j<cols; j++){
(*dest)[i][j] = source[i][j];
}
}
}
void print_matrix(double **array, int rows, int cols){
for (int i=0; i<cols; i++){
for (int j=0; j<rows; j++){
printf("%f ", array[j][i]);
}
printf("\n");
}
}
void save_matrix(double **matrix, int iteration){
char filename[50];
snprintf(filename, sizeof(filename), "%s%d", "../output/output_", iteration);
FILE *file;
file = fopen(filename, "w");
for (int rows=0; rows<NUMBER_OF_POINTS; ++rows){
for (int cols=0; cols<DIMENSIONS; ++cols){
fprintf(file, "%f", matrix[rows][cols]);
if (cols != DIMENSIONS - 1){
fprintf(file, ",");
}
}
fprintf(file, "\n");
}
}

19
mean_shift_cuda/meanshift_kernels.cu

@ -0,0 +1,19 @@
#include "meanshift_kernels.h"
#include <stdio.h>
__global__ void multiply_kernel(Matrix matrix1, Matrix matrix2, Matrix output){
// Each thread computes one element of output
// by accumulating results into cell_value
double cell_value = 0;
int row = blockIdx.y * blockDim.y + threadIdx.y;
int col = blockIdx.x * blockDim.x + threadIdx.x;
if (row < output.height && col < output.width){
for (int element_index = 0; element_index < matrix1.width; ++element_index){
cell_value += matrix1.elements[row * matrix1.width + element_index]
* matrix2.elements[element_index * matrix2.width + col];
}
printf("%f\n", cell_value);
output.elements[row * output.width + col] = cell_value;
}
}

13
mean_shift_cuda/meanshift_kernels.h

@ -0,0 +1,13 @@
#ifndef SERIAL_KERNELS_H /* Include guard */
#define SERIAL_KERNELS_H
typedef struct{
int width;
int height;
double *elements;
} Matrix;
//Function multiply_kernel calculates the product of matrices 1 and 2 into output.
__global__ void multiply_kernel(Matrix matrix1, Matrix matrix2, Matrix output);
#endif //SERIAL_KERNELS_H

282
mean_shift_cuda/meanshift_utils.cu

@ -0,0 +1,282 @@
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include <string.h>
#include "meanshift_utils.h"
#include "meanshift_kernels.h"
#define OUTPUT_PREFIX "../output/output_"
#define BLOCK_SIZE 16
void get_args(int argc, char **argv){
if (argc != 6) {
printf("Usage: %s h N D Pd Pl\nwhere:\n", argv[0]);
printf("\th is the variance\n");
printf("\tN is the the number of points\n");
printf("\tD is the number of dimensions of each point\n");
printf("\tPd is the path of the dataset file\n");
printf("\tPl is the path of the labels file\n");
exit(1);
}
DEVIATION = atoi(argv[1]);
NUMBER_OF_POINTS = atoi(argv[2]);
DIMENSIONS = atoi(argv[3]);
POINTS_FILENAME = argv[4];
LABELS_FILENAME = argv[5];
}
void init(double ***vectors, char **labels, parameters *params){
int bytes_read = 0;
// initializes vectors
FILE *points_file;
points_file = fopen(POINTS_FILENAME, "rb");
if (points_file != NULL){
// allocates memory for the array
(*vectors) = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
// reads vectors dataset from file
for (int i=0; i<NUMBER_OF_POINTS; i++){
bytes_read = fread((*vectors)[i], sizeof(double), DIMENSIONS, points_file);
if ( bytes_read != DIMENSIONS ){
if(feof(points_file)){
printf("Premature end of file reached.\n");
} else{
printf("Error reading points file.");
}
fclose(points_file);
exit(EXIT_FAILURE);
}
}
} else {
printf("Error reading dataset file.\n");
exit(EXIT_FAILURE);
}
fclose(points_file);
// initializes file that will contain the labels (train)
FILE *labels_file;
labels_file = fopen(LABELS_FILENAME, "rb");
if (labels_file != NULL){
// NOTE : Labels were classified as <class 'numpy.uint8'>
// variables of type uint8 are stored as 1-byte (8-bit) unsigned integers
// gets number of labels
fseek(labels_file, 0L, SEEK_END);
long int pos = ftell(labels_file);
rewind(labels_file);
int label_elements = pos/ sizeof(char);
// allocates memory for the array
*labels = (char*)malloc(label_elements* sizeof(char));
fseek(labels_file, 0L, SEEK_SET);
bytes_read = fread((*labels), sizeof(char), label_elements, labels_file);
if ( bytes_read != label_elements ){
if(feof(points_file)){
printf("Premature end of file reached.\n");
} else{
printf("Error reading points file.");
}
fclose(labels_file);
exit(EXIT_FAILURE);
}
}
fclose(labels_file);
// MEAN SHIFT OPTIONS
params->epsilon = 0.0001;
params->verbose = false;
params->display = false;
}
int meanshift(double **original_points, double ***shifted_points, int deviation
, parameters *opt){
static int iteration = 0;
static double **mean_shift_vector, **kernel_matrix, *denominator;
// allocates memory and copies original points on first iteration
if (iteration == 0 || (*shifted_points) == NULL){
(*shifted_points) = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
duplicate(original_points, NUMBER_OF_POINTS, DIMENSIONS, shifted_points);
// allocates memory for mean shift vector
mean_shift_vector = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
// initializes elements of mean_shift_vector to inf
for (int i=0;i<NUMBER_OF_POINTS;i++){
for (int j=0;j<DIMENSIONS;j++){
mean_shift_vector[i][j] = DBL_MAX;
}
}
// allocates memory for other arrays needed
kernel_matrix = alloc_2d_double(NUMBER_OF_POINTS, NUMBER_OF_POINTS);
denominator = (double *)malloc(NUMBER_OF_POINTS * sizeof(double));
}
// finds pairwise distance matrix (inside radius)
// [I, D] = rangesearch(x,y,h);
for (int i=0; i<NUMBER_OF_POINTS; i++){
double sum = 0;
for (int j=0; j<NUMBER_OF_POINTS; j++){
double distance = calculateDistance((*shifted_points)[i]
, original_points[j]);
double deviation_square = deviation*deviation;
if (distance < deviation_square){
// computes kernel matrix
double pow = ((-1)*(distance * distance))/(2*(deviation_square));
kernel_matrix[i][j] = exp(pow);
} else {
kernel_matrix[i][j] = 0;
}
if (i == j){
kernel_matrix[i][j] += 1;
}
sum = sum + kernel_matrix[i][j];
}
denominator[i] = sum;
}
// creates new y vector
double **new_shift = alloc_2d_double(NUMBER_OF_POINTS, DIMENSIONS);
//==============================================================================
// builds nominator
/*multiply(kernel_matrix, original_points, new_shift);*/
Matrix d_kernel_matrix;
d_kernel_matrix.width = NUMBER_OF_POINTS;
d_kernel_matrix.height = NUMBER_OF_POINTS;
int size = NUMBER_OF_POINTS * NUMBER_OF_POINTS * sizeof(double);
cudaMalloc(&d_kernel_matrix.elements, size);
cudaMemcpy(d_kernel_matrix.elements, &(kernel_matrix[0][0]), size, cudaMemcpyHostToDevice);
Matrix d_original_points;
d_original_points.width = DIMENSIONS;
d_original_points.height = NUMBER_OF_POINTS;
size = NUMBER_OF_POINTS * DIMENSIONS * sizeof(double);
cudaMalloc(&d_original_points.elements, size);
cudaMemcpy(d_original_points.elements, &(original_points[0][0]), size, cudaMemcpyHostToDevice);
Matrix d_new_shift;
d_new_shift.width = DIMENSIONS;
d_new_shift.height = NUMBER_OF_POINTS;
size = NUMBER_OF_POINTS * DIMENSIONS * sizeof(double);
cudaMalloc(&d_new_shift.elements, size);
dim3 dimBlock(BLOCK_SIZE, BLOCK_SIZE);
dim3 dimGrid(d_original_points.width / dimBlock.x, d_kernel_matrix.height / dimBlock.y);
multiply_kernel<<<dimGrid, dimBlock>>>(d_kernel_matrix, d_original_points
, d_new_shift);
size = NUMBER_OF_POINTS * DIMENSIONS * sizeof(double);
cudaMemcpy(&(new_shift[0][0]), d_new_shift.elements, size, cudaMemcpyDeviceToHost);
cudaFree(d_kernel_matrix.elements);
cudaFree(d_original_points.elements);
cudaFree(d_new_shift.elements);
//==============================================================================
// divides element-wise
for (int i=0; i<NUMBER_OF_POINTS; i++){
for (int j=0; j<DIMENSIONS; j++){
new_shift[i][j] = new_shift[i][j] / denominator[i];
// calculates mean-shift vector at the same time
mean_shift_vector[i][j] = new_shift[i][j] - (*shifted_points)[i][j];
}
}
// frees previously shifted points, they're now garbage
free((*shifted_points)[0]);
// updates shifted points pointer to the new array address
shifted_points = &new_shift;
save_matrix((*shifted_points), iteration);
// calculates norm of the new mean shift vector
double current_norm = norm(mean_shift_vector, NUMBER_OF_POINTS, DIMENSIONS);
printf("Iteration n. %d, error %f \n", iteration, current_norm);
/** iterates until convergence **/
if (current_norm > opt->epsilon) {
++iteration;
meanshift(original_points, shifted_points, deviation, opt);
}
if (iteration == 0){
// cleans up this iteration's allocations
free(mean_shift_vector[0]);
free(mean_shift_vector);
free(kernel_matrix[0]);
free(kernel_matrix);
free(denominator);
}
return iteration;
}
// TODO check why there's is a difference in the norm calculate in matlab
double norm(double **matrix, int rows, int cols){
double sum=0, temp_mul=0;
for (int i=0; i<rows; i++) {
for (int j=0; j<cols; j++) {
temp_mul = matrix[i][j] * matrix[i][j];
sum = sum + temp_mul;
}
}
double norm = sqrt(sum);
return norm;
}
double calculateDistance(double *y, double *x){
double sum = 0, dif;
for (int i=0; i<DIMENSIONS; i++){
dif = y[i]-x[i];
sum += dif * dif;
}
double distance = sqrt(sum);
return distance;
}
double **alloc_2d_double(int rows, int cols) {
double *data = (double *) malloc(rows*cols*sizeof(double));
double **array = (double **) malloc(rows*sizeof(double*));
for (int i=0; i<rows; i++)
array[i] = &(data[cols*i]);
return array;
}
void duplicate(double **source, int rows, int cols, double ***dest){
for (int i=0; i<rows; i++){
for (int j=0; j<cols; j++){
(*dest)[i][j] = source[i][j];
}
}
}
void print_matrix(double **array, int rows, int cols){
for (int i=0; i<cols; i++){
for (int j=0; j<rows; j++){
printf("%f ", array[j][i]);
}
printf("\n");
}
}
void save_matrix(double **matrix, int iteration){
char filename[50];
snprintf(filename, sizeof(filename), "%s%d", "../output/output_", iteration);
FILE *file;
file = fopen(filename, "w");
for (int rows=0; rows<NUMBER_OF_POINTS; ++rows){
for (int cols=0; cols<DIMENSIONS; ++cols){
fprintf(file, "%f", matrix[rows][cols]);
if (cols != DIMENSIONS - 1){
fprintf(file, ",");
}
}
fprintf(file, "\n");
}
}

22
mean_shift_cuda/meanshift_declarations.h → mean_shift_cuda/meanshift_utils.h

@ -1,8 +1,9 @@
#ifndef SERIAL_DECLARATIONS_H /* Include guard */
#define SERIAL_DECLARATIONS_H
#ifndef SERIAL_UTILS_H /* Include guard */
#define SERIAL_UTILS_H
#include <stdbool.h>
extern int DEVIATION;
extern int NUMBER_OF_POINTS;
extern int DIMENSIONS;
extern char* POINTS_FILENAME;
@ -15,17 +16,22 @@ typedef struct parameters {
} parameters;
//Function get_args parses command line arguments.
void get_args(int argc, char **argv, int *h);
void get_args(int argc, char **argv);
//Function init reads the dataset and label arrays from the corresponding files.
void init(double ***vectors, char **labels, parameters *params);
//Function meanshift recursively shifts original points according to th
//mean-shift algorithm saving the result to shiftedPoints. Struct opt has user
//options, h is the desirable deviation, iteration is this call's iteration
//number.
//options, h is the desirable deviation.
int meanshift(double **original_points, double ***shifted_points, int h
, parameters *opt, int iteration);
, parameters *opt);
//Function norm returns the second norm of matrix of dimensions rowsXcols.
//double norm(double **matrix, int rows, int cols);
double norm(double **matrix, int rows, int cols);
//Function calculateDistance returns the distance between x and y vectors.
double calculateDistance(double *y, double *x);
//Function alloc_2d_double allocates rows*cols bytes of continuous memory.
double **alloc_2d_double(int rows, int cols);
@ -41,4 +47,4 @@ void print_matrix(double **array, int rows, int cols);
void save_matrix(double **matrix
, int iteration);
#endif //SERIAL_DECLARATIONS_H
#endif //SERIAL_UTILS_H
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