From 3ea298d64d8360fdf2afb094a67768578e50ce37 Mon Sep 17 00:00:00 2001
From: anapt <pt.anastasia@gmail.com>
Date: Tue, 23 Jan 2018 12:05:39 +0200
Subject: [PATCH] clean up

---
 cuda_helpers.cu |  21 ---
 mean-shift.cu   | 369 ------------------------------------------------
 2 files changed, 390 deletions(-)
 delete mode 100644 cuda_helpers.cu
 delete mode 100644 mean-shift.cu

diff --git a/cuda_helpers.cu b/cuda_helpers.cu
deleted file mode 100644
index 06433d8..0000000
--- a/cuda_helpers.cu
+++ /dev/null
@@ -1,21 +0,0 @@
-
-// Host code 
-int width = 64, height = 64; 
-float* devPtr; 
-size_t pitch; 
-cudaMallocPitch(&devPtr, &pitch, width * sizeof(float), height); 
-MyKernel<<<100, 512>>>(devPtr, pitch, width, height); 
-
-
-// Device code 
-__global__ voidMyKernel(float* devPtr, size_t pitch, int width, int height) { 
-    for (int r = 0; r < height; ++r) { 
-        float* row = (float*)((char*)devPtr + r * pitch);
-        for (int c = 0; c < width; ++c) {
-            float element = row[c]; 
-        } 
-    } 
-}
-
-Read more at: http://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#ixzz54kTh80mZ 
-Follow us: @GPUComputing on Twitter | NVIDIA on Facebook
\ No newline at end of file
diff --git a/mean-shift.cu b/mean-shift.cu
deleted file mode 100644
index 916c94a..0000000
--- a/mean-shift.cu
+++ /dev/null
@@ -1,369 +0,0 @@
-#include <stdio.h>
-#include <stdlib.h>
-#include <sys/time.h>
-#include <stdbool.h>
-#include <math.h>
-
-#define X "data/X.bin"
-#define L "data/L.bin"
-#define COLUMNS     2
-#define ROWS        600
-
-struct parameters {
-    double epsilon;
-    bool verbose;
-    bool display;
-};
-
-double **alloc_2d_double(int rows, int cols);
-double **duplicate(double **a, double **b, int rows, int cols);
-void meanshift(double **x, int h, struct parameters *opt);
-double norm(double ** m, int rows, int cols);
-void multiply(double ** matrix1, double ** matrix2, double ** output);
-double calculateDistance(double *, double *);
-void print_matrix(double ** array, int rows, int cols);
-
-
-struct timeval startwtime, endwtime;
-double seq_time;
-
-int main(int argc, char **argv){
-
-//    if (argc<2){
-//        printf("%s\n", "Specify the k");
-//        return 1;
-//    }
-//    = atoi(argv[1]);  // the k-parameter
-
-
-    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/COLUMNS;
-//    //printf("points : %d \n", points);
-    f = fopen(X, "rb");
-    double ** vectors;
-    vectors = alloc_2d_double(ROWS, COLUMNS);
-    for (int i=0; i<ROWS; i++){
-        int out = fread(vectors[i], sizeof(double), COLUMNS, f);
-    }
-    //printf("test : %f \n", vectors[0][0]);
-    //printf("test : %f \n", vectors[ROWS-1][COLUMNS-1]);
-
-    // initializing file that will contain the labels (train)
-    f = fopen(L, "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
-    int h = 1;
-    struct parameters params;
-    params.epsilon = 0.0001;
-    params.verbose = false;
-    params.display = false;
-    struct parameters *opt;
-    opt = &params;
-
-    // tic
-    gettimeofday (&startwtime, NULL);
-
-    meanshift(vectors, h, opt);
-
-    // 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
-
-}
-
-void meanshift(double **x, int h, struct parameters *opt){
-
-    double **y;
-    y = alloc_2d_double(ROWS, COLUMNS);
-    y = duplicate(x, y, ROWS, COLUMNS);
-
-    // mean shift vectors
-    double **m;
-    m = alloc_2d_double(ROWS, COLUMNS);
-    // initialize elements of m to inf
-    for (int i=0;i<ROWS;i++){
-        for (int j=0;j<COLUMNS;j++){
-            m[i][j] = DBL_MAX;
-        }
-    }
-
-    // initialize iteration counter
-    int iter = 0;
-
-    // printf("%f \n", opt->epsilon);
-
-    /** iterate until convergence **/
-    // printf("norm : %f \n", norm(m, ROWS, COLUMNS));
-    /** allocate memory **/
-    double ** W = alloc_2d_double(ROWS, ROWS);
-    double * l = malloc(ROWS * sizeof(double));
-
-    double * d_W;
-    cudaMalloc(&d_W, ROWS * ROWS * sizeof(double));
-    double * d_I;
-    cudaMalloc(&d_I, ROWS * sizeof(double));
-    double * d_y_new;
-    cudaMalloc(&d_y_new, ROWS * COLUMNS * sizeof(double));
-
-    double * d_y;
-    cudaMalloc(&d_y, ROWS * COLUMNS * sizeof(double));
-    double * d_m;
-    cudaMalloc(&d_m, ROWS * COLUMNS * sizeof(double));
-
-    //Copy vectors from host memory to device memory
-    cudaMemcpy(d_y, y, ROWS * COLUMNS * sizeof(double), cudaMemcpyHostToDevice);
-    // y[i][j] == d_y[COLUMNS*i + j]
-    cudaMemcpy(d_m, m, ROWS * COLUMNS * sizeof(double), cudaMemcpyHostToDevice);
-
-
-    while (norm(m, ROWS, COLUMNS) > opt->epsilon) {
-        iter = iter +1;
-        // find pairwise distance matrix (inside radius)
-        /** allocate memory for inside iteration arrays **/
-        double ** W = alloc_2d_double(ROWS, ROWS);
-        double * l = malloc(ROWS * sizeof(double));
-        // [I, D] = rangesearch(x,y,h);
-        for (int i=0; i<ROWS; i++){
-            for (int j=0; j<ROWS; j++){
-                double dist = calculateDistance(y[i],x[j]);
-
-                // 2sparse matrix
-                if (dist < h){
-                    W[i][j] = dist;
-                    //printf("%f \n", W[i][j]);
-                }else{
-                    W[i][j] = 0;
-                }
-            }
-        }
-
-
-        // for each element of W (x) do x^2
-        // size of W is [600 600]
-        // W is a sparse matrix -> apply to non-zero elements
-        for (int i=0; i<ROWS; i++){
-            double sum =0;
-            for (int j=0; j < ROWS; j++){
-                if (W[i][j] != 0){
-                    W[i][j] = W[i][j]*W[i][j];
-                    // compute kernel matrix
-                    // apply function to non zero elements of a sparse matrix
-                    double pow = ((-1)*(W[i][j]))/(2*(h*h));
-                    W[i][j] = exp(pow);
-                }
-                // make sure diagonal elements are 1
-                if (i==j){
-                    W[i][j] = W[i][j] +1;
-                }
-                // calculate sum(W,2)
-                sum = sum + W[i][j];
-            }
-            /** l array is correct**/
-            l[i] = sum;
-            // printf("l[%d] : %f \n", i, l[i]);
-        }
-        /** W is correct**/
-        //print_matrix(W, ROWS, ROWS);
-
-
-        // create new y vector
-        double** y_new = alloc_2d_double(ROWS, COLUMNS);
-
-        multiply(W, x, y_new);
-        /** y_new is CORRECT **/
-        // print_matrix(y_new, ROWS, COLUMNS);
-        // divide element-wise
-        for (int i=0; i<ROWS; i++){
-            for (int j=0; j<COLUMNS; j++){
-                y_new[i][j] = y_new[i][j] / l[i];
-            }
-        }
-
-        // calculate mean-shift vector
-        for (int i=0; i<ROWS; i++){
-            for (int j=0; j<COLUMNS; j++){
-                m[i][j] = y_new[i][j] - y[i][j];
-
-                // update y
-                y[i][j] = y_new[i][j];
-            }
-        }
-
-        printf("Iteration n. %d, error %f \n", iter, norm(m, ROWS, COLUMNS));
-        // TODO maybe keep y for live display later?
-    };
-
-
-
-}
-
-// allocates a 2d array in continuous memory positions
-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;
-}
-
-// copy the values of a 2d double array to another
-double **duplicate(double **a, double **b, int rows, int cols){
-    for (int i=0;i<rows;i++){
-        for (int j=0;j<cols;j++){
-            b[i][j] = a[i][j];
-        }
-    }
-    return b;
-}
-
-// TODO check why there's is a difference in the norm calculate in matlab
-double norm(double ** m, int rows, int cols){
-    double sum=0, a=0;
-    for (int i = 0; i < rows; i++) {
-        for (int j = 0; j < cols; j++) {
-            a = m[i][j] * m[i][j];
-            sum = sum + a;
-        }
-    }
-    double norm = sqrt(sum);
-    return norm;
-}
-
-double calculateDistance(double *y, double *x){
-    double sum = 0, dif;
-    for (int i=0;i<COLUMNS;i++){
-        dif = y[i]-x[i];
-        sum += dif * dif;
-    }
-    double distance = sqrt(sum);
-    return distance;
-}
-
-void multiply(double ** matrix1, double ** matrix2, double ** output){
-    // W dims are ROWS ROWS and x dims are ROWS COLUMNS
-
-    int i, j, k;
-    for (i=0; i<ROWS; i++){
-        for (j=0; j<COLUMNS; j++){
-            output[i][j] = 0;
-            for (k=0; k<ROWS; k++){
-                output[i][j] += matrix1[i][k] * matrix2[k][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");
-    }
-}
-
-__global__ void iteration (double* W, double epsilon){
-    // TODO check if they also need cudamalloc
-    // todo find how to keep counter
-    int iter;
-    int i = blockDim.x * blockIdx.x + threadIdx.x;
-    int j = blockDim.x * blockIdx.x + threadIdx.x;
-    while (norm > epsilon){
-        // TODO ITERATION
-        iter = iter +1;
-        // find pairwise distance matrix (inside radius)
-        /** allocate memory for inside iteration arrays **/
-        // TODO ALLOCATE MEMORY BEFORE CALLING KERNEL
-//        double ** W = alloc_2d_double(ROWS, ROWS);
-//        double * l = malloc(ROWS * sizeof(double));
-        // [I, D] = rangesearch(x,y,h);
-        for (int i=0; i<ROWS; i++){
-            for (int j=0; j<ROWS; j++){
-                // TODO REFACTOR CALCULATE DISTANCE
-                double dist = calculateDistance(y[i],x[j]);
-
-                // 2sparse matrix
-                if (dist < h){
-                    W[i][j] = dist;
-                    //printf("%f \n", W[i][j]);
-                }else{
-                    W[i][j] = 0;
-                }
-            }
-        }
-
-
-        // for each element of W (x) do x^2
-        // size of W is [600 600]
-        // W is a sparse matrix -> apply to non-zero elements
-        for (int i=0; i<ROWS; i++){
-            double sum =0;
-            for (int j=0; j < ROWS; j++){
-                if (W[i][j] != 0){
-                    W[i][j] = W[i][j]*W[i][j];
-                    // compute kernel matrix
-                    // apply function to non zero elements of a sparse matrix
-                    double pow = ((-1)*(W[i][j]))/(2*(h*h));
-                    W[i][j] = exp(pow);
-                }
-                // make sure diagonal elements are 1
-                if (i==j){
-                    W[i][j] = W[i][j] +1;
-                }
-                // calculate sum(W,2)
-                sum = sum + W[i][j];
-            }
-            /** l array is correct**/
-            l[i] = sum;
-            // printf("l[%d] : %f \n", i, l[i]);
-        }
-        /** W is correct**/
-        //print_matrix(W, ROWS, ROWS);
-
-
-        // create new y vector
-        double** y_new = alloc_2d_double(ROWS, COLUMNS);
-
-        multiply(W, x, y_new);
-        /** y_new is CORRECT **/
-        // print_matrix(y_new, ROWS, COLUMNS);
-        // divide element-wise
-        for (int i=0; i<ROWS; i++){
-            for (int j=0; j<COLUMNS; j++){
-                y_new[i][j] = y_new[i][j] / l[i];
-            }
-        }
-
-        // calculate mean-shift vector
-        for (int i=0; i<ROWS; i++){
-            for (int j=0; j<COLUMNS; j++){
-                m[i][j] = y_new[i][j] - y[i][j];
-
-                // update y
-                y[i][j] = y_new[i][j];
-            }
-        }
-
-        printf("Iteration n. %d, error %f \n", iter, norm(m, ROWS, COLUMNS));
-        // TODO maybe keep y for live display later?
-    }
-}
\ No newline at end of file