csci5451/assignments/01/lc_openmp.c
2023-10-09 03:49:21 -05:00

143 lines
No EOL
4 KiB
C

#include <math.h>
#include <omp.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "common.h"
int main(int argc, char **argv) {
if (argc < 5) {
fprintf(stderr,
"USAGE: %s data_file label_file outer_iterations thread_count",
argv[0]);
exit(1);
}
char *data_file_name = argv[1], *label_file_name = argv[2];
int outer_iterations = atoi(argv[3]);
int thread_count = atoi(argv[4]);
omp_set_num_threads(thread_count);
struct data *data = read_data(data_file_name);
struct labels *labels = read_labels(label_file_name);
FLOAT *w = calloc(data->dimensions, sizeof(FLOAT));
FLOAT *new_w = calloc(data->dimensions, sizeof(FLOAT));
FLOAT *inner_calc = calloc(data->dimensions * data->rows, sizeof(FLOAT));
printf("Running %d iteration(s) with %d thread(s).\n", outer_iterations,
thread_count);
double program_start_time = monotonic_seconds();
double total_compute_time = 0;
for (int iter = 0; iter < outer_iterations; iter++) {
double iter_start_time = monotonic_seconds();
#pragma omp parallel for default(shared)
for (int i = 0; i < data->dimensions; i++) {
// #pragma omp parallel for default(shared)
for (int j = 0; j < data->rows; j++) {
FLOAT x_ni_w_ni = 0;
// #pragma omp parallel for default(shared) reduction(+ : x_ni_w_ni)
for (int i2 = 0; i2 < data->dimensions; i2++) {
if (i2 == i)
continue;
x_ni_w_ni = data->buf[data->rows * i2 + j] * w[i2];
}
inner_calc[data->rows * i + j] = labels->buf[j] - x_ni_w_ni;
}
FLOAT numer = 0, denom = 0;
// #pragma omp parallel for default(shared) reduction(+ : numer, denom)
for (int j = 0; j < data->rows; j++) {
FLOAT xij = data->buf[data->rows * i + j];
numer += xij * inner_calc[data->rows * i + j];
denom += xij * xij;
}
if (denom == 0)
new_w[i] = 0;
else
new_w[i] = numer / denom;
}
double iter_end_time = monotonic_seconds();
total_compute_time += iter_end_time - iter_start_time;
printf("Iter duration (no print): %0.04fs\n",
iter_end_time - iter_start_time);
// Update w
// printf("w = [");
for (int idx = 0; idx < data->dimensions; idx++) {
w[idx] = new_w[idx];
// printf("%.3f ", w[idx]);
}
// printf("]\n");
// Compute loss
FLOAT loss_sum = 0;
#pragma omp parallel for default(shared)
for (int j = 0; j < data->rows; j++) {
FLOAT loss_value = 0;
for (int i = 0; i < data->dimensions; i++) {
loss_value += data->buf[data->rows * i + j] * w[i];
}
loss_value -= labels->buf[j];
loss_sum += loss_value * loss_value;
}
FLOAT loss = sqrt(loss_sum);
printf("Loss: %0.04f\n", loss);
// memcpy(w, new_w, data->dimensions * sizeof(FLOAT));
}
double program_end_time = monotonic_seconds();
printf("Program time (compute): %0.04fs\n", total_compute_time);
printf("Program time (total): %0.04fs\n",
program_end_time - program_start_time);
// free(loss_matrix);
free(inner_calc);
free(new_w);
free(data->buf);
free(labels->buf);
free(data);
free(labels);
// NOTE: NOT PART OF THE ASSIGNMENT
// Perform validation to see how well the model performs on training data
if (argc >= 7) {
struct data *test_data = read_data(argv[5]);
struct labels *test_label = read_labels(argv[6]);
int num_correct = 0;
for (int j = 0; j < test_data->rows; j++) {
FLOAT output = 0;
for (int i = 0; i < test_data->dimensions; i++) {
output += test_data->buf[test_data->rows * i + j] * w[i];
}
FLOAT correct_answer = test_label->buf[j];
FLOAT incorrect_answer = -correct_answer;
if (fabs(output - correct_answer) < fabs(output - incorrect_answer))
num_correct += 1;
}
printf("num correct: %d, out of %d (%.2f%%)\n", num_correct,
test_data->rows, (100.0 * num_correct) / test_data->rows);
}
free(w);
return 0;
}