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matrix.cpp
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matrix.cpp
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#include <iostream>
#include <thread>
#include <algorithm>
#include <vector>
#include <chrono>
#include <fstream>
using namespace std::chrono;
using namespace std;
class Matrix{
int* data;
int rows;
int columns;
public:
Matrix(int _n, int _m): rows(_n), columns(_m){
data = new int[rows * columns];
//init the data array to zero
fill(data, data + rows*columns, 0);
}
void set_value(int i, int j, int value){
data[i*columns + j] = value;
}
void set_all(int value){
fill(data, data + rows*columns, value);
}
void print(){
for(int i = 0; i < this->rows; i++){
for(int j = 0; j < this->columns; j++){
cout<<data[i+j]<<" ";
}
cout<<endl;
}
}
static void multiply(Matrix *x, Matrix *y, Matrix *results){
if(!(x->columns == y->rows))
cout << "Error: Invalid Dimension of Matrix for Multiplication"<<endl;
int r = results->rows * results->columns;
for(int i = 0; i < r; i++){
for(int j = 0; j < x->columns; j++){
int row = (i /results->columns)*x->columns + j;
int column = i % results->rows + j*y->columns;
results->data[i] = x->data[row ] * y->data[ column];
}
}
}
static void parallel_multiply(Matrix *x, Matrix *y, Matrix *results){
struct process_data_chunk{
void operator()(Matrix *x, Matrix *y, Matrix *results, int start_index, int end_index){
for(int i = start_index; i < end_index; i++){
for(int j = 0; j < x->columns; j++){
int row = (i /results->columns)*x->columns + j;
int column = i % results->rows + j*y->columns;
results->data[i] = x->data[row ] * y->data[ column];
}
}
}
};
int length = results->rows * results->columns;
if(!length) return;
int min_per_thread = 10000;
int max_threads = (length + min_per_thread - 1) / min_per_thread;
int hardware_threads = thread::hardware_concurrency();
int num_threads = min(hardware_threads != 0 ? hardware_threads : 2, max_threads);
int block_size = length / num_threads;
vector<thread> threads(num_threads - 1);
int block_start = 0;
int block_end = 0;
{
for(unsigned long i = 0; i < (num_threads -1); i++){
block_start = i * block_size;
block_end = block_start + block_size;
threads[i] = thread(process_data_chunk(), results, x, y, block_start, block_end);
}
process_data_chunk()(results, x, y, block_end, length);
for(int i=0; i<threads.size(); ++i)
if(threads[i].joinable())
threads[i].join();
}
}
};
int main(){
vector<int> matrix_sizes = {10, 50, 100, 250, 500, 1000, 2000};
string out_string;
for(vector<int>::iterator ptr = matrix_sizes.begin(); ptr < matrix_sizes.end(); ptr++ ){
int matrix_size = *ptr;
Matrix A(matrix_size, matrix_size);
Matrix B(matrix_size, matrix_size);
Matrix C(matrix_size, matrix_size);
Matrix D(matrix_size, matrix_size);
A.set_all(1);
B.set_all(1);
unsigned long duration_par = 0;
unsigned long duration_seq = 0;
int test_length = 5;
for(int i = 0; i<test_length; i++){
auto start = high_resolution_clock::now();
Matrix::multiply(&A, &B, &C);
auto stop = high_resolution_clock::now();
auto duration = duration_cast<microseconds>(stop - start);
cout<<"Matrix Size " << to_string(matrix_size) <<", Sequential Matrix Mult "<< duration.count() << endl;
duration_seq += duration.count();
start = high_resolution_clock::now();
Matrix::parallel_multiply(&A, &B, &D);
stop = high_resolution_clock::now();
duration = duration_cast<microseconds>(stop - start);
cout<<"Matrix Size " << to_string(matrix_size) <<", Parallel Matrix Mult "<< duration.count() << endl<<endl;
duration_par += duration.count();
}
out_string += "Matrix Size " + to_string(matrix_size)+ ", Sequential Matrix Mult\n Time:" + to_string(duration_seq/test_length) + "\n";
out_string += "Matrix Size " + to_string(matrix_size)+ ", Parallel Matrix Mult\n Time:" + to_string(duration_par/test_length) + "\n\n";
}
cout<<out_string;
ofstream myfile("results.txt");
if(myfile.is_open())
myfile<<out_string;
return 0;
}