### Instruction:
Develop a C++ program that uses multithreading to perform matrix multiplication on two large matrices. The program should read the matrices from text files and write the result to another text file. Measure and display the time taken for the operation.


### Response:

Here's a C++ program that uses multithreading to perform matrix multiplication on two large matrices. The program reads the matrices from text files and writes the result to another text file. It also measures and displays the time taken for the operation.

```cpp
#include <iostream>
#include <fstream>
#include <vector>
#include <thread>
#include <chrono>

using namespace std;

void multiply_matrices(const vector<vector<int>>& A, const vector<vector<int>>& B,
                       vector<vector<int>>& C, int start_row, int end_row) {
    for (int i = start_row; i < end_row; ++i) {
        for (int j = 0; j < B[0].size(); ++j) {
            for (int k = 0; k < A[0].size(); ++k) {
                C[i][j] += A[i][k] * B[k][j];
            }
        }
    }
}

vector<vector<int>> read_matrix_from_file(const string& filename) {
    ifstream input(filename);
    int rows, cols;
    input >> rows >> cols;
    vector<vector<int>> matrix(rows, vector<int>(cols));
    for (int i = 0; i < rows; ++i) {
        for (int j = 0; j < cols; ++j) {
            input >> matrix[i][j];
        }
    }
    return matrix;
}

void write_matrix_to_file(const string& filename, const vector<vector<int>>& matrix) {
    ofstream output(filename);
    output << matrix.size() << " " << matrix[0].size() << endl;
    for (const auto& row : matrix) {
        for (int val : row) {
            output << val << " ";
        }
        output << endl;
    }
}

int main() {
    // Read matrices from files
    vector<vector<int>> A = read_matrix_from_file("matrixA.txt");
    vector<vector<int>> B = read_matrix_from_file("matrixB.txt");

    // Check if matrices can be multiplied
    if (A[0].size() != B.size()) {
        cerr << "Error: Matrices cannot be multiplied" << endl;
        return 1;
    }

    // Initialize result matrix
    vector<vector<int>> C(A.size(), vector<int>(B[0].size(), 0));

    // Measure time taken for the operation
    auto start_time = chrono::high_resolution_clock::now();

    // Perform matrix multiplication using multithreading
    int num_threads = thread::hardware_concurrency();
    vector<thread> threads(num_threads);
    int rows_per_thread = A.size() / num_threads;

    for (int i = 0; i < num_threads; ++i) {
        int start_row = i * rows_per_thread;
        int end_row = (i == num_threads - 1) ? A.size() : start_row + rows_per_thread;
        threads[i] = thread(multiply_matrices, ref(A), ref(B), ref(C), start_row, end_row);
    }

    for (auto& t : threads) {
        t.join();
    }

    auto end_time = chrono::high_resolution_clock::now();
    auto duration = chrono::duration_cast<chrono::milliseconds>(end_time - start_time).count();

    // Write result to file
    write_matrix_to_file("result.txt", C);

    cout << "Matrix multiplication completed in " << duration << " milliseconds." << endl;

    return 0;
}
```

To use this program, create two text files named `matrixA.txt` and `matrixB.txt` with the following format:

```
<number_of_rows> <number_of_columns>
<row_1_values_separated_by_spaces>
<row_2_values_separated_by_spaces>
...
```

For example:

```
3 3
1 2 3
4 5 6
7 8 9
```

After running the program, you'll find a new text file named `result.txt` containing the result of the matrix multiplication. The time taken for the operation will be displayed on the console.