distributedtests.cpp

#include "distributedmatrix.hpp"
#include "matrix.hpp"
#include "mlp_sgd_distributed.cpp"
#include <mpi.h>
#include <fstream>
#include <iostream>
#include <cassert>
#include <cmath>
#include <functional>

// Fonction utilitaire pour vérifier si deux doubles sont proches
bool approxEqual(double a, double b, double epsilon = 1e-10) {
    return std::abs(a - b) < epsilon;
}

// Fonction utilitaire pour vérifier si deux matrices sont égales
bool matricesEqual(const Matrix& a, const Matrix& b, double epsilon = 1e-10) {
    if (a.numRows() != b.numRows() || a.numCols() != b.numCols()) {
        return false;
    }

    for (int i = 0; i < a.numRows(); i++) {
        for (int j = 0; j < a.numCols(); j++) {
            if (!approxEqual(a.get(i, j), b.get(i, j), epsilon)) {
                return false;
            }
        }
    }

    return true;
}


void testMultiplyTransposed() {
    int sizes[] = {512, 1024, 2058};
    int rank, numProcs;
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);
    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);

    std::ofstream csvFile;
    if (rank == 0) {
        csvFile.open("results.csv");
        csvFile << "MatrixSize,SequentialTime,DistributedTime,SpeedUp\n";
    }

    for (int s = 0; s < 3; ++s) {
        int N = sizes[s];

        // Initialisation des matrices pleines
        Matrix matrix1Full(N, N); 
        Matrix matrix2Full(N, N);
        for (int i = 0; i < N; i++) {
            for (int j = 0; j < N; j++) {
                matrix1Full.set(i, j, i * 5 + j + 1);
                matrix2Full.set(i, j, i * 5 + j + 2);
            }
        }

        // Création des matrices distribuées
        DistributedMatrix matrix1(matrix1Full, numProcs);
        DistributedMatrix matrix2(matrix2Full, numProcs);

        // Chronométrage de l'opération distribuée
        MPI_Barrier(MPI_COMM_WORLD);
        double startDistributed = MPI_Wtime();
        Matrix resultDistributed = matrix1.multiplyTransposed(matrix2);
        MPI_Barrier(MPI_COMM_WORLD);
        double endDistributed = MPI_Wtime();
        double timeDist = endDistributed - startDistributed;

        // Chronométrage de l'opération séquentielle
        double timeSeq = 0.0;
        if (rank == 0) {
            double startSequential = MPI_Wtime();
            Matrix resultSequential = matrix1Full * matrix2Full.transpose();
            double endSequential = MPI_Wtime();
            timeSeq = endSequential - startSequential;

            double speedUp = timeSeq / timeDist;

            std::cout << "Matrix size: " << N << "x" << N << std::endl;
            std::cout << "Sequential time: " << timeSeq << " s" << std::endl;
            std::cout << "Distributed time: " << timeDist << " s" << std::endl;
            std::cout << "Speed up (Seq/Dist): " << speedUp << std::endl;
            std::cout << "-----------------------------------------" << std::endl;

            csvFile << N << "," << timeSeq << "," << timeDist << "," << speedUp << "\n";
        }
    }

    if (rank == 0) {
        csvFile.close();
        std::cout << "Results written to results.csv\n";
    }
}

int main(int argc, char** argv) {
    // Initialiser MPI
    int initialized;
    MPI_Initialized(&initialized);
    if (!initialized) {
        MPI_Init(&argc, &argv);
    }

    int rank;
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);

    if (rank == 0) {
        std::cout << "Starting DistributedMatrix tests..." << std::endl;
    }

    try {
        // Lancer le test
        testMultiplyTransposed();
        
        if (rank == 0) {
            std::cout << "All tests passed successfully!" << std::endl;
        }
    } 
    catch (std::exception& e) {
        if (rank == 0) {
            std::cerr << "Test failed with exception: " << e.what() << std::endl;
        }
        MPI_Abort(MPI_COMM_WORLD, 1);
    }

    // Finaliser MPI si nécessaire
    MPI_Finalize();
    return 0;
}