// bench_funcs.cpp
#include "bench_funcs.h"
#include <omp.h>
#include <cmath>
#include <cstddef>
#include <vector>
#include <algorithm>

// A: parallel sum 
double sum_basic(const std::vector<double>& x)
{
    double sum = 0.0;
    #pragma omp parallel for reduction(+:sum)
    for (std::size_t i = 0; i < x.size(); ++i) sum += x[i];
    return sum;
}

// A: parallel dot product 
double dot_basic(const std::vector<double>& x, const std::vector<double>& y)
{
    std::size_t N = x.size();
    double sum = 0.0;
    #pragma omp parallel for reduction(+:sum)
    for (std::size_t i = 0; i < N; ++i) sum += x[i] * y[i];
    return sum;
}

// Kahan remains same
double dot_kahan(const std::vector<double>& x, const std::vector<double>& y)
{
    double sum = 0.0;
    double c = 0.0;
    for (std::size_t i = 0; i < x.size(); ++i)
    {
        double prod = x[i] * y[i];
        double yk = prod - c;
        double t = sum + yk;
        c = (t - sum) - yk;
        sum = t;
    }
    return sum;
}

// Norm (sum of squares) 
double norm_basic(const std::vector<double>& x)
{
    double sumsq = 0.0;
    #pragma omp parallel for reduction(+:sumsq)
    for (std::size_t i = 0; i < x.size(); ++i) sumsq += x[i]*x[i];
    return sumsq;
}

// B: matvec (row-major)
void matvec_rowmajor(const std::vector<double>& A, std::size_t M, std::size_t N,
                     const std::vector<double>& x, std::vector<double>& b)
{
    b.assign(M, 0.0);
    #pragma omp parallel for
    for (std::size_t i = 0; i < M; ++i) {
        double tmp = 0.0;
        const double* Ai = &A[i*N];
        for (std::size_t j = 0; j < N; ++j) tmp += Ai[j] * x[j];
        b[i] = tmp;
    }
}

// C: matmul (row-major)
void matmul_rowmajor(const std::vector<double>& A, std::size_t M, std::size_t L,
                     const std::vector<double>& B, std::size_t N,
                     std::vector<double>& C)
{
    C.assign(M * N, 0.0);
    // Parallelize over output rows (i)
    #pragma omp parallel for
    for (std::size_t i = 0; i < M; ++i) {
        for (std::size_t k = 0; k < L; ++k) {
            double Aik = A[i*L + k];
            const double* Bk = &B[k*N];
            double* Ci = &C[i*N];
            for (std::size_t j = 0; j < N; ++j) {
                Ci[j] += Aik * Bk[j];
            }
        }
    }
}

// D: polynomial evaluation (Horner), parallel over x points
void polyp_horner(const std::vector<double>& a, const std::vector<double>& x, std::vector<double>& y)
{
    std::size_t p = a.size() - 1;
    std::size_t N = x.size();
    y.assign(N, 0.0);

    #pragma omp parallel for
    for (std::size_t i = 0; i < N; ++i) {
        double xi = x[i];
        double val = a[p];
        for (std::size_t k = p; k-- > 0; ) { 
            val = val * xi + a[k];
        }
        y[i] = val;
    }
}