From 9429c9d22b7786d7e9ddd4a2c6fe5475aac23ca9 Mon Sep 17 00:00:00 2001
From: "lisa.pizzo" <lisa.pizzo@noreply.imsc.uni-graz.at>
Date: Thu, 4 Dec 2025 12:17:08 +0100
Subject: [PATCH] Delete Sheet5/bench_funcs.cpp

---
 Sheet5/bench_funcs.cpp | 177 -----------------------------------------
 1 file changed, 177 deletions(-)
 delete mode 100644 Sheet5/bench_funcs.cpp

diff --git a/Sheet5/bench_funcs.cpp b/Sheet5/bench_funcs.cpp
deleted file mode 100644
index 4123517..0000000
--- a/Sheet5/bench_funcs.cpp
+++ /dev/null
@@ -1,177 +0,0 @@
-// 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;
-    }
-}
-
-// Parallel assembly of tridiagonal FEM matrix (CSR)
-void build_fem_system(std::size_t n, CSR& K, std::vector<double>& f)
-{
-    K.n = n;
-    K.row_ptr.resize(n+1);
-    f.assign(n, 1.0);
-    K.val.resize(3*n); // Each row has at most 3 non-zero entries: [-1,2,-1]
-    K.col.resize(3*n);
-
-    for (std::size_t i = 0; i < n; ++i)
-        K.row_ptr[i] = 3*i;
-    K.row_ptr[n] = 3*n;
-
-    #pragma omp parallel for     // Fill matrix in parallel
-    for (std::size_t i = 0; i < n; ++i) {
-        std::size_t base = 3*i;
-
-        if (i > 0) {
-            K.val[base] = -1.0;
-            K.col[base] = i - 1;
-        } else {
-            K.val[base] = 0.0;
-            K.col[base] = 0;
-        }
-
-        K.val[base + 1] = 2.0;
-        K.col[base + 1] = i;
-
-        if (i + 1 < n) {
-            K.val[base + 2] = -1.0;
-            K.col[base + 2] = i + 1;
-        } else {
-            K.val[base + 2] = 0.0;
-            K.col[base + 2] = i;
-        }
-    }
-}
-
-// Parallel Jacobi iteration
-void jacobi_csr_parallel(const CSR& K, const std::vector<double>& f,
-                         std::vector<double>& u,
-                         std::size_t max_iter, double omega, double tol)
-{
-    std::size_t n = K.n;
-    u.assign(n, 0.0);
-    std::vector<double> u_new(n, 0.0);
-
-    for (std::size_t iter = 0; iter < max_iter; ++iter) {
-        double max_err = 0.0;
-
-        #pragma omp parallel for reduction(max:max_err)
-        for (std::size_t i = 0; i < n; ++i) {
-            double diag = 0.0;
-            double sum  = 0.0;
-
-            for (std::size_t idx = K.row_ptr[i]; idx < K.row_ptr[i+1]; ++idx) {
-                std::size_t j = K.col[idx];
-                double v = K.val[idx];
-                if (j == i) diag = v;
-                else sum += v * u[j];
-            }
-
-            double ui_new = u[i] + omega * (f[i] - sum - diag*u[i]) / diag;
-            u_new[i] = ui_new;
-
-            double err = std::fabs(ui_new - u[i]);
-            if (err > max_err) max_err = err;
-        }
-
-        u.swap(u_new);
-        if (max_err < tol) break;
-    }
-}