singe vs multi error

lab06/MonteCarloPi.cpp

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+#include "matrix.h"
+#include <chrono>
+#include <cstdint>
+#include <fstream>
+#include <iostream>
+#include <omp.h>
+#include <random>
+
+struct bench_result {
+  double time;
+  double pi;
+};
+
+double monteCarloPi(int64_t N) {
+  int localCount = 0;
+  std::mt19937 generator(std::random_device{}());
+  std::uniform_real_distribution<double> dist(0.0, 1.0);
+#pragma omp parallel for reduction(+ : localCount)
+  for (int i = 0; i < N; ++i) {
+    double x = dist(generator);
+    double y = dist(generator);
+    if (x * x + y * y <= 1.0) {
+      localCount++;
+    }
+  }
+
+  return 4.0 * localCount / N;
+}
+
+bench_result benchmark(int numThreads, int64_t N, double function(int64_t)) {
+  omp_set_num_threads(numThreads);
+
+  // start time measurement
+  auto start = std::chrono::system_clock::now();
+  auto result = bench_result{0.0, 0.0};
+
+  // perform benchmark
+  const int maxNumExec = 10;
+  for (int nExec = 0; nExec < maxNumExec; ++nExec) {
+    result.pi = function(N);
+  }
+
+  auto end = std::chrono::system_clock::now();
+  std::chrono::duration<double, std::milli> diff = end - start;
+  result.time = diff.count() / maxNumExec;
+
+  return result;
+}
+
+int main() {
+  const int64_t max_n = 10000000;
+  const int numThreads = 12;
+  std::ofstream fout("multi_monte.csv", std::ios::app);
+  fout << "pi" << ",";
+  fout << "time" << "\n";
+
+  for (int64_t i = 1000; i <= max_n; i += 1000) {
+    const bench_result res = benchmark(numThreads, i, monteCarloPi);
+
+    fout << res.pi << ",";
+    fout << res.time << "\n";
+  }
+}

lab06/MonteCarloPiThreads.cpp

@@ -0,0 +1,63 @@
+#include "matrix.h"
+#include <chrono>
+#include <cstdint>
+#include <fstream>
+#include <iostream>
+#include <omp.h>
+#include <random>
+
+struct bench_result {
+  double time;
+  double pi;
+};
+
+double monteCarloPi(int64_t N) {
+  int localCount = 0;
+  std::mt19937 generator(std::random_device{}());
+  std::uniform_real_distribution<double> dist(0.0, 1.0);
+#pragma omp parallel for reduction(+ : localCount)
+  for (int i = 0; i < N; ++i) {
+    double x = dist(generator);
+    double y = dist(generator);
+    if (x * x + y * y <= 1.0) {
+      localCount++;
+    }
+  }
+
+  return 4.0 * localCount / N;
+}
+
+bench_result benchmark(int numThreads, int64_t N, double function(int64_t)) {
+  omp_set_num_threads(numThreads);
+
+  // start time measurement
+  auto start = std::chrono::system_clock::now();
+  auto result = bench_result{0.0, 0.0};
+
+  // perform benchmark
+  const int maxNumExec = 10;
+  for (int nExec = 0; nExec < maxNumExec; ++nExec) {
+    result.pi = function(N);
+  }
+
+  auto end = std::chrono::system_clock::now();
+  std::chrono::duration<double, std::milli> diff = end - start;
+  result.time = diff.count() / maxNumExec;
+
+  return result;
+}
+
+int main() {
+  const int64_t max_n = 10000000;
+  const int numThreads = 12;
+  std::ofstream fout("multi_monte.csv", std::ios::app);
+  fout << "pi" << ",";
+  fout << "time" << "\n";
+
+  for (int64_t i = 1000; i <= max_n; i += 1000) {
+    const bench_result res = benchmark(numThreads, i, monteCarloPi);
+
+    fout << res.pi << ",";
+    fout << res.time << "\n";
+  }
+}