hey

.vscode/settings.json

@@ -0,0 +1,63 @@
+{
+    "files.associations": {
+        "fstream": "cpp",
+        "iosfwd": "cpp",
+        "atomic": "cpp",
+        "bit": "cpp",
+        "cctype": "cpp",
+        "charconv": "cpp",
+        "chrono": "cpp",
+        "clocale": "cpp",
+        "cmath": "cpp",
+        "compare": "cpp",
+        "concepts": "cpp",
+        "cstddef": "cpp",
+        "cstdint": "cpp",
+        "cstdio": "cpp",
+        "cstdlib": "cpp",
+        "cstring": "cpp",
+        "ctime": "cpp",
+        "cwchar": "cpp",
+        "exception": "cpp",
+        "format": "cpp",
+        "forward_list": "cpp",
+        "initializer_list": "cpp",
+        "iomanip": "cpp",
+        "ios": "cpp",
+        "iostream": "cpp",
+        "istream": "cpp",
+        "iterator": "cpp",
+        "limits": "cpp",
+        "locale": "cpp",
+        "memory": "cpp",
+        "new": "cpp",
+        "optional": "cpp",
+        "ostream": "cpp",
+        "ratio": "cpp",
+        "sstream": "cpp",
+        "stdexcept": "cpp",
+        "streambuf": "cpp",
+        "string": "cpp",
+        "system_error": "cpp",
+        "tuple": "cpp",
+        "type_traits": "cpp",
+        "typeinfo": "cpp",
+        "utility": "cpp",
+        "vector": "cpp",
+        "xfacet": "cpp",
+        "xiosbase": "cpp",
+        "xlocale": "cpp",
+        "xlocbuf": "cpp",
+        "xlocinfo": "cpp",
+        "xlocmes": "cpp",
+        "xlocmon": "cpp",
+        "xlocnum": "cpp",
+        "xloctime": "cpp",
+        "xmemory": "cpp",
+        "xstring": "cpp",
+        "xtr1common": "cpp",
+        "xutility": "cpp",
+        "stop_token": "cpp",
+        "thread": "cpp"
+    }
+}

lab02/main.py

@@ -8,7 +8,7 @@ def read_csv_pandas(filename):
     return df.values.flatten().astype(float)  # Konvertiert in flaches NumPy-Array (float, um Fehler zu vermeiden)
 
 # Daten einlesen
-data = read_csv_pandas("output.csv")
+data = read_csv_pandas("outcomes-100-1000000.csv")
 
 # Plot erstellen
 plt.figure(figsize=(8, 5))

lab02/optimized.cpp

@@ -0,0 +1,34 @@
+#include "matrix.h"
+#include <cmath>
+int fib(int n)
+{
+    if (n < 2)
+        return n;
+
+    int a = 0;
+    int b = 1;
+
+    for (int i = 2; i <= n; ++i)
+    {
+        int temp = a + b;
+        a = b;
+        b = temp;
+    }
+
+    return b;
+}
+
+Matrix compute(const Matrix &s, const std::vector<int> &v)
+{
+    Matrix m(s.dim());
+    const int n = v.size();
+    for (int j = 0; j < n; ++j)
+    {
+        for (int i = 0; i < n; ++i)
+        {
+            double val = static_cast<double>(fib(v[j] % 256));
+            m(j, i) = s(j, i) * (sin(val) * tan(val) / sqrt(cos(val) + 2));
+        }
+    }
+    return m;
+}

lab02/triad_bench.cpp

@@ -2,6 +2,8 @@
 #include <vector>
 #include <iostream>
 #include <fstream> 
+#include <sstream>
+#include <thread>
 
 std::vector<double> B(1000000, 1);
 std::vector<double> C(1000000, 2);
@@ -9,12 +11,11 @@ std::vector<double> D(1000000, 3);
 
 static double ownMethod(int n) {
   std::vector<double> A(n, 0);
-  
   std::chrono::duration<double, std::milli> sumTime;
   for (int i = 0; i < 20; ++i) {
     auto startTime = std::chrono::system_clock::now();
-    for (int i = 0; i < n; ++i) {
-      A[i] = B[i] + C[i] * D[i];
+    for (int j = 0; j < n; ++j) {
+      A[j] = B[j] + C[j] * D[j];
     }
     // prevent the compiler from optimizing everything away
     volatile double dummy = A[0];
@@ -25,14 +26,39 @@ static double ownMethod(int n) {
   return averageTime;
 }
 
-int main() {
+static void workerThread(int start, int end) {
   std::vector<double> outcomes;
-  for (int i = 100; i < 1000000; i+=10) {
+  for (int i = start; i < end; i+=10) {
     outcomes.push_back(ownMethod(i));
   }
-  std::ofstream MyFile("outcomes.csv");
+  std::stringstream fileName;
+  fileName << "outcomes-" << start << "-" << end << ".csv";
+  std::ofstream MyFile(fileName.str());
   for (int j = 0; j < outcomes.size(); j++) {
     MyFile << outcomes[j] << ",";
   }
   MyFile.close();
+}
+
+int main() {
+  int range_start = 100;
+  int range_end = 1'000'000;
+  int num_threads = std::thread::hardware_concurrency(); // use system's core count
+
+  int total = range_end - range_start;
+  int chunk_size = total / num_threads;
+
+  std::vector<std::thread> threads;
+
+  for (int i = 0; i < num_threads; ++i) {
+      int start = range_start + i * chunk_size;
+      int end = (i == num_threads - 1) ? range_end : start + chunk_size;
+
+      threads.emplace_back(workerThread, start, end);
+  }
+
+  for (auto& t : threads) t.join();
+
+  std::cout << "All threads finished.\n";
+  return 0;
 }