diff --git a/Lab04/HPC-Lab-04.pdf b/Lab04/HPC-Lab-04.pdf
index 0dc215f..2380976 100644
Binary files a/Lab04/HPC-Lab-04.pdf and b/Lab04/HPC-Lab-04.pdf differ
diff --git a/Lab04/lab04.zip b/Lab04/lab04.zip
new file mode 100644
index 0000000..6fb5f5c
Binary files /dev/null and b/Lab04/lab04.zip differ
diff --git a/Lab04/plot.py b/Lab04/plot.py
new file mode 100644
index 0000000..7728542
--- /dev/null
+++ b/Lab04/plot.py
@@ -0,0 +1,58 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+count_threads = [1, 2, 3, 4, 6, 8, 12, 16, 24, 32, 48, 64]
+average_flops = []
+average_runtimes = []
+for i in range(0, 12):
+    avg_flops = 0
+    avg_runtime = 0
+    with open(f"./stats/stats{i}.csv", 'r') as file:
+        line = file.read()
+        stats = line.split(";")
+        for stat in stats:
+            splited = stat.split(",")
+            if len(splited) == 2:
+                avg_flops += float(splited[0])
+                avg_runtime += float(splited[1])
+    average_flops.append(avg_flops / 1000)
+    if i > 0:
+        average_runtimes.append(average_runtimes[0]/avg_runtime)
+    else:
+        average_runtimes.append(1)
+
+
+efficiencies = []
+
+for j in range(0, 12):
+    efficiencies.append(average_runtimes[j] / count_threads[j] * 100) 
+    
+# First plot: FLOPs vs Threads
+plt.figure(figsize=(10, 4))
+plt.plot(count_threads, average_flops, marker='o')
+plt.title("Average FLOPs vs Number of Threads")
+plt.xlabel("Number of Threads")
+plt.ylabel("Average FLOPs")
+plt.grid(True)
+plt.tight_layout()
+plt.show()
+
+# Second plot: Runtime vs Threads
+plt.figure(figsize=(10, 4))
+plt.plot(count_threads, average_runtimes, marker='o', color='orange')
+plt.title("Speedup")
+plt.xlabel("Number of Threads")
+plt.ylabel("Factor in %")
+plt.grid(True)
+plt.tight_layout()
+plt.show()
+
+# Second plot: Runtime vs Threads
+plt.figure(figsize=(10, 4))
+plt.plot(count_threads, efficiencies, marker='o', color='red')
+plt.title("Efficiency")
+plt.xlabel("Number of Threads")
+plt.ylabel("Speedup per Number of Threads (/count)")
+plt.grid(True)
+plt.tight_layout()
+plt.show()  
\ No newline at end of file
diff --git a/Lab04/triad_bench_2.cpp b/Lab04/triad_bench_2.cpp
index dde6032..79d0a2b 100644
--- a/Lab04/triad_bench_2.cpp
+++ b/Lab04/triad_bench_2.cpp
@@ -26,7 +26,7 @@ void ownMethod(std::vector<double>& A, int start, int end) {
 
 void workerThread(std::vector<double>& A, int start, int end, int threadCount, Statistics& stat) {
   
-  std::chrono::duration<double, std::milli> sumTime;
+  std::chrono::duration<double, std::nano> sumTime;
   for (int i = 0; i < 20; i++) {
     auto startTime = std::chrono::system_clock::now();
     ownMethod(A, start, end);
@@ -35,7 +35,7 @@ void workerThread(std::vector<double>& A, int start, int end, int threadCount, S
   }
   
   stat.avg_time = sumTime.count() / 20;
-  stat.flops = (2.0 * N) / (stat.avg_time  / 1000);
+  stat.flops = (2.0 * N) / (stat.avg_time  / 1000000);
 }
 
 int main() {
@@ -56,22 +56,23 @@ int main() {
       int start = N / countThreads[j] * i;
       int end = N / countThreads[j] * (i + 1);
 
-      threads.emplace_back(workerThread, std::ref(A), start, end, countThreads[j], std::ref(stats[j]));
+      threads.emplace_back(workerThread, std::ref(A), start, end, countThreads[j], std::ref(stats[i]));
     }
 
     for (auto& t : threads) {
       t.join();
     }
 
-    std::cout << A[1179647];
+    //std::cout << A[1179647];
     volatile std::vector<double> dummy(A);
 
-    // std::stringstream fileName;
-    // fileName << "outcomes-" << start << "-" << end << ".csv";
-    // std::ofstream MyFile(fileName.str());
-  
-    // MyFile << "(" << averageTime << "" << flops << ")";
-    // MyFile.close();
+    std::stringstream fileName;
+    fileName << "stats" << j << ".csv";
+    std::ofstream MyFile(fileName.str());
+    for (auto entry : stats) {
+      MyFile << entry.avg_time << "," << entry.flops << ";";
+    }
+    MyFile.close();
 
     std::cout << "All threads finished.\n";
   }