"Ferdig" med øving 2

lab_2/11/memleak.cpp

@@ -49,7 +49,7 @@ int main(int argc, char** argv)
       // Simple fix to memleak:
       float* old_configuration = present_configuration;
       present_configuration = crw::step(size, present_configuration);
-      delete old_configuration;
+      delete[] old_configuration;
       float present_elongation = crw::elongation(size, present_configuration);
 
       if(present_elongation > extreme_elongation)

lab_2/12/Makefile

@@ -6,7 +6,7 @@ run: $(binary)
 	./$(binary) 7 100000000
 
 $(binary): $(objects)
-	g++ -o $@ $^
+	g++ -Ofast -march=native -flto -fno-signed-zeros -fno-trapping-math -o $@ $^
 
 clean:
 	rm -f *.o

lab_2/13/Makefile

@@ -6,7 +6,7 @@ run: $(binary)
 	./$(binary) 7 100000000
 
 $(binary): $(objects)
-	g++ -o $@ $^
+	g++ -Ofast -march=native -flto -fno-signed-zeros -fno-trapping-math -o $@ $^
 
 clean:
 	rm -f *.o

lab_2/13/memleak.cpp

@@ -1,6 +1,7 @@
 #include <cassert>
 #include <cstdlib>
 #include <ctime>
+#include <fstream>
 
 #include "chain-random-walk.h"
 
@@ -62,5 +63,10 @@ int main(int argc, char** argv)
    }
    crw::output(steps, size, present_configuration, extreme_configuration, el_avg);
    
+   std::ofstream myfile;
+   myfile.open ("elongation.csv", std::ios::app);
+   myfile << size  << ", "  << el_avg << ", "  << crw::elongation(size, extreme_configuration) << "\n";
+   myfile.close();
+   
    delete[] present_configuration;
 }

lab_2/13/plot_elongation.py

@@ -0,0 +1,30 @@
+import matplotlib.pyplot as plt
+import matplotlib.cbook as cbook
+
+import numpy as np
+import pandas as pd
+
+f = open('elongation.csv', 'r')
+x = []
+y_average = []
+y_extreme = []
+for l in f.readlines():
+    l = l.split(',')
+    x.append(l[0])
+    y_average.append(float(l[1]))
+    y_extreme.append(float(l[2]))
+
+plt.plot(x, y_average, label = 'average')
+plt.plot(x, y_extreme, label = 'extreme')
+
+for i in range(len(x)):
+        plt.text(i,y_average[i],f'{y_average[i]:.2f}', color="blue")
+for i in range(len(x)):
+        plt.text(i,y_extreme[i],f'{y_extreme[i]:.2f}', color="orange")
+
+plt.title('Speedup after optimization')
+plt.xlabel('N')
+plt.ylabel('elongation')
+plt.grid()
+plt.legend()
+plt.show()

lab_2/15.cpp

@@ -0,0 +1,23 @@
+#include <vector>
+#include <chrono>
+#include <fstream>
+#include <iostream>
+int main()
+{
+    auto t0 = std::chrono::high_resolution_clock::now();
+    //std::ofstream myfile;
+    
+    std::vector<int> list;
+    int data = 1024;
+    int n = 0;
+    while (true) {
+        n++;
+        list.push_back(data);
+        auto t1 = std::chrono::high_resolution_clock::now();
+        auto delta_t = std::chrono::duration_cast<std::chrono::microseconds>(t1-t0).count();
+        //myfile.open("15cpp.csv", std::ios::trunc);
+        //myfile << n << ", " << delta_t << "\n";
+        //myfile.close();
+        std::cout << n << ", " << delta_t << "\n";
+    }
+}

lab_2/15.py

@@ -0,0 +1,11 @@
+import time
+
+start = time.time()
+f = open('15py.csv', 'w')
+n = 0
+list = []
+while True:
+    list.append(1024)
+    n += 1
+    end = time.time()
+    f.write(f'{n}, {end-start}')