diff --git a/(p,t)_sparsification/main.cpp b/(p,t)_sparsification/main.cpp
index ce3bc9d20300afda0857d880878610a693c7c174..b4b342b53125528fa344fa4d37473f1d63deb596 100644
--- a/(p,t)_sparsification/main.cpp
+++ b/(p,t)_sparsification/main.cpp
@@ -1,15 +1,15 @@
 #include <iostream>
-#include <chrono>
 #include "p_k_compression.h"
 #include <boost/program_options.hpp>
 #include "graph.h"
 #include "io.h"
-#include <sstream>
 #include <string>
-#include <fstream>
 #include "hash.h"
+#include <omp.h>
 
 
+#define NUM_TRIALS 10
+
 using  namespace std;
 namespace po = boost::program_options;
 
@@ -51,45 +51,59 @@ int main(int argc, char *argv[]) {
 
     vector<int> s ;
     vector<double> c ;
-    // perform 30 experiments
-    for (int i =0; i<30;i++) {
-        cout << i << endl;
-        string file_name = var["input"].as<string>() + to_string(i) + ".txt";
-        double compression_rate = 0;
-        auto[g, e_s] = read_graph_from_file(file_name, var["directed"].as<bool>());
-        auto start = chrono::steady_clock::now();
-
-        if (var["algorithm"].as<string>() == "Random") {
-            g2 = compress_graph_basic(g, var["depth"].as<int>(), var["proportions"].as<vector<double>>(),
+    int edges_compressed = 0;
+
+    string file_name = var["input"].as<string>();
+
+    double compression_rate = 0;
+    double elapsed_time = 0;
+
+    auto[g, e_s] = read_graph_from_file(file_name, var["directed"].as<bool>());
+    auto start = chrono::steady_clock::now();
+
+    string execMode=var["algorithm"].as<string>();
+
+
+
+
+    #pragma omp parallel for  num_threads(NUM_TRIALS)
+    for (int i = 0; i < NUM_TRIALS; i++) {
+
+        auto start = std::chrono::steady_clock::now();
+
+        if (execMode == "Random") {
+            g2 = compress_graph_basic(g, var["depth"].as<int>(), var["proportions"].as<std::vector<double>>(),
                                       var["directed"].as<bool>());
 
-        } else if (var["algorithm"].as<string>() == "LP") {
-            g2 = compress_graph_LP(g, e_s, var["depth"].as<int>(), var["proportions"].as<vector<double>>(),
-                                var["directed"].as<bool>());
+        } else if (execMode == "LP") {
+            g2 = compress_graph_LP(g, e_s, var["depth"].as<int>(), var["proportions"].as<std::vector<double>>(),
+                                   var["directed"].as<bool>());
 
-        } else if (var["algorithm"].as<string>() == "SA") {
+        } else if (execMode == "SA") {
             g2 = Simulated_annealing(1000, 10, 0.99, g, var["directed"].as<bool>(), var["depth"].as<int>(),
-                                     var["proportions"].as<vector<double>>());
-        }else if (var["algorithm"].as<string>() == "Greedy") {
-            g2 = compress_graph_greedy(g, var["depth"].as<int>(), var["proportions"].as<vector<double>>(),
-                                      var["directed"].as<bool>());
+                                     var["proportions"].as<std::vector<double>>());
+        } else if (execMode == "Greedy") {
+            g2 = compress_graph_greedy(g, var["depth"].as<int>(), var["proportions"].as<std::vector<double>>(),
+                                       var["directed"].as<bool>());
+
+        }
+
+        auto finish = std::chrono::steady_clock::now();
 
+        // Update edges_compressed and elapsed_time in a thread-safe manner
+        #pragma omp critical
+        {
+            vector<edge> edges_original = get_edges(g, var["directed"].as<bool>());
+            edges_compressed += get_edges(g2, var["directed"].as<bool>()).size();
+            elapsed_time += std::chrono::duration_cast<std::chrono::duration<double>>(finish - start).count();
         }
 
-        auto finish = chrono::steady_clock::now();
-        vector<edge> edges_original = get_edges(g, var["directed"].as<bool>());
-        vector<edge> edges_compressed = get_edges(g2, var["directed"].as<bool>());
-
-        double elapsed_time = chrono::duration_cast<chrono::duration<double>>(finish - start).count();
-        compression_rate = ((double) (edges_original.size() - edges_compressed.size()) /
-                            edges_original.size());
-         c.push_back(compression_rate);
-         s.push_back(edges_compressed.size());
-        //graph_to_file(var, elapsed_time, compression_rate, edges_compressed);
-        cout << "compression time " << elapsed_time << endl;
-        cout << "compression rate " << compression_rate << endl;
     }
-    for (int i = 0 ; i<30;i++) cout << c.at(i) << '\t' << s.at(i) << endl;
 
-    return 0;
+
+//    graph_to_file(var, elapsed_time, compression_rate, edges_compressed);
+//    cout << "compression rate: " << compression_rate << endl;
+    cout <<endl << "compression time: " << elapsed_time/NUM_TRIALS << endl;
+    cout << "Average of compressed edges: " << edges_compressed/NUM_TRIALS;
+
 }
diff --git a/README.md b/README.md
index b33d853617035d2c1e8363dd1b0f1d9c4ceda13c..751af029527bab671ca841d41cfa56133593256f 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@ ptSpar is a C++ program implementing a Neighborhood-Preserving Graph Sparsificat
 
 ## Compilation
 1. **Install Boost Library:** Ensure the Boost Program Options library is installed on your system.
-2. **Compilation Command:** In the source directory, compile using `g++ -std=c++11 main.c++ -o ptSpar -lboost_program_options`.
+2. **Compilation Command:** In the source directory, compile using `g++ -std=c++11 main.cpp -o ptSpar -lboost_program_options`.
 
 ## Usage
 - **Basic Command Structure:**