benchmarking distribution #6 Adds real uniform distribution benchmark…

…s, removes error when plotting

benchmark/distributions/CMakeLists.txt

@@ -25,7 +25,7 @@
 cmake_minimum_required(VERSION 3.10) # Adjust this to your actual CMake version
 
 # Add an executable target called 'uniform' to be built from 'uniform.cpp'
-add_executable(uniform uniform.cpp)
+add_executable(uniform uniform_int.cpp uniform_real.cpp)
 
 # Include directories for the 'uniform' target
 target_include_directories(uniform PRIVATE

benchmark/distributions/README.md

@@ -26,8 +26,9 @@ cd distributions
 chmod +x runbenchmark.sh
 ./runbenchmark.sh
 ```
+And then either type `uniform_int` or `uniform_real` when asked to choose the distribution to benchmark.
 
-After running this, the benchmarks can be found in the benchmark/distributions directory next to the scripts. The benchmarks are composed of two files, comparison.csv containing the results of the benchmarks and comparison.png containing the plots of the benchmarks in ascending order of execution time.
+After running this, the benchmarks can be found in the benchmark/distributions directory next to the scripts. The benchmarks are composed of two files, `uniform_int.csv` (or `uniform_real.csv`) containing the results of the benchmarks and `uniform_int.png` (or `uniform_real.png`) containing the plots of the benchmarks in ascending order of execution time.
 
 
 After each execution, the results are saved in these two files, but if you want to rerun the benchmark, you will have to respond 'Y' to the question 'Do you want to erase the previous results ?' in the script.

benchmark/distributions/plotresults.py

@@ -1,8 +1,18 @@
+import argparse
 import pandas as pd
 import matplotlib.pyplot as plt
+import os
+
+# Parse command-line arguments
+parser = argparse.ArgumentParser()
+parser.add_argument('csv_file', help='Name of the CSV file')
+args = parser.parse_args()
+
+# Read the CSV file
+data = pd.read_csv(args.csv_file)
+
+file_name = os.path.splitext(args.csv_file)[0]
 
-# read the csv file
-data = pd.read_csv('/home/u4/csmi/2022/devora/solar-shading/benchmark/distributions/comparison.csv')
 
 # plot the method
 plt.figure(figsize=(20,12))
@@ -42,5 +52,5 @@
 plt.xticks(rotation=45, ha='right', fontsize=8)
 
 plt.tight_layout()
-plt.savefig('comparison.png')
+plt.savefig(file_name + '.png')
 plt.show()

benchmark/distributions/runbenchmark.sh

@@ -2,31 +2,39 @@
 
 set -e
 
+# Ask for the .cpp file name
+echo "Enter the name of the .cpp file (without the .cpp extension):"
+read cpp_file_name
+
 # Compiler flags array
 declare -a flagsArr=("-O1" "-O2" "-O3" "-Ofast" "-O1 -march=native" "-O2 -march=native" "-O3 -march=native" "-Ofast -march=native" "-O1 -march=native -funroll-loops" "-O2 -march=native -funroll-loops" "-O3 -march=native -funroll-loops" "-Ofast -march=native -funroll-loops" "-O1 -march=native -fdisable-tree-cunrolli" "-O2 -march=native -fdisable-tree-cunrolli" "-O3 -march=native -fdisable-tree-cunrolli" "-Ofast -march=native -fdisable-tree-cunrolli")
 
 # Loop through the array of flags
 for flag in "${flagsArr[@]}"
 do
     # Build the C++ code with the current flag
-    g++ -Wno-enum-compare $flag -o uniform uniform.cpp # -I/home/u4/csmi/2022/devora/intel/oneapi/mkl/2023.1.0/include -L/home/u4/csmi/2022/devora/intel/oneapi/mkl/2023.1.0/lib/intel64 -lmkl_intel_lp64 -lmkl_sequential -lmkl_core -lpthread -lm -ldl
+    g++ -Wno-enum-compare $flag -o $cpp_file_name $cpp_file_name.cpp
 
     # Execute the C++ code with the current flag as a command-line argument
-    ./uniform $flag
+    ./$cpp_file_name $flag
 
     # Remove the executable
-    rm uniform
+    rm $cpp_file_name
 done
 
-# Execute the Python script for plotting
-python3 plotresults.py
+# Determine the CSV file name based on the CPP file name
+csv_file_name="${cpp_file_name}.csv"
+
+# Execute the Python script for plotting, passing the CSV file name
+python3 plotresults.py "$csv_file_name"
+
 
 # Ask user for confirmation to delete all lines except the first one from the CSV file
 read -p "Do you want to delete all lines except the first one from the CSV file? [Y/n] " answer
 
 case $answer in
     [Yy]* )
-        sed -i '2,$d' comparison.csv
+        sed -i '2,$d' $csv_file_name
         echo "All lines except the first one from the CSV file have been deleted."
         ;;
     * )

benchmark/distributions/uniform.cpp → benchmark/distributions/uniform_int.cpp

@@ -44,7 +44,7 @@ int main(int argc, char *argv[]) {
 
 
     // Open the CSV file for writing
-    std::ofstream outputFile("comparison.csv", std::ofstream::app);
+    std::ofstream outputFile("uniform_int.csv", std::ofstream::app);
 
     //~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Parameters Initialization ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 

benchmark/distributions/uniform_int.csv

@@ -0,0 +1 @@
+Flag,Method,Duration

benchmark/distributions/uniform_real.cpp

@@ -0,0 +1,105 @@
+#include <iostream>
+#include <vector>
+#include <random>
+#include <chrono>
+#include <fstream>
+#include "../extlibs/EigenRand/EigenRand/EigenRand"
+#include "../extlibs/Xoshiro-cpp/XoshiroCpp.hpp"
+#include "../extlibs/pcg-cpp/include/pcg_random.hpp"
+#include "../extlibs/eigen/Eigen/Dense"
+#include "../extlibs/eigen/Eigen/Core"
+
+using namespace XoshiroCpp;
+
+int main(int argc, char *argv[]) {
+    std::string flag;
+    std::stringstream ss;
+
+    if (argc > 1) {
+        for(int i = 1; i < argc; ++i) {
+            if(i != 1) {
+                ss << " ";
+            }
+            ss << argv[i];
+        }
+
+        flag = ss.str();
+    }
+    else {
+        flag = "default";
+    }
+
+    std::ofstream outputFile("uniform_real.csv", std::ofstream::app);
+
+    const int numVectors = 100000000;
+
+    std::vector<double> stdVector(numVectors);
+    std::vector<double> mersenneVector(numVectors);
+    Eigen::VectorXd EigenVector(numVectors);
+    std::vector<double> pcgCppVector(numVectors);
+    std::vector<double> xoshiroCppVector(numVectors);
+    Eigen::VectorXd EigenVector2(numVectors);
+
+    auto startEigen = std::chrono::steady_clock::now();
+    Eigen::VectorXd eigenVector = Eigen::VectorXd::Random(numVectors).array() / 2.0 + 0.5; // Remap the Eigen random from [-1,1] to [0,1]
+    auto endEigen = std::chrono::steady_clock::now();
+    auto durationEigen = std::chrono::duration_cast<std::chrono::milliseconds>(endEigen - startEigen);
+    outputFile<< "\n" << flag << ",Eigen::VectorXd::Random,"<< durationEigen.count();
+
+    std::random_device rd;
+    std::mt19937 gen(rd());
+    std::uniform_real_distribution<double> dist(0.0, 1.0);
+
+    auto startStdUniform = std::chrono::steady_clock::now();
+    for (int i = 0; i < numVectors; ++i) {
+        stdVector[i] = dist(gen);
+    }
+    auto endStdUniform = std::chrono::steady_clock::now();
+    auto durationStdUniform = std::chrono::duration_cast<std::chrono::milliseconds>(endStdUniform - startStdUniform);
+    outputFile<< "\n" << flag << ",std::uniform_real_distribution," << durationStdUniform.count();
+
+    std::mt19937 mersenne(gen());
+    std::uniform_real_distribution<double> mersenneDist(0.0, 1.0);
+
+    auto startMersenne = std::chrono::steady_clock::now();
+    for (int i = 0; i < numVectors; ++i) {
+        mersenneVector[i] = mersenneDist(mersenne);
+    }
+    auto endMersenne = std::chrono::steady_clock::now();
+    auto durationMersenne = std::chrono::duration_cast<std::chrono::milliseconds>(endMersenne - startMersenne);
+    outputFile<< "\n" << flag << ",Mersenne Twister," << durationMersenne.count();
+
+    Eigen::Rand::Vmt19937_64 urng{ 42 };
+    auto startEigenRand = std::chrono::steady_clock::now();
+    EigenVector = Eigen::Rand::uniformRealLike(EigenVector, urng);
+    auto endEigenRand = std::chrono::steady_clock::now();
+    auto durationEigenRand = std::chrono::duration_cast<std::chrono::milliseconds>(endEigenRand - startEigenRand);
+    outputFile << "\n" << flag << ",EigenRand,"<< durationEigenRand.count();
+
+    pcg64_fast rng;  
+    rng.seed(42);  
+    std::uniform_real_distribution<double> pcgDist(0.0, 1.0); 
+
+    auto startPcgCpp = std::chrono::steady_clock::now();
+    for (int i = 0; i < numVectors; ++i) {
+        pcgCppVector[i] = pcgDist(rng);
+    }
+    auto endPcgCpp = std::chrono::steady_clock::now();
+    auto durationPcgCpp = std::chrono::duration_cast<std::chrono::milliseconds>(endPcgCpp - startPcgCpp);
+    outputFile << "\n" << flag << ",pcg-cpp," << durationPcgCpp.count();
+
+    const std::uint64_t seed = 12345;
+    Xoshiro256PlusPlus rg(seed);
+    std::uniform_real_distribution<double> DIST(0.0,1.0);
+
+    auto startXoshiroCpp = std::chrono::steady_clock::now();
+    for (int i = 0; i < numVectors; i++) {
+        xoshiroCppVector[i] =  DIST(rg);
+    }
+    auto endXoshiroCpp = std::chrono::steady_clock::now();
+    auto durationXoshiroCpp = std::chrono::duration_cast<std::chrono::milliseconds>(endXoshiroCpp - startXoshiroCpp);
+    outputFile << "\n" << flag << ",XoshiroCpp,"<< durationXoshiroCpp.count();
+    outputFile.close();
+
+    return 0;
+}

benchmark/distributions/uniform_real.csv

@@ -0,0 +1 @@
+Flag,Method,Duration

results/csv/results.csv

@@ -1 +1,25 @@
-RNG TYPE,EXECUTION TIME
+METHOD,TIME
+Shading mask STD RNG -Ofast -march=native,9.99015
+Shading mask PCG RNG -Ofast -march=native,8.34877
+Shading mask XOSHIRO RNG -Ofast -march=native,7.88745
+Shading mask MIX RNG -Ofast -march=native,9.741
+Shading mask STD RNG -Ofast -march=native,9.88132
+Shading mask PCG RNG -Ofast -march=native,9.80248
+Shading mask XOSHIRO RNG -Ofast -march=native,9.92391
+Shading mask MIX RNG -Ofast -march=native,10.1443
+Shading mask STD RNG -Ofast -march=native,10.9991
+Shading mask PCG RNG -Ofast -march=native,9.99749
+Shading mask XOSHIRO RNG -Ofast -march=native,9.81854
+Shading mask MIX RNG -Ofast -march=native,9.63068
+Shading mask STD RNG -Ofast -march=native,11.0136
+Shading mask PCG RNG -Ofast -march=native,10.4724
+Shading mask XOSHIRO RNG -Ofast -march=native,10.855
+Shading mask MIX RNG -Ofast -march=native,10.9804
+Shading mask STD RNG -Ofast -march=native -funroll-loops -funsafe-math-optimizations,11.7976
+Shading mask PCG RNG -Ofast -march=native -funroll-loops -funsafe-math-optimizations,10.2469
+Shading mask XOSHIRO RNG -Ofast -march=native -funroll-loops -funsafe-math-optimizations,9.38577
+Shading mask MIX RNG -Ofast -march=native -funroll-loops -funsafe-math-optimizations,10.0054
+Shading mask STD RNG -O3 -march=native,10.7028
+Shading mask PCG RNG -O3 -march=native,10.8316
+Shading mask XOSHIRO RNG -O3 -march=native,10.3154
+Shading mask MIX RNG -O3 -march=native,11.3336