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fix: reverted local profiling_openmp.cpp to commit 1dbee6d8, small updates in index.rst

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Marco De Lucia 2023-08-27 13:56:44 +02:00
parent 6363585a00
commit 2d50f32e37
2 changed files with 49 additions and 35 deletions
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3
docs_sphinx/index.rst
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@ -10,8 +10,9 @@ Welcome to the documentation of the TUG project, a simulation program
for solving transport equations in one- and two-dimensional uniform for solving transport equations in one- and two-dimensional uniform
grids using cell centered finite differences. grids using cell centered finite differences.
---------
Diffusion Diffusion
----------- ---------
TUG can solve diffusion problems with heterogeneous and anisotropic TUG can solve diffusion problems with heterogeneous and anisotropic
diffusion coefficients. The partial differential equation expressing diffusion coefficients. The partial differential equation expressing

81
examples/profiling_openmp.cpp
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@ -2,47 +2,60 @@
#include <iostream> #include <iostream>
#include <fstream> #include <fstream>
#include <chrono> #include <chrono>
#include <easy/profiler.h>
int main(int argc, char *argv[]) { int main(int argc, char *argv[]) {
EASY_MAIN_THREAD;
EASY_PROFILER_ENABLE;
profiler::startListen();
int n = 1000; int n[4] = {100, 500, 1000, 2000};
int threads[10] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10};
int iterations[1] = {5};
int repetition = 1;
Grid grid = Grid(n, n); ofstream myfile;
grid.setDomain(10, 10); myfile.open("testLarge.csv");
MatrixXd concentrations = MatrixXd::Constant(n, n, 0); for (int i = 0; i < size(n); i++){
concentrations(n/2,n/2) = 1; cout << "Grid size: " << n[i] << " x " << n[i] << endl << endl;
grid.setConcentrations(concentrations); myfile << "Grid size: " << n[i] << " x " << n[i] << endl << endl;
MatrixXd alpha = MatrixXd::Constant(n, n, 0.001); for(int j = 0; j < size(iterations); j++){
cout << "Iterations: " << iterations[j] << endl;
Boundary bc = Boundary(grid); myfile << "Iterations: " << iterations[j] << endl;
for (int k = 0; k < repetition; k++){
Simulation sim = Simulation(grid, bc, BTCS_APPROACH); cout << "Wiederholung: " << k << endl;
sim.setSolver(THOMAS_ALGORITHM_SOLVER); Grid grid = Grid(n[i], n[i]);
sim.setNumberThreads(1); grid.setDomain(1, 1);
sim.setTimestep(0.001);
sim.setIterations(2);
sim.setOutputCSV(CSV_OUTPUT_OFF);
auto begin = std::chrono::high_resolution_clock::now();
EASY_BLOCK("SIMULATION"); MatrixXd concentrations = MatrixXd::Constant(n[i], n[i], 0);
sim.run(); concentrations(n[i]/2,n[i]/2) = 1;
EASY_END_BLOCK; grid.setConcentrations(concentrations);
MatrixXd alpha = MatrixXd::Constant(n[i], n[i], 0.5);
auto end = std::chrono::high_resolution_clock::now(); Boundary bc = Boundary(grid);
auto milliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(end - begin); Simulation sim = Simulation(grid, bc, BTCS_APPROACH);
cout << milliseconds.count() << endl; sim.setSolver(THOMAS_ALGORITHM_SOLVER);
profiler::dumpBlocksToFile("./mytest_profile.prof"); if(argc == 2){
profiler::stopListen(); int numThreads = atoi(argv[1]);
sim.setNumberThreads(numThreads);
}
else{
sim.setNumberThreads(1);
}
return(0); sim.setTimestep(0.001);
} sim.setIterations(iterations[j]);
sim.setOutputCSV(CSV_OUTPUT_OFF);
auto begin = std::chrono::high_resolution_clock::now();
sim.run();
auto end = std::chrono::high_resolution_clock::now();
auto milliseconds = std::chrono::duration_cast<std::chrono::milliseconds>(end - begin);
myfile << milliseconds.count() << endl;
}
}
cout << endl;
myfile << endl;
}
myfile.close();
}