uct full
This commit is contained in:
James E McClure
parent
7738ebced1
commit
c7d0d40c4b
@ -35,49 +35,49 @@ int main(int argc, char **argv)
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MPI_Comm comm = MPI_COMM_WORLD;
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MPI_Comm_rank(comm,&rank);
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MPI_Comm_size(comm,&nprocs);
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Utilities::setErrorHandlers();
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Utilities::setErrorHandlers();
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PROFILE_START("Main");
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//std::vector<std::string> filenames;
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if ( argc<2 ) {
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if ( rank == 0 ){
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printf("At least one filename must be specified\n");
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}
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if ( rank == 0 ){
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printf("At least one filename must be specified\n");
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}
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return 1;
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}
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std::string filename = std::string(argv[1]);
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if ( rank == 0 ){
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if ( rank == 0 ){
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printf("Input data file: %s\n",filename.c_str());
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}
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auto db = std::make_shared<Database>( filename );
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auto domain_db = db->getDatabase( "Domain" );
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auto uct_db = db->getDatabase( "uCT" );
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auto analysis_db = db->getDatabase( "Analysis" );
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// Read domain values
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auto L = domain_db->getVector<double>( "L" );
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auto size = domain_db->getVector<int>( "n" );
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auto nproc = domain_db->getVector<int>( "nproc" );
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int BoundaryCondition = domain_db->getScalar<int>( "BC" );
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int nx = size[0];
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int ny = size[1];
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int nz = size[2];
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double Lx = L[0];
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double Ly = L[1];
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double Lz = L[2];
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int nprocx = nproc[0];
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int nprocy = nproc[1];
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int nprocz = nproc[2];
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auto InputFile=uct_db->getScalar<std::string>( "InputFile" );
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}
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auto db = std::make_shared<Database>( filename );
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auto domain_db = db->getDatabase( "Domain" );
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auto uct_db = db->getDatabase( "uCT" );
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auto analysis_db = db->getDatabase( "Analysis" );
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// Read domain values
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auto L = domain_db->getVector<double>( "L" );
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auto size = domain_db->getVector<int>( "n" );
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auto nproc = domain_db->getVector<int>( "nproc" );
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int BoundaryCondition = domain_db->getScalar<int>( "BC" );
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int nx = size[0];
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int ny = size[1];
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int nz = size[2];
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double Lx = L[0];
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double Ly = L[1];
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double Lz = L[2];
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int nprocx = nproc[0];
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int nprocy = nproc[1];
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int nprocz = nproc[2];
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auto InputFile=uct_db->getScalar<std::string>( "InputFile" );
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//.......................................................................
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// Reading the domain information file
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//.......................................................................
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// std::shared_ptr<Domain> Dm ();
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//for (int i=0; i<Dm->Nx*Dm->Ny*Dm->Nz; i++) Dm->id[i] = 1;
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//Dm->CommInit();
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// std::shared_ptr<Domain> Dm ();
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//for (int i=0; i<Dm->Nx*Dm->Ny*Dm->Nz; i++) Dm->id[i] = 1;
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//Dm->CommInit();
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// Check that the number of processors >= the number of ranks
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if ( rank==0 ) {
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@ -89,93 +89,93 @@ int main(int argc, char **argv)
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ERROR("Insufficient number of processors");
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}
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// Determine the maximum number of levels for the desired coarsen ratio
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int ratio[3] = {2,2,2};
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//std::vector<size_t> ratio = {4,4,4};
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std::vector<int> Nx(1,nx), Ny(1,ny), Nz(1,nz);
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while ( Nx.back()%ratio[0]==0 && Nx.back()>8 &&
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Ny.back()%ratio[1]==0 && Ny.back()>8 &&
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Nz.back()%ratio[2]==0 && Nz.back()>8 )
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{
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Nx.push_back( Nx.back()/ratio[0] );
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Ny.push_back( Ny.back()/ratio[1] );
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Nz.push_back( Nz.back()/ratio[2] );
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}
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int N_levels = Nx.size();
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// Determine the maximum number of levels for the desired coarsen ratio
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int ratio[3] = {2,2,2};
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//std::vector<size_t> ratio = {4,4,4};
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std::vector<int> Nx(1,nx), Ny(1,ny), Nz(1,nz);
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while ( Nx.back()%ratio[0]==0 && Nx.back()>8 &&
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Ny.back()%ratio[1]==0 && Ny.back()>8 &&
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Nz.back()%ratio[2]==0 && Nz.back()>8 )
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{
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Nx.push_back( Nx.back()/ratio[0] );
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Ny.push_back( Ny.back()/ratio[1] );
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Nz.push_back( Nz.back()/ratio[2] );
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}
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int N_levels = Nx.size();
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// Initialize the domain
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std::vector<std::shared_ptr<Domain>> Dm(N_levels);
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for (int i=0; i<N_levels; i++) {
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Dm[i].reset( new Domain(domain_db, comm) );
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int N = (Nx[i]+2)*(Ny[i]+2)*(Nz[i]+2);
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for (int n=0; n<N; n++){
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Dm[i]->id[n] = 1;
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}
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Dm[i]->CommInit();
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}
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// Initialize the domain
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std::vector<std::shared_ptr<Domain>> Dm(N_levels);
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for (int i=0; i<N_levels; i++) {
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Dm[i].reset( new Domain(domain_db, comm) );
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int N = (Nx[i]+2)*(Ny[i]+2)*(Nz[i]+2);
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for (int n=0; n<N; n++){
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Dm[i]->id[n] = 1;
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}
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Dm[i]->CommInit();
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}
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// array containing a distance mask
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Array<float> MASK(Nx[0]+2,Ny[0]+2,Nz[0]+2);
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// Create the level data
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std::vector<Array<char>> ID(N_levels);
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std::vector<Array<float>> LOCVOL(N_levels);
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std::vector<Array<float>> Dist(N_levels);
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std::vector<Array<float>> MultiScaleSmooth(N_levels);
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std::vector<Array<float>> Mean(N_levels);
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std::vector<Array<float>> NonLocalMean(N_levels);
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// array containing a distance mask
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Array<float> MASK(Nx[0]+2,Ny[0]+2,Nz[0]+2);
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// Create the level data
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std::vector<Array<char>> ID(N_levels);
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std::vector<Array<float>> LOCVOL(N_levels);
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std::vector<Array<float>> Dist(N_levels);
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std::vector<Array<float>> MultiScaleSmooth(N_levels);
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std::vector<Array<float>> Mean(N_levels);
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std::vector<Array<float>> NonLocalMean(N_levels);
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std::vector<std::shared_ptr<fillHalo<double>>> fillDouble(N_levels);
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std::vector<std::shared_ptr<fillHalo<float>>> fillFloat(N_levels);
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std::vector<std::shared_ptr<fillHalo<char>>> fillChar(N_levels);
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for (int i=0; i<N_levels; i++) {
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ID[i] = Array<char>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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LOCVOL[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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Dist[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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MultiScaleSmooth[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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Mean[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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NonLocalMean[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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ID[i].fill(0);
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LOCVOL[i].fill(0);
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Dist[i].fill(0);
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MultiScaleSmooth[i].fill(0);
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Mean[i].fill(0);
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NonLocalMean[i].fill(0);
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fillDouble[i].reset(new fillHalo<double>(Dm[i]->Comm,Dm[i]->rank_info,{Nx[i],Ny[i],Nz[i]},{1,1,1},0,1) );
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fillFloat[i].reset(new fillHalo<float>(Dm[i]->Comm,Dm[i]->rank_info,{Nx[i],Ny[i],Nz[i]},{1,1,1},0,1) );
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fillChar[i].reset(new fillHalo<char>(Dm[i]->Comm,Dm[i]->rank_info,{Nx[i],Ny[i],Nz[i]},{1,1,1},0,1) );
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for (int i=0; i<N_levels; i++) {
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ID[i] = Array<char>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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LOCVOL[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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Dist[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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MultiScaleSmooth[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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Mean[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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NonLocalMean[i] = Array<float>(Nx[i]+2,Ny[i]+2,Nz[i]+2);
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ID[i].fill(0);
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LOCVOL[i].fill(0);
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Dist[i].fill(0);
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MultiScaleSmooth[i].fill(0);
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Mean[i].fill(0);
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NonLocalMean[i].fill(0);
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fillDouble[i].reset(new fillHalo<double>(Dm[i]->Comm,Dm[i]->rank_info,{Nx[i],Ny[i],Nz[i]},{1,1,1},0,1) );
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fillFloat[i].reset(new fillHalo<float>(Dm[i]->Comm,Dm[i]->rank_info,{Nx[i],Ny[i],Nz[i]},{1,1,1},0,1) );
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fillChar[i].reset(new fillHalo<char>(Dm[i]->Comm,Dm[i]->rank_info,{Nx[i],Ny[i],Nz[i]},{1,1,1},0,1) );
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}
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// Read the subvolume of interest on each processor
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// Read the subvolume of interest on each processor
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PROFILE_START("ReadVolume");
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int fid = netcdf::open(InputFile,netcdf::READ);
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std::string varname("VOLUME");
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netcdf::VariableType type = netcdf::getVarType( fid, varname );
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std::vector<size_t> dim = netcdf::getVarDim( fid, varname );
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if ( rank == 0 ) {
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printf("Reading %s (%s)\n",varname.c_str(),netcdf::VariableTypeName(type).c_str());
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printf(" dims = %i x %i x %i \n",int(dim[0]),int(dim[1]),int(dim[2]));
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}
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{
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RankInfoStruct info( rank, nprocx, nprocy, nprocz );
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int x = info.ix*nx;
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int y = info.jy*ny;
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int z = info.kz*nz;
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// Read the local data
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int fid = netcdf::open(InputFile,netcdf::READ);
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std::string varname("VOLUME");
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netcdf::VariableType type = netcdf::getVarType( fid, varname );
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std::vector<size_t> dim = netcdf::getVarDim( fid, varname );
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if ( rank == 0 ) {
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printf("Reading %s (%s)\n",varname.c_str(),netcdf::VariableTypeName(type).c_str());
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printf(" dims = %i x %i x %i \n",int(dim[0]),int(dim[1]),int(dim[2]));
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}
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{
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RankInfoStruct info( rank, nprocx, nprocy, nprocz );
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int x = info.ix*nx;
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int y = info.jy*ny;
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int z = info.kz*nz;
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// Read the local data
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Array<short> VOLUME = netcdf::getVar<short>( fid, varname, {x,y,z}, {nx,ny,nz}, {1,1,1} );
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// Copy the data and fill the halos
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LOCVOL[0].fill(0);
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fillFloat[0]->copy( VOLUME, LOCVOL[0] );
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fillFloat[0]->fill( LOCVOL[0] );
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}
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netcdf::close( fid );
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// Copy the data and fill the halos
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LOCVOL[0].fill(0);
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fillFloat[0]->copy( VOLUME, LOCVOL[0] );
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fillFloat[0]->fill( LOCVOL[0] );
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}
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netcdf::close( fid );
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MPI_Barrier(comm);
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PROFILE_STOP("ReadVolume");
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if (rank==0) printf("Read complete\n");
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// Filter the original data
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filter_src( *Dm[0], LOCVOL[0] );
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// Filter the original data
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filter_src( *Dm[0], LOCVOL[0] );
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// Set up the mask to be distance to cylinder (crop outside cylinder)
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float CylRad=900;
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for (int k=0;k<Nz[0]+2;k++) {
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@ -184,18 +184,18 @@ int main(int argc, char **argv)
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int iproc = Dm[0]->iproc();
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int jproc = Dm[0]->jproc();
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int kproc = Dm[0]->kproc();
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int x=iproc*Nx[0]+i-1;
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int y=jproc*Ny[0]+j-1;
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int z=kproc*Nz[0]+k-1;
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int cx = 0.5*nprocx*Nx[0];
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int cy = 0.5*nprocy*Ny[0];
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int cz = 0.5*nprocz*Nz[0];
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// distance from the center line
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MASK(i,j,k) = CylRad - sqrt(float((z-cz)*(z-cz) + (y-cy)*(y-cy)) );
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}
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}
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}
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@ -223,81 +223,89 @@ int main(int argc, char **argv)
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}
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}
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}
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mean_plus = sumReduce( Dm[0]->Comm, mean_plus ) / sumReduce( Dm[0]->Comm, count_plus );
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mean_minus = sumReduce( Dm[0]->Comm, mean_minus ) / sumReduce( Dm[0]->Comm, count_minus );
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mean_plus = sumReduce( Dm[0]->Comm, mean_plus ) / sumReduce( Dm[0]->Comm, count_plus );
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mean_minus = sumReduce( Dm[0]->Comm, mean_minus ) / sumReduce( Dm[0]->Comm, count_minus );
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if (rank==0) printf(" Region 1 mean (+): %f, Region 2 mean (-): %f \n",mean_plus, mean_minus);
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MPI_Barrier(comm);
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// Scale the source data to +-1.0
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for (size_t i=0; i<LOCVOL[0].length(); i++) {
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if (MASK(i) < 0.f){
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LOCVOL[0](i) = 1.0;
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}
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else if ( LOCVOL[0](i) >= 0 ) {
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LOCVOL[0](i) /= mean_plus;
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LOCVOL[0](i) = std::min( LOCVOL[0](i), 1.0f );
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} else {
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LOCVOL[0](i) /= -mean_minus;
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LOCVOL[0](i) = std::max( LOCVOL[0](i), -1.0f );
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}
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}
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// Scale the source data to +-1.0
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for (size_t i=0; i<LOCVOL[0].length(); i++) {
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if (MASK(i) < 0.f){
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LOCVOL[0](i) = 1.0;
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}
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else if ( LOCVOL[0](i) >= 0 ) {
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LOCVOL[0](i) /= mean_plus;
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LOCVOL[0](i) = std::min( LOCVOL[0](i), 1.0f );
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} else {
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LOCVOL[0](i) /= -mean_minus;
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LOCVOL[0](i) = std::max( LOCVOL[0](i), -1.0f );
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}
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}
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// Fill the source data for the coarse meshes
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PROFILE_START("CoarsenMesh");
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for (int i=1; i<N_levels; i++) {
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Array<float> filter(ratio[0],ratio[1],ratio[2]);
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filter.fill(1.0f/filter.length());
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Array<float> tmp(Nx[i-1],Ny[i-1],Nz[i-1]);
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fillFloat[i-1]->copy( LOCVOL[i-1], tmp );
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Array<float> coarse = tmp.coarsen( filter );
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fillFloat[i]->copy( coarse, LOCVOL[i] );
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fillFloat[i]->fill( LOCVOL[i] );
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if (rank==0){
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printf("Coarsen level %i \n",i);
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printf(" Nx=%i, Ny=%i, Nz=%i \n",int(tmp.size(0)),int(tmp.size(1)),int(tmp.size(2)) );
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printf(" filter_x=%i, filter_y=%i, filter_z=%i \n",int(filter.size(0)),int(filter.size(1)),int(filter.size(2)) );
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printf(" ratio= %i,%i,%i \n",int(ratio[0]),int(ratio[1]),int(ratio[2]) );
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PROFILE_START("CoarsenMesh");
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for (int i=1; i<N_levels; i++) {
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Array<float> filter(ratio[0],ratio[1],ratio[2]);
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filter.fill(1.0f/filter.length());
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Array<float> tmp(Nx[i-1],Ny[i-1],Nz[i-1]);
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fillFloat[i-1]->copy( LOCVOL[i-1], tmp );
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Array<float> coarse = tmp.coarsen( filter );
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fillFloat[i]->copy( coarse, LOCVOL[i] );
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fillFloat[i]->fill( LOCVOL[i] );
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if (rank==0){
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printf("Coarsen level %i \n",i);
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printf(" Nx=%i, Ny=%i, Nz=%i \n",int(tmp.size(0)),int(tmp.size(1)),int(tmp.size(2)) );
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printf(" filter_x=%i, filter_y=%i, filter_z=%i \n",int(filter.size(0)),int(filter.size(1)),int(filter.size(2)) );
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printf(" ratio= %i,%i,%i \n",int(ratio[0]),int(ratio[1]),int(ratio[2]) );
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}
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MPI_Barrier(comm);
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}
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PROFILE_STOP("CoarsenMesh");
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// Initialize the coarse level
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PROFILE_START("Solve full mesh");
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if (rank==0)
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printf("Initialize full mesh\n");
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solve( LOCVOL[0], Mean[0], ID[0], Dist[0], MultiScaleSmooth[0],
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NonLocalMean[0], *fillFloat[0], *Dm[0], nprocx );
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PROFILE_STOP("Solve fill mesh");
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MPI_Barrier(comm);
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}
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PROFILE_STOP("CoarsenMesh");
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/* // Initialize the coarse level
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PROFILE_START("Solve coarse mesh");
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if (rank==0)
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printf("Initialize coarse mesh\n");
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solve( LOCVOL.back(), Mean.back(), ID.back(), Dist.back(), MultiScaleSmooth.back(),
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NonLocalMean.back(), *fillFloat.back(), *Dm.back(), nprocx );
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PROFILE_STOP("Solve coarse mesh");
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MPI_Barrier(comm);
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// Initialize the coarse level
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PROFILE_START("Solve coarse mesh");
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if (rank==0)
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printf("Initialize coarse mesh\n");
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solve( LOCVOL.back(), Mean.back(), ID.back(), Dist.back(), MultiScaleSmooth.back(),
|
||||
NonLocalMean.back(), *fillFloat.back(), *Dm.back(), nprocx );
|
||||
PROFILE_STOP("Solve coarse mesh");
|
||||
MPI_Barrier(comm);
|
||||
// Refine the solution
|
||||
PROFILE_START("Refine distance");
|
||||
if (rank==0)
|
||||
printf("Refine mesh\n");
|
||||
for (int i=int(Nx.size())-2; i>=0; i--) {
|
||||
if (rank==0)
|
||||
printf(" Refining to level %i\n",int(i));
|
||||
refine( Dist[i+1], LOCVOL[i], Mean[i], ID[i], Dist[i], MultiScaleSmooth[i],
|
||||
NonLocalMean[i], *fillFloat[i], *Dm[i], nprocx, i );
|
||||
}
|
||||
PROFILE_STOP("Refine distance");
|
||||
MPI_Barrier(comm);
|
||||
|
||||
// Refine the solution
|
||||
PROFILE_START("Refine distance");
|
||||
if (rank==0)
|
||||
printf("Refine mesh\n");
|
||||
for (int i=int(Nx.size())-2; i>=0; i--) {
|
||||
if (rank==0)
|
||||
printf(" Refining to level %i\n",int(i));
|
||||
refine( Dist[i+1], LOCVOL[i], Mean[i], ID[i], Dist[i], MultiScaleSmooth[i],
|
||||
NonLocalMean[i], *fillFloat[i], *Dm[i], nprocx, i );
|
||||
}
|
||||
PROFILE_STOP("Refine distance");
|
||||
MPI_Barrier(comm);
|
||||
|
||||
// Perform a final filter
|
||||
PROFILE_START("Filtering final domains");
|
||||
if (rank==0)
|
||||
printf("Filtering final domains\n");
|
||||
Array<float> filter_Mean, filter_Dist1, filter_Dist2;
|
||||
filter_final( ID[0], Dist[0], *fillFloat[0], *Dm[0], filter_Mean, filter_Dist1, filter_Dist2 );
|
||||
PROFILE_STOP("Filtering final domains");
|
||||
|
||||
//removeDisconnected( ID[0], *Dm[0] );
|
||||
// Perform a final filter
|
||||
PROFILE_START("Filtering final domains");
|
||||
if (rank==0)
|
||||
printf("Filtering final domains\n");
|
||||
Array<float> filter_Mean, filter_Dist1, filter_Dist2;
|
||||
filter_final( ID[0], Dist[0], *fillFloat[0], *Dm[0], filter_Mean, filter_Dist1, filter_Dist2 );
|
||||
PROFILE_STOP("Filtering final domains");
|
||||
*/
|
||||
//removeDisconnected( ID[0], *Dm[0] );
|
||||
|
||||
/*
|
||||
/*
|
||||
// Write the distance function to a netcdf file
|
||||
const char* netcdf_filename = "Distance.nc";
|
||||
{
|
||||
@ -310,34 +318,33 @@ int main(int argc, char **argv)
|
||||
netcdf::write( fid, "Distance", dims, data, info );
|
||||
netcdf::close( fid );
|
||||
}
|
||||
*/
|
||||
*/
|
||||
|
||||
|
||||
// Write the results to visit
|
||||
// Write the results to visit
|
||||
if (rank==0) printf("Setting up visualization structure \n");
|
||||
// std::vector<IO::MeshDataStruct> meshData(N_levels);
|
||||
std::vector<IO::MeshDataStruct> meshData(1);
|
||||
// for (size_t i=0; i<Nx.size(); i++) {
|
||||
// Mesh
|
||||
meshData[0].meshName = "image";
|
||||
meshData[0].mesh = std::shared_ptr<IO::DomainMesh>( new IO::DomainMesh(Dm[0]->rank_info,Nx[0],Ny[0],Nz[0],Lx,Ly,Lz) );
|
||||
// Source data
|
||||
std::shared_ptr<IO::Variable> OrigData( new IO::Variable() );
|
||||
OrigData->name = "Source Data";
|
||||
OrigData->type = IO::VariableType::VolumeVariable;
|
||||
OrigData->dim = 1;
|
||||
OrigData->data.resize(Nx[0],Ny[0],Nz[0]);
|
||||
meshData[0].vars.push_back(OrigData);
|
||||
fillDouble[0]->copy( LOCVOL[0], OrigData->data );
|
||||
// Non-Local Mean
|
||||
std::shared_ptr<IO::Variable> NonLocMean( new IO::Variable() );
|
||||
NonLocMean->name = "Non-Local Mean";
|
||||
NonLocMean->type = IO::VariableType::VolumeVariable;
|
||||
NonLocMean->dim = 1;
|
||||
NonLocMean->data.resize(Nx[0],Ny[0],Nz[0]);
|
||||
meshData[0].vars.push_back(NonLocMean);
|
||||
fillDouble[0]->copy( NonLocalMean[0], NonLocMean->data );
|
||||
/*// Segmented Data
|
||||
// Mesh
|
||||
meshData[0].meshName = "image";
|
||||
meshData[0].mesh = std::shared_ptr<IO::DomainMesh>( new IO::DomainMesh(Dm[0]->rank_info,Nx[0],Ny[0],Nz[0],Lx,Ly,Lz) );
|
||||
// Source data
|
||||
std::shared_ptr<IO::Variable> OrigData( new IO::Variable() );
|
||||
OrigData->name = "Source Data";
|
||||
OrigData->type = IO::VariableType::VolumeVariable;
|
||||
OrigData->dim = 1;
|
||||
OrigData->data.resize(Nx[0],Ny[0],Nz[0]);
|
||||
meshData[0].vars.push_back(OrigData);
|
||||
fillDouble[0]->copy( LOCVOL[0], OrigData->data );
|
||||
// Non-Local Mean
|
||||
std::shared_ptr<IO::Variable> NonLocMean( new IO::Variable() );
|
||||
NonLocMean->name = "Non-Local Mean";
|
||||
NonLocMean->type = IO::VariableType::VolumeVariable;
|
||||
NonLocMean->dim = 1;
|
||||
NonLocMean->data.resize(Nx[0],Ny[0],Nz[0]);
|
||||
meshData[0].vars.push_back(NonLocMean);
|
||||
fillDouble[0]->copy( NonLocalMean[0], NonLocMean->data );
|
||||
/*// Segmented Data
|
||||
std::shared_ptr<IO::Variable> SegData( new IO::Variable() );
|
||||
SegData->name = "Segmented Data";
|
||||
SegData->type = IO::VariableType::VolumeVariable;
|
||||
@ -361,7 +368,7 @@ int main(int argc, char **argv)
|
||||
SmoothData->data.resize(Nx[i],Ny[i],Nz[i]);
|
||||
meshData[i].vars.push_back(SmoothData);
|
||||
fillDouble[i]->copy( MultiScaleSmooth[i], SmoothData->data );
|
||||
|
||||
|
||||
}
|
||||
#if 0
|
||||
std::shared_ptr<IO::Variable> filter_Mean_var( new IO::Variable() );
|
||||
@ -386,7 +393,7 @@ int main(int argc, char **argv)
|
||||
meshData[0].vars.push_back(filter_Dist2_var);
|
||||
fillDouble[0]->copy( filter_Dist2, filter_Dist2_var->data );
|
||||
#endif
|
||||
*/
|
||||
*/
|
||||
MPI_Barrier(comm);
|
||||
if (rank==0) printf("Writing output \n");
|
||||
// Write visulization data
|
||||
@ -418,7 +425,7 @@ int main(int argc, char **argv)
|
||||
*/
|
||||
|
||||
PROFILE_STOP("Main");
|
||||
PROFILE_SAVE("lbpm_uCT_pp",true);
|
||||
PROFILE_SAVE("lbpm_uCT_pp",true);
|
||||
MPI_Barrier(comm);
|
||||
MPI_Finalize();
|
||||
return 0;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user