C++ impl::Timer类代码示例

void Loop(int loop, int test, const char* type_name) {
  LoopVariant<T>(loop,test);

  Kokkos::Impl::Timer timer;
  T res = LoopVariant<T>(loop,test);
  double time = timer.seconds();

  timer.reset();
  T resNonAtomic = LoopVariantNonAtomic<T>(loop,test);
  double timeNonAtomic = timer.seconds();

  timer.reset();
  T resSerial = LoopVariantSerial<T>(loop,test);
  double timeSerial = timer.seconds();

  time         *=1e6/loop;
  timeNonAtomic*=1e6/loop;
  timeSerial   *=1e6/loop;
  //textcolor_standard();
  bool passed = true;
  if(resSerial!=res) passed = false;
  //if(!passed) textcolor(RESET,BLACK,YELLOW);
  printf("%s Test %i %s  --- Loop: %i Value (S,A,NA): %e %e %e Time: %7.4e %7.4e %7.4e Size of Type %i)",
         type_name,test,passed?"PASSED":"FAILED",loop,
         1.0*resSerial,1.0*res,1.0*resNonAtomic,
         timeSerial,time,timeNonAtomic,(int)sizeof(T));
  //if(!passed) textcolor_standard();
  printf("\n");
}

int main(int narg, char* args[]) {
  Kokkos::initialize(narg,args);
  
  int chunk_size = 1024;
  int nchunks = 100000; //1024*1024;
  Kokkos::DualView<int*> data("data",nchunks*chunk_size+1);

  srand(1231093);

  for(int i = 0; i < data.dimension_0(); i++) {
    data.h_view(i) = rand()%TS;
  }
  data.modify<Host>();
  data.sync<Device>();

  Kokkos::DualView<int**> histogram("histogram",TS,TS);


  Kokkos::Impl::Timer timer;
  // Threads/team (TS) is automically limited to the maximum supported by the device.
  Kokkos::parallel_for( team_policy( nchunks , TS )
                      , find_2_tuples(chunk_size,data,histogram) );
  Kokkos::fence();
  double time = timer.seconds();

  histogram.sync<Host>();

  printf("Time: %lf \n\n",time);
  int sum = 0;
  for(int k=0; k<TS; k++) {
    for(int l=0; l<TS; l++) {
      printf("%i ",histogram.h_view(k,l));
      sum += histogram.h_view(k,l);
    }
    printf("\n");
  }
  printf("Result: %i %i\n",sum,chunk_size*nchunks);
  Kokkos::finalize();
}

int main(int narg, char* args[]) {
  Kokkos::initialize(narg,args);
  
  int chunk_size = 1024;
  int nchunks = 100000; //1024*1024;
  Kokkos::DualView<int*> data("data",nchunks*chunk_size+1);

  srand(1231093);

  for(int i = 0; i < data.dimension_0(); i++) {
    data.h_view(i) = rand()%TS;
  }
  data.modify<Host>();
  data.sync<Device>();

  Kokkos::DualView<int**> histogram("histogram",TS,TS);


  Kokkos::Impl::Timer timer;
  Kokkos::parallel_for(
      Kokkos::ParallelWorkRequest(nchunks,TS<Device::team_max()?TS:Device::team_max()),
      find_2_tuples(chunk_size,data,histogram));
  Kokkos::fence();
  double time = timer.seconds();

  histogram.sync<Host>();

  printf("Time: %lf \n\n",time);
  int sum = 0;
  for(int k=0; k<TS; k++) {
    for(int l=0; l<TS; l++) {
      printf("%i ",histogram.h_view(k,l));
      sum += histogram.h_view(k,l);
    }
    printf("\n");
  }
  printf("Result: %i %i\n",sum,chunk_size*nchunks);
  Kokkos::finalize();
}

  static double test( const int count , const int iter = 1 )
  {
    elem_coord_type coord( "coord" , count );
    elem_grad_type  grad ( "grad" , count );

    // Execute the parallel kernels on the arrays:

    double dt_min = 0 ;

    Kokkos::parallel_for( count , Init( coord ) );
    device_type::fence();

    for ( int i = 0 ; i < iter ; ++i ) {
      Kokkos::Impl::Timer timer ;
      Kokkos::parallel_for( count , HexGrad<device_type>( coord , grad ) );
      device_type::fence();
      const double dt = timer.seconds();
      if ( 0 == i ) dt_min = dt ;
      else dt_min = dt < dt_min ? dt : dt_min ;
    }

    return dt_min ;
  }

int main (int argc, char ** argv){
  if (argc < 2){
    std::cerr << "Usage:" << argv[0] << " input_bin_file" << std::endl;
    exit(1);
  }


  Kokkos::initialize(argc, argv);
  MyExecSpace::print_configuration(std::cout);
  idx nv = 0, ne = 0;
  idx *xadj, *adj;
  wt *ew;

  KokkosKernels::Experimental::Graph::Utils::read_graph_bin<idx, wt> (&nv, &ne, &xadj, &adj, &ew, argv[1]);

  std::cout << "nv:" << nv << " ne:" << ne << std::endl;

  um_array_type _xadj (xadj, nv + 1);
  um_edge_array_type _adj (adj, ne);

  idx_array_type kok_xadj ("xadj", nv + 1);
  idx_edge_array_type kok_adj("adj", ne);

  idx_array_type sym_xadj;
  idx_edge_array_type sym_adj;

  Kokkos::deep_copy (kok_xadj, _xadj);
  Kokkos::deep_copy (kok_adj, _adj);

  wt_um_edge_array_type _mtx_vals (ew, ne);
  value_array_type kok_mtx_vals ("MTX_VALS", ne);
  Kokkos::deep_copy (kok_mtx_vals, _mtx_vals);

  delete [] xadj;
  delete [] adj;
  delete [] ew;

  std::cout << "Symetrizing Graph" << std::endl;

  Kokkos::Impl::Timer timer;

  KokkosKernels::Experimental::Util::symmetrize_graph_symbolic_hashmap<
  idx_array_type, idx_edge_array_type, idx_array_type, idx_edge_array_type, MyExecSpace>
    (nv, kok_xadj, kok_adj,sym_xadj, sym_adj);
  Kokkos::fence();

  double t = timer.seconds();
  std::cout << "Time to symmetrize:" << t << std::endl;
  KokkosKernels::Experimental::Util::print_1Dview(kok_xadj);
  KokkosKernels::Experimental::Util::print_1Dview(kok_adj);

  std::cout << "Symetric Graph" << std::endl;
  KokkosKernels::Experimental::Util::print_1Dview(sym_xadj);

  KokkosKernels::Experimental::Util::print_1Dview(sym_adj);

  Kokkos::finalize();



  return 0;
}

  KOKKOS_INLINE_FUNCTION
  int exampleCholDirectPerformance(const string file_input,
                                   const int treecut,
                                   const int minblksize,
                                   const int prunecut,
                                   const int seed,
                                   const int niter,
                                   const int nthreads,
                                   const int max_task_dependence,
                                   const int team_size,
                                   const int league_size,
                                   const bool team_interface,
                                   const bool skip_serial,
                                   const bool mkl_interface,
                                   const bool verbose) {
    typedef ValueType   value_type;
    typedef OrdinalType ordinal_type;
    typedef SizeType    size_type;

    typedef TaskFactory<Kokkos::Experimental::TaskPolicy<SpaceType>,
      Kokkos::Experimental::Future<int,SpaceType> > TaskFactoryType;

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> CrsMatrixBaseType;
    typedef GraphHelper_Scotch<CrsMatrixBaseType> GraphHelperType;
    typedef SymbolicFactorHelper<CrsMatrixBaseType> SymbolicFactorHelperType;

#ifdef HAVE_SHYLUTACHO_MKL 
    typedef typename CrsMatrixBaseType::value_type_array value_type_array;
#endif

    typedef CrsMatrixView<CrsMatrixBaseType> CrsMatrixViewType;
    typedef TaskView<CrsMatrixViewType,TaskFactoryType> CrsTaskViewType;
    
    typedef CrsMatrixBase<CrsTaskViewType,ordinal_type,size_type,SpaceType,MemoryTraits> CrsHierMatrixBaseType;

    typedef CrsMatrixView<CrsHierMatrixBaseType> CrsHierMatrixViewType;
    typedef TaskView<CrsHierMatrixViewType,TaskFactoryType> CrsHierTaskViewType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    double 
      t_import = 0.0,
      t_reorder = 0.0,
      t_symbolic = 0.0,
      t_flat2hier = 0.0,
#ifdef HAVE_SHYLUTACHO_MKL 
      t_mkl = 0.0,
#endif
      t_factor_seq = 0.0,   t_solve_seq = 0.0,
      t_factor_task = 0.0,  t_solve_task = 0.0;
    const int start = 0;
    
    cout << "CholDirectPerformance:: import input file = " << file_input << endl;        
    CrsMatrixBaseType AA("AA");
    {
      timer.reset();

      ifstream in;
      in.open(file_input);
      if (!in.good()) {
        cout << "Failed in open the file: " << file_input << endl;
        return ++r_val;
      }
      AA.importMatrixMarket(in);

      t_import = timer.seconds();
    }
    cout << "CholDirectPerformance:: import input file::time = " << t_import << endl;

    cout << "CholDirectPerformance:: reorder the matrix" << endl;        
    CrsMatrixBaseType PA("Permuted AA");
    CrsMatrixBaseType UU("UU");     // permuted base upper triangular matrix
    CrsHierMatrixBaseType HU("HU"); // hierarchical matrix of views

    DenseMatrixBaseType BB("BB", AA.NumRows(), nrhs);
    DenseHierMatrixBaseType HB("HB");

    {
      GraphHelperType S(AA, seed);
      {
        timer.reset();
        
        S.computeOrdering(treecut, minblksize);
        S.pruneTree(prunecut);
        
        PA.copy(S.PermVector(), S.InvPermVector(), AA);
        
        t_reorder = timer.seconds();
      }

      cout << "CholDirectPerformance:: reorder the matrix::time = " << t_reorder << endl;            
      {
        SymbolicFactorHelperType F(PA, league_size);
        for (int i=start;i<niter;++i) {
          timer.reset();
        
          F.createNonZeroPattern(Uplo::Upper, UU);

          t_symbolic += timer.seconds() * (i>=0);
//.........这里部分代码省略.........

  KOKKOS_INLINE_FUNCTION
  int exampleTriSolvePerformance(const string file_input,
                                 const OrdinalType nrhs,
                                 const OrdinalType nb,
                                 const int niter,
                                 const int nthreads,
                                 const int max_task_dependence,
                                 const int team_size, 
                                 const bool team_interface,
                                 const bool skip_serial,
                                 const bool verbose) {
    typedef ValueType   value_type;
    typedef OrdinalType ordinal_type;
    typedef SizeType    size_type;

    typedef TaskFactory<Kokkos::Experimental::TaskPolicy<SpaceType>,
      Kokkos::Experimental::Future<int,SpaceType> > TaskFactoryType;

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> CrsMatrixBaseType;
    typedef GraphHelper_Scotch<CrsMatrixBaseType> GraphHelperType;

    typedef CrsMatrixView<CrsMatrixBaseType> CrsMatrixViewType;
    typedef TaskView<CrsMatrixViewType,TaskFactoryType> CrsTaskViewType;
    
    typedef CrsMatrixBase<CrsTaskViewType,ordinal_type,size_type,SpaceType,MemoryTraits> CrsHierMatrixBaseType;

    typedef CrsMatrixView<CrsHierMatrixBaseType> CrsHierMatrixViewType;
    typedef TaskView<CrsHierMatrixViewType,TaskFactoryType> CrsHierTaskViewType;

    typedef DenseMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> DenseMatrixBaseType;

    typedef DenseMatrixView<DenseMatrixBaseType> DenseMatrixViewType;
    typedef TaskView<DenseMatrixViewType,TaskFactoryType> DenseTaskViewType;

    typedef DenseMatrixBase<DenseTaskViewType,ordinal_type,size_type,SpaceType,MemoryTraits> DenseHierMatrixBaseType;

    typedef DenseMatrixView<DenseHierMatrixBaseType> DenseHierMatrixViewType;
    typedef TaskView<DenseHierMatrixViewType,TaskFactoryType> DenseHierTaskViewType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    double 
      t_import = 0.0,
      t_reorder = 0.0,
      t_solve_seq = 0.0,
      t_solve_task = 0.0;
    const int start = -2;

    cout << "TriSolvePerformance:: import input file = " << file_input << endl;
    CrsMatrixBaseType AA("AA");
    {
      timer.reset();

      ifstream in;
      in.open(file_input);
      if (!in.good()) {
        cout << "Failed in open the file: " << file_input << endl;
        return ++r_val;
      }
      AA.importMatrixMarket(in);

      t_import = timer.seconds();

      if (verbose)
        cout << AA << endl;
    }
    cout << "TriSolvePerformance:: import input file::time = " << t_import << endl;

    CrsMatrixBaseType   UU("UU");
    DenseMatrixBaseType BB("BB",  AA.NumRows(), nrhs);

    cout << "TriSolvePerformance:: reorder the matrix and partition right hand side, nb = " << nb << endl;
    CrsHierMatrixBaseType   HU("HU");
    DenseHierMatrixBaseType HB("HB");
    {
      timer.reset();

      GraphHelperType S(AA);
      S.computeOrdering();

      CrsMatrixBaseType PA("Permuted AA");
      PA.copy(S.PermVector(), S.InvPermVector(), AA);

      UU.copy(Uplo::Upper, PA);

      CrsMatrixHelper::flat2hier(Uplo::Upper, UU, HU,
                                 S.NumBlocks(),
                                 S.RangeVector(),
                                 S.TreeVector());

      DenseMatrixHelper::flat2hier(BB, HB,
                                   S.NumBlocks(),
                                   S.RangeVector(),
                                   nb);

      t_reorder = timer.seconds();

      cout << "TriSolvePerformance:: Hier (dof, nnz) = " << HU.NumRows() << ", " << HU.NumNonZeros() << endl;

//.........这里部分代码省略.........

  KOKKOS_INLINE_FUNCTION
  int exampleDenseGemmByBlocks(const OrdinalType mmin,
                               const OrdinalType mmax,
                               const OrdinalType minc,
                               const OrdinalType k,
                               const OrdinalType mb,
                               const int max_concurrency,
                               const int max_task_dependence,
                               const int team_size,
                               const int mkl_nthreads,
                               const bool check,
                               const bool verbose) {
    typedef ValueType   value_type;
    typedef OrdinalType ordinal_type;
    typedef SizeType    size_type;

    typedef TaskFactory<Kokkos::Experimental::TaskPolicy<SpaceType>,
      Kokkos::Experimental::Future<int,SpaceType> > TaskFactoryType;

    typedef DenseMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> DenseMatrixBaseType;

    typedef DenseMatrixView<DenseMatrixBaseType> DenseMatrixViewType;
    typedef TaskView<DenseMatrixViewType,TaskFactoryType> DenseTaskViewType;

    typedef DenseMatrixBase<DenseTaskViewType,ordinal_type,size_type,SpaceType,MemoryTraits> DenseHierMatrixBaseType;

    typedef DenseMatrixView<DenseHierMatrixBaseType> DenseHierMatrixViewType;
    typedef TaskView<DenseHierMatrixViewType,TaskFactoryType> DenseHierTaskViewType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    double t = 0.0;

    cout << "DenseGemmByBlocks:: test matrices "
         <<":: mmin = " << mmin << " , mmax = " << mmax << " , minc = " << minc << " , k = "<< k << " , mb = " << mb << endl;

    const size_t max_task_size = (3*sizeof(DenseTaskViewType)+196); // when 128 error
    //cout << "max task size = "<< max_task_size << endl;
    typename TaskFactoryType::policy_type policy(max_concurrency,
                                                 max_task_size,
                                                 max_task_dependence, 
                                                 team_size);
    
    TaskFactoryType::setMaxTaskDependence(max_task_dependence);
    TaskFactoryType::setPolicy(&policy);

    ostringstream os;
    os.precision(3);
    os << scientific;

    for (ordinal_type m=mmin;m<=mmax;m+=minc) {
      os.str("");

      DenseMatrixBaseType AA, BB, CC("CC", m, m), CB("CB", m, m);

      if (ArgTransA == Trans::NoTranspose) 
        AA = DenseMatrixBaseType("AA", m, k); 
      else 
        AA = DenseMatrixBaseType("AA", k, m);
      
      if (ArgTransB == Trans::NoTranspose) 
        BB = DenseMatrixBaseType("BB", k, m);
      else 
        BB = DenseMatrixBaseType("BB", m, k);
      
      for (ordinal_type j=0;j<AA.NumCols();++j)
        for (ordinal_type i=0;i<AA.NumRows();++i)
          AA.Value(i,j) = 2.0*((value_type)rand()/(RAND_MAX)) - 1.0;
      
      for (ordinal_type j=0;j<BB.NumCols();++j)
        for (ordinal_type i=0;i<BB.NumRows();++i)
          BB.Value(i,j) = 2.0*((value_type)rand()/(RAND_MAX)) - 1.0;
      
      for (ordinal_type j=0;j<CC.NumCols();++j)
        for (ordinal_type i=0;i<CC.NumRows();++i)
          CC.Value(i,j) = 2.0*((value_type)rand()/(RAND_MAX)) - 1.0;
      CB.copy(CC);

      const double flop = get_flop_gemm<value_type>(m, m, k);

#ifdef HAVE_SHYLUTACHO_MKL
      mkl_set_num_threads(mkl_nthreads);
#endif

      os << "DenseGemmByBlocks:: m = " << m << " n = " << m << " k = " << k;
      if (check) {
        timer.reset();
        DenseTaskViewType A(&AA), B(&BB), C(&CB);
        Gemm<ArgTransA,ArgTransB,AlgoGemm::ExternalBlas>::invoke
          (TaskFactoryType::Policy(),
           TaskFactoryType::Policy().member_single(),
           1.0, A, B, 1.0, C);
        t = timer.seconds();
        os << ":: Serial Performance = " << (flop/t/1.0e9) << " [GFLOPs]  ";
      }

      {
        DenseHierMatrixBaseType HA, HB, HC;
        DenseMatrixHelper::flat2hier(AA, HA, mb, mb);
//.........这里部分代码省略.........

  int exampleCholByBlocks(const std::string file_input,
                          const int treecut,
                          const int prunecut,
                          const int fill_level,
                          const int rows_per_team,
                          const int max_concurrency,
                          const int max_task_dependence,
                          const int team_size,
                          const bool check,
                          const bool verbose) {
    typedef typename
      Kokkos::Impl::is_space<DeviceSpaceType>::host_mirror_space::execution_space HostSpaceType ;

    const bool detail = false;
    std::cout << "DeviceSpace::  "; DeviceSpaceType::print_configuration(std::cout, detail);
    std::cout << "HostSpace::    ";   HostSpaceType::print_configuration(std::cout, detail);

    // for simple test, let's use host space only here, for device it needs mirroring.

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,HostSpaceType> CrsMatrixBaseHostType;
    typedef CrsMatrixView<CrsMatrixBaseHostType> CrsMatrixViewHostType;

    typedef GraphTools<ordinal_type,size_type,HostSpaceType> GraphToolsHostType;

    typedef GraphTools_Scotch<ordinal_type,size_type,HostSpaceType> GraphToolsHostType_Scotch;
    typedef GraphTools_CAMD<ordinal_type,size_type,HostSpaceType> GraphToolsHostType_CAMD;

    typedef IncompleteSymbolicFactorization<CrsMatrixBaseHostType> IncompleteSymbolicFactorizationType;

    typedef Kokkos::Experimental::TaskPolicy<DeviceSpaceType> PolicyType;

    typedef TaskView<CrsMatrixViewHostType> CrsTaskViewHostType;
    typedef CrsMatrixBase<CrsTaskViewHostType,ordinal_type,size_type,HostSpaceType> CrsHierBaseHostType;
    typedef CrsMatrixView<CrsHierBaseHostType> CrsHierViewHostType;
    typedef TaskView<CrsHierViewHostType> CrsTaskHierViewHostType;

    int r_val = 0;
    
    Kokkos::Impl::Timer timer;

    ///
    /// Read from matrix market
    ///
    ///     input  - file
    ///     output - AA_host
    ///
    CrsMatrixBaseHostType AA_host("AA_host");
    timer.reset();
    {
      std::ifstream in;
      in.open(file_input);
      if (!in.good()) {
        std::cout << "Failed in open the file: " << file_input << std::endl;
        return -1;
      }
      MatrixMarket::read(AA_host, in);
    }
    double t_read = timer.seconds();

    if (verbose)
      AA_host.showMe(std::cout) << std::endl;

    ///
    /// Create a graph structure for Scotch and CAMD (rptr, cidx)
    ///     
    ///     rptr and cidx are need to be set up for Scotch and CAMD
    ///
    typename GraphToolsHostType::size_type_array rptr("Graph::RowPtrArray", AA_host.NumRows() + 1);
    typename GraphToolsHostType::ordinal_type_array cidx("Graph::ColIndexArray", AA_host.NumNonZeros());

    ///
    /// Run Scotch
    ///
    ///     input  - rptr, cidx, A_host
    ///     output - S (perm, iperm, nblks, range, tree), AA_scotch_host (permuted)
    ///
    timer.reset();
    GraphToolsHostType::getGraph(rptr, cidx, AA_host);
    double t_graph = timer.seconds();

    GraphToolsHostType_Scotch S;
    S.setGraph(AA_host.NumRows(), rptr, cidx);
    S.setSeed(0);
    S.setTreeLevel();
    S.setStrategy( SCOTCH_STRATSPEED 
                   | SCOTCH_STRATLEVELMAX   
                   | SCOTCH_STRATLEVELMIN   
                   | SCOTCH_STRATLEAFSIMPLE 
                   | SCOTCH_STRATSEPASIMPLE 
                   );
    
    timer.reset();
    S.computeOrdering(treecut);
    double t_scotch = timer.seconds();
    
    if (verbose)
      S.showMe(std::cout) << std::endl;

    CrsMatrixBaseHostType AA_scotch_host("AA_scotch_host");
    AA_scotch_host.createConfTo(AA_host);
//.........这里部分代码省略.........

  KOKKOS_INLINE_FUNCTION
  int exampleSymbolicFactor(const string file_input,
                            const int treecut,
                            const int minblksize,
                            const int seed,
                            const int fill_level,
                            const int league_size,
                            const bool reorder,
                            const bool verbose) {
    typedef ValueType   value_type;
    typedef OrdinalType ordinal_type;
    typedef SizeType    size_type;

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> CrsMatrixBaseType;
    typedef GraphHelper_Scotch<CrsMatrixBaseType> GraphHelperType;
    typedef SymbolicFactorHelper<CrsMatrixBaseType> SymbolicFactorHelperType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    double t = 0.0;

    cout << "SymbolicFactor:: import input file = " << file_input << endl;
    CrsMatrixBaseType AA("AA");
    {
      timer.reset();

      ifstream in;
      in.open(file_input);
      if (!in.good()) {
        cout << "Failed in open the file: " << file_input << endl;
        return ++r_val;
      }
      AA.importMatrixMarket(in);
      t = timer.seconds();

      cout << "SymbolicFactor:: AA nnz = " << AA.NumNonZeros() << endl;
      if (verbose)
        cout << AA << endl;
    }
    cout << "SymbolicFactor:: import input file::time = " << t << endl;

    CrsMatrixBaseType PA("Permuted AA");
    GraphHelperType S(AA, seed);
    if (reorder) {
      timer.reset();

      S.computeOrdering(treecut, minblksize);

      PA.copy(S.PermVector(), S.InvPermVector(), AA);

      t = timer.seconds();

      if (verbose)
        cout << S << endl
             << PA << endl;
    } else {
      PA = AA;

      t = 0.0;
    }
    cout << "SymbolicFactor:: reorder the matrix::time = " << t << endl;


    CrsMatrixBaseType UU("UU");
    {
      timer.reset();

      SymbolicFactorHelperType symbolic(PA, league_size);
      symbolic.createNonZeroPattern(fill_level, Uplo::Upper, UU);

      t = timer.seconds();

      cout << "SymbolicFactor:: UU nnz = " << UU.NumNonZeros() << endl;

      if (verbose) {
        cout << symbolic << endl;
        cout << UU << endl;
      }
    }
    cout << "SymbolicFactor:: factorize the matrix::time = " << t << endl;

    return r_val;
  }

  int exampleCholUnblocked(const std::string file_input,
                           const int treecut,
                           const int prunecut,
                           const int fill_level,
                           const int rows_per_team,
                           const bool verbose) {
    typedef typename
      Kokkos::Impl::is_space<DeviceSpaceType>::host_mirror_space::execution_space HostSpaceType ;

    const bool detail = false;
    std::cout << "DeviceSpace::  "; DeviceSpaceType::print_configuration(std::cout, detail);
    std::cout << "HostSpace::    ";   HostSpaceType::print_configuration(std::cout, detail);

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,HostSpaceType> CrsMatrixBaseHostType;
    typedef GraphTools<ordinal_type,size_type,HostSpaceType> GraphToolsHostType;

    typedef GraphTools_Scotch<ordinal_type,size_type,HostSpaceType> GraphToolsHostType_Scotch;
    typedef GraphTools_CAMD<ordinal_type,size_type,HostSpaceType> GraphToolsHostType_CAMD;

    typedef IncompleteSymbolicFactorization<CrsMatrixBaseHostType> IncompleteSymbolicFactorizationType;

    typedef Kokkos::Experimental::TaskPolicy<DeviceSpaceType> PolicyType;

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,DeviceSpaceType> CrsMatrixBaseDeviceType;

    typedef CrsMatrixView<CrsMatrixBaseDeviceType> CrsMatrixViewDeviceType;
    typedef TaskView<CrsMatrixViewDeviceType> CrsTaskViewDeviceType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;

    CrsMatrixBaseHostType AA_host("AA_host");
    timer.reset();
    {
      std::ifstream in;
      in.open(file_input);
      if (!in.good()) {
        std::cout << "Failed in open the file: " << file_input << std::endl;
        return -1;
      }
      MatrixMarket::read(AA_host, in);
    }
    double t_read = timer.seconds();

    if (verbose)
      AA_host.showMe(std::cout) << std::endl;

    typename GraphToolsHostType::size_type_array rptr("Graph::RowPtrArray", AA_host.NumRows() + 1);
    typename GraphToolsHostType::ordinal_type_array cidx("Graph::ColIndexArray", AA_host.NumNonZeros());

    timer.reset();
    GraphToolsHostType::getGraph(rptr, cidx, AA_host);
    double t_graph = timer.seconds();

    GraphToolsHostType_Scotch S;
    S.setGraph(AA_host.NumRows(), rptr, cidx);
    S.setSeed(0);
    S.setTreeLevel();
    S.setStrategy( SCOTCH_STRATSPEED
                   | SCOTCH_STRATLEVELMAX  
                   | SCOTCH_STRATLEVELMIN  
                   | SCOTCH_STRATLEAFSIMPLE
                   | SCOTCH_STRATSEPASIMPLE
                   );

    timer.reset();
    S.computeOrdering(treecut);
    double t_scotch = timer.seconds();

    S.pruneTree(prunecut);
    if (verbose)
      S.showMe(std::cout) << std::endl;

    CrsMatrixBaseHostType BB_host("BB_host");
    BB_host.createConfTo(AA_host);

    CrsMatrixTools::copy(BB_host,
                         S.PermVector(),
                         S.InvPermVector(),
                         AA_host);

    if (verbose)
      BB_host.showMe(std::cout) << std::endl;

    timer.reset();
    GraphToolsHostType::getGraph(rptr, cidx, BB_host);
    t_graph += timer.seconds();

    GraphToolsHostType_CAMD C;
    C.setGraph(BB_host.NumRows(),
               rptr, cidx,
               S.NumBlocks(),
               S.RangeVector());

    timer.reset();
    C.computeOrdering();
    double t_camd = timer.seconds();

    if (verbose)
//.........这里部分代码省略.........

  KOKKOS_INLINE_FUNCTION
  int exampleStatByBlocks(const string file_input,
                          const int treecut,
                          const int minblksize,
                          const int prunecut,
                          const int seed,
                          const int fill_level,
                          const int league_size,
                          const int histogram_size,
                          const bool verbose) {
    typedef ValueType   value_type;
    typedef OrdinalType ordinal_type;
    typedef SizeType    size_type;

    typedef CrsMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> CrsMatrixBaseType;
    typedef GraphHelper_Scotch<CrsMatrixBaseType> GraphHelperType;
    typedef SymbolicFactorHelper<CrsMatrixBaseType> SymbolicFactorHelperType;

    typedef CrsMatrixView<CrsMatrixBaseType> CrsMatrixViewType;
    typedef CrsMatrixBase<CrsMatrixViewType,ordinal_type,size_type,SpaceType,MemoryTraits> CrsHierMatrixBaseType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    double t = 0.0;

    cout << "StatByBlocks:: import input file = " << file_input << endl;
    CrsMatrixBaseType AA("AA");
    {
      timer.reset();

      ifstream in;
      in.open(file_input);
      if (!in.good()) {
        cout << "Failed in open the file: " << file_input << endl;
        return ++r_val;
      }
      AA.importMatrixMarket(in);

      t = timer.seconds();

      if (verbose)
        cout << AA << endl;
    }
    cout << "StatByBlocks:: import input file::time = " << t << endl;


    CrsMatrixBaseType UU("UU");
    CrsHierMatrixBaseType HU("HU");
    {
      CrsMatrixBaseType PA("Permuted AA");
      typename GraphHelperType::size_type_array rptr(AA.Label()+"Graph::RowPtrArray", AA.NumRows() + 1);
      typename GraphHelperType::ordinal_type_array cidx(AA.Label()+"Graph::ColIndexArray", AA.NumNonZeros());

      AA.convertGraph(rptr, cidx);
      GraphHelperType S(AA.Label()+"ScotchHelper",
                        AA.NumRows(),
                        rptr,
                        cidx,
                        seed);
      {
        timer.reset();

        S.computeOrdering(treecut, minblksize);
        S.pruneTree(prunecut);

        PA.copy(S.PermVector(), S.InvPermVector(), AA);

        t = timer.seconds();

        if (verbose)
          cout << S << endl;
      }
      cout << "StatByBlocks:: reorder the matrix::time = " << t << endl;

      {
        SymbolicFactorHelperType F(PA, league_size);
        timer.reset();

        F.createNonZeroPattern(fill_level, Uplo::Upper, UU);

        t = timer.seconds();
        cout << "StatByBlocks:: AA (nnz) = " << AA.NumNonZeros() << ", UU (nnz) = " << UU.NumNonZeros() << endl;
      }
      cout << "StatByBlocks:: symbolic factorization::time = " << t << endl;

      {
        timer.reset();

        CrsMatrixHelper::flat2hier(Uplo::Upper, UU, HU,
                                   S.NumBlocks(),
                                   S.RangeVector(),
                                   S.TreeVector());

        for (ordinal_type k=0;k<HU.NumNonZeros();++k)
          HU.Value(k).fillRowViewArray();

        t = timer.seconds();
        cout << "StatByBlocks:: Hier (dof, nnz) = " << HU.NumRows() << ", " << HU.NumNonZeros() << endl;
      }
//.........这里部分代码省略.........

  KOKKOS_INLINE_FUNCTION
  int exampleDenseTrsmMKL(const OrdinalType mmin,
                          const OrdinalType mmax,
                          const OrdinalType minc,
                          const OrdinalType k,
                          const bool verbose) {
    typedef ValueType   value_type;
    typedef OrdinalType ordinal_type;
    typedef SizeType    size_type;

    typedef DenseMatrixBase<value_type,ordinal_type,size_type,SpaceType,MemoryTraits> DenseMatrixBaseType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    double t = 0.0;

    cout << "DenseGemmMKL:: test matrices "
         <<":: mmin = " << mmin << " , mmax = " << mmax << " , minc = " << minc << " , k = "<< k << endl;

    ostringstream os;
    os.precision(3);
    os << scientific;

    for (ordinal_type m=mmin;m<=mmax;m+=minc) {
      os.str("");

      DenseMatrixBaseType AA("AA", m, m), BB("BB", m, k), BC("BC", m, k);
      
      // setup upper triangular
      for (ordinal_type j=0;j<AA.NumCols();++j) {
        AA.Value(j,j) = 10.0;
        for (ordinal_type i=0;i<j;++i)
          AA.Value(i,j) = 2.0*((value_type)rand()/(RAND_MAX)) - 1.0;
      }

      // setup one and right hand side is going to be overwritten by the product of AB
      for (ordinal_type j=0;j<BB.NumCols();++j)
        for (ordinal_type i=0;i<BB.NumRows();++i)
          BB.Value(i,j) = 1.0;

      Teuchos::BLAS<ordinal_type,value_type> blas;

      blas.GEMM(Teuchos::CONJ_TRANS, Teuchos::NO_TRANS,
                m, k, m,
                1.0,
                AA.ValuePtr(), AA.ColStride(),
                BB.ValuePtr(), BB.ColStride(),
                0.0,
                BC.ValuePtr(), BC.ColStride());
      BB.copy(BC);

      const double flop = get_flop_trsm_upper<value_type>(m, k);

      os << "DenseTrsmMKL:: m = " << m << " k = " << k;
      {
        timer.reset();
        Teuchos::BLAS<ordinal_type,value_type> blas;

        const ordinal_type mm = AA.NumRows();
        const ordinal_type nn = BB.NumCols();

        blas.TRSM(Teuchos::LEFT_SIDE, Teuchos::UPPER_TRI, Teuchos::CONJ_TRANS,
                  Teuchos::NON_UNIT_DIAG,
                  mm, nn,
                  1.0,
                  AA.ValuePtr(), AA.ColStride(),
                  BB.ValuePtr(), BB.ColStride());
        t = timer.seconds();
        os << ":: MKL Performance = " << (flop/t/1.0e9) << " [GFLOPs]  ";
      }
      cout << os.str() << endl;
    }

    return r_val;
  }

  int exampleMatrixMarket(const std::string file_input,
                          const bool verbose) {
    typedef typename
      Kokkos::Impl::is_space<DeviceSpaceType>::host_mirror_space::execution_space HostSpaceType ;

    const bool detail = false;
    std::cout << "DeviceSpace::  "; DeviceSpaceType::print_configuration(std::cout, detail);
    std::cout << "HostSpace::    ";   HostSpaceType::print_configuration(std::cout, detail);
  
    typedef CrsMatrixBase<value_type,ordinal_type,size_type,HostSpaceType>   CrsMatrixBaseHostType;

    int r_val = 0;

    Kokkos::Impl::Timer timer;
    
    CrsMatrixBaseHostType AA("AA");
    timer.reset();
    {
      std::ifstream in;
      in.open(file_input);
      if (!in.good()) {
        std::cout << "Failed in open the file: " << file_input << std::endl;
        return -1;
      }
      MatrixMarket::read(AA, in);
    }
    double t_read = timer.seconds();
    
    timer.reset();
    {
      std::string file_output = "mm-test-output.mtx";
      std::ofstream out;
      out.open(file_output);
      if (!out.good()) {
        std::cout << "Failed in open the file: " << file_output << std::endl;
        return -1;
      }
      MatrixMarket::write(out, AA, "%% Test output");
    }
    double t_write = timer.seconds();

    {
      const auto prec = std::cout.precision();
      std::cout.precision(4);

      std::cout << std::scientific
                << "MatrixMarket:: dimension = " << AA.NumRows() << " x " << AA.NumCols() 
                << ", " << " nnz = " << AA.NumNonZeros() << ", "
                << "read = " << t_read << " [sec], "
                << "write = " << t_write << " [sec] "
                << std::endl;

      std::cout.unsetf(std::ios::scientific);
      std::cout.precision(prec);
    }
    
    if (verbose) {
      AA.showMe(std::cout) << std::endl;
    }

    CrsMatrixBaseHostType BB("BB");
    BB.createConfTo(AA);

    CrsMatrixTools::copy(BB, Uplo::Upper, 0, AA);
    if (verbose) {
      BB.setLabel("Copy::AA:Upper::0"); BB.showMe(std::cout) << std::endl;
    }

    CrsMatrixTools::copy(BB, Uplo::Upper, 1, AA);
    if (verbose) {
      BB.setLabel("Copy::AA:Upper::1"); BB.showMe(std::cout) << std::endl;    
    }

    CrsMatrixTools::copy(BB, Uplo::Lower, 0, AA);
    if (verbose) {
      BB.setLabel("Copy::AA:Lower::0"); BB.showMe(std::cout) << std::endl;    
    }

    CrsMatrixTools::copy(BB, Uplo::Lower, 1, AA);
    if (verbose) {
      BB.setLabel("Copy::AA:Lower::1"); BB.showMe(std::cout) << std::endl;    
    }

    return r_val;
  }

    int ComputeBasis_HGRAD_Vector(const ordinal_type nworkset,
                                  const ordinal_type C,
                                  const ordinal_type order,
                                  const bool verbose) {
      typedef Vector<VectorTagType> VectorType;

      typedef typename VectorTagType::value_type ValueType;
      constexpr int VectorLength = VectorTagType::length;

      Teuchos::RCP<std::ostream> verboseStream;
      Teuchos::oblackholestream bhs; // outputs nothing

      if (verbose) 
        verboseStream = Teuchos::rcp(&std::cout, false);
      else
        verboseStream = Teuchos::rcp(&bhs,       false);

      Teuchos::oblackholestream oldFormatState;
      oldFormatState.copyfmt(std::cout);

      typedef typename
        Kokkos::Impl::is_space<DeviceSpaceType>::host_mirror_space::execution_space HostSpaceType ;

      *verboseStream << "DeviceSpace::  "; DeviceSpaceType::print_configuration(*verboseStream, false);
      *verboseStream << "HostSpace::    ";   HostSpaceType::print_configuration(*verboseStream, false);
      *verboseStream << "VectorLength::  " << (VectorLength) << "\n";

      using BasisTypeHost = Basis_HGRAD_HEX_C1_FEM<HostSpaceType,ValueType,ValueType>;
      using ImplBasisType = Impl::Basis_HGRAD_HEX_C1_FEM;
      using range_type = Kokkos::pair<ordinal_type,ordinal_type>;

      constexpr size_t LLC_CAPACITY = 32*1024*1024;
      Intrepid2::Test::Flush<LLC_CAPACITY,DeviceSpaceType> flush;
      
      Kokkos::Impl::Timer timer;
      double t_vectorize = 0;
      int errorFlag = 0;

      BasisTypeHost hostBasis;
      const auto cellTopo = hostBasis.getBaseCellTopology();

      auto cubature = DefaultCubatureFactory::create<DeviceSpaceType,ValueType,ValueType>(cellTopo, order);

      const ordinal_type 
        numCells = C,
        numCellsAdjusted = C/VectorLength + (C%VectorLength > 0),
        numVerts = cellTopo.getVertexCount(),
        numDofs = hostBasis.getCardinality(),
        numPoints = cubature->getNumPoints(), 
        spaceDim = cubature->getDimension();

      Kokkos::DynRankView<ValueType,HostSpaceType> dofCoordsHost("dofCoordsHost", numDofs, spaceDim);
      hostBasis.getDofCoords(dofCoordsHost);
      const auto refNodesHost = Kokkos::subview(dofCoordsHost, range_type(0, numVerts), Kokkos::ALL());
      
      // pertub nodes
      Kokkos::DynRankView<VectorType,HostSpaceType> worksetCellsHost("worksetCellsHost", numCellsAdjusted, numVerts, spaceDim);
      for (ordinal_type cell=0;cell<numCells;++cell) {
        for (ordinal_type i=0;i<numVerts;++i)
          for (ordinal_type j=0;j<spaceDim;++j) {
            ValueType val = (rand()/(RAND_MAX + 1.0))*0.2 -0.1;
            worksetCellsHost(cell/VectorLength, i, j)[cell%VectorLength] = refNodesHost(i, j) + val; 
          }
      }

      auto worksetCells = Kokkos::create_mirror_view(typename DeviceSpaceType::memory_space(), worksetCellsHost);
      Kokkos::deep_copy(worksetCells, worksetCellsHost);

      Kokkos::DynRankView<ValueType,DeviceSpaceType> refPoints("refPoints", numPoints, spaceDim), refWeights("refWeights", numPoints);
      cubature->getCubature(refPoints, refWeights);

      std::cout
        << "===============================================================================\n" 
        << " Performance Test evaluating ComputeBasis \n"
        << " # of workset = " << nworkset << "\n" 
        << " Test Array Structure (C,F,P,D) = " << numCells << ", " << numDofs << ", " << numPoints << ", " << spaceDim << "\n"
        << "===============================================================================\n";

      *verboseStream
        << "\n"
        << "===============================================================================\n"
        << "TEST 1: evaluateFields vector version\n"
        << "===============================================================================\n";
      
      try {
        Kokkos::DynRankView<ValueType,DeviceSpaceType> 
          refBasisValues("refBasisValues", numDofs, numPoints),
          refBasisGrads ("refBasisGrads",  numDofs, numPoints, spaceDim);
        
        ImplBasisType::getValues<DeviceSpaceType>(refBasisValues, refPoints, OPERATOR_VALUE);
        ImplBasisType::getValues<DeviceSpaceType>(refBasisGrads,  refPoints, OPERATOR_GRAD);
        
        const ordinal_type ibegin = -3;

        // testing vertical approach
        {          
          Kokkos::DynRankView<VectorType,DeviceSpaceType> 
            weightedBasisValues("weightedBasisValues", numCellsAdjusted, numDofs, numPoints),
            weightedBasisGrads ("weightedBasisGrads",  numCellsAdjusted, numDofs, numPoints, spaceDim);

//.........这里部分代码省略.........