C++ Epetra_MpiComm::Comm方法代码示例

// This constructor is for just one subdomain, so only adds the info
// for multiple time steps on the domain. No two-level parallelism.
MultiMpiComm::MultiMpiComm(const Epetra_MpiComm& EpetraMpiComm_, int numTimeSteps_,
                           const Teuchos::EVerbosityLevel verbLevel) :
        Epetra_MpiComm(EpetraMpiComm_),
        Teuchos::VerboseObject<MultiMpiComm>(verbLevel),
        myComm(Teuchos::rcp(new Epetra_MpiComm(EpetraMpiComm_))),
        subComm(0)
{

  numSubDomains = 1;
  subDomainRank = 0;
  numTimeSteps = numTimeSteps_;
  numTimeStepsOnDomain = numTimeSteps_;
  firstTimeStepOnDomain = 0;

  subComm = new Epetra_MpiComm(EpetraMpiComm_);

  // Create split communicators for time domain
  MPI_Comm time_split_MPI_Comm;
  int rank = EpetraMpiComm_.MyPID();
  (void) MPI_Comm_split(EpetraMpiComm_.Comm(), rank, rank,
                        &time_split_MPI_Comm);
  timeComm = new Epetra_MpiComm(time_split_MPI_Comm);
  numTimeDomains = EpetraMpiComm_.NumProc();
  timeDomainRank = rank;
}

int ARPACKm3::reSolve(int numEigen, Epetra_MultiVector &Q, double *lambda, int startingEV) {

  // Computes eigenvalues and the corresponding eigenvectors
  // of the generalized eigenvalue problem
  // 
  //      K X = M X Lambda
  // 
  // using ARPACK (mode 3).
  //
  // The convergence test is provided by ARPACK.
  //
  // Note that if M is not specified, then  K X = X Lambda is solved.
  // (using the mode for generalized eigenvalue problem).
  // 
  // Input variables:
  // 
  // numEigen  (integer) = Number of eigenmodes requested
  // 
  // Q (Epetra_MultiVector) = Initial search space
  //                   The number of columns of Q defines the size of search space (=NCV).
  //                   The rows of X are distributed across processors.
  //                   As a rule of thumb in ARPACK User's guide, NCV >= 2*numEigen.
  //                   At exit, the first numEigen locations contain the eigenvectors requested.
  // 
  // lambda (array of doubles) = Converged eigenvalues
  //                   The length of this array is equal to the number of columns in Q.
  //                   At exit, the first numEigen locations contain the eigenvalues requested.
  // 
  // startingEV (integer) = Number of eigenmodes already stored in Q
  //                   A linear combination of these vectors is made to define the starting
  //                   vector, placed in resid.
  //
  // Return information on status of computation
  // 
  // info >=   0 >> Number of converged eigenpairs at the end of computation
  // 
  // // Failure due to input arguments
  // 
  // info = -  1 >> The stiffness matrix K has not been specified.
  // info = -  2 >> The maps for the matrix K and the matrix M differ.
  // info = -  3 >> The maps for the matrix K and the preconditioner P differ.
  // info = -  4 >> The maps for the vectors and the matrix K differ.
  // info = -  5 >> Q is too small for the number of eigenvalues requested.
  // info = -  6 >> Q is too small for the computation parameters.
  // 
  // info = -  8 >> numEigen must be smaller than the dimension of the matrix.
  //
  // info = - 30 >> MEMORY
  //
  // See ARPACK documentation for the meaning of INFO

  if (numEigen <= startingEV) {
    return numEigen;
  }

  int info = myVerify.inputArguments(numEigen, K, M, 0, Q, minimumSpaceDimension(numEigen));
  if (info < 0)
    return info;

  int myPid = MyComm.MyPID();

  int localSize = Q.MyLength();
  int NCV = Q.NumVectors();
  int knownEV = 0;

  if (NCV > Q.GlobalLength()) {
    if (numEigen >= Q.GlobalLength()) {
      cerr << endl;
      cerr << " !! The number of requested eigenvalues must be smaller than the dimension";
      cerr << " of the matrix !!\n";
      cerr << endl;
      return -8;
    }
    NCV = Q.GlobalLength();
  }

  int localVerbose = verbose*(myPid == 0);

  // Define data for ARPACK
  highMem = (highMem > currentSize()) ? highMem : currentSize();

  int ido = 0;

  int lwI = 22 + NCV;
  int *wI = new (nothrow) int[lwI];
  if (wI == 0) {
    return -30;
  }
  memRequested += sizeof(int)*lwI/(1024.0*1024.0);

  int *iparam = wI;
  int *ipntr = wI + 11;
  int *select = wI + 22;

  int lworkl = NCV*(NCV+8);
  int lwD = lworkl + 4*localSize;
  double *wD = new (nothrow) double[lwD];
  if (wD == 0) {
    delete[] wI;
    return -30;
//.........这里部分代码省略.........

int ModifiedARPACKm3::reSolve(int numEigen, Epetra_MultiVector &Q, double *lambda, 
                              int startingEV, const Epetra_MultiVector *orthoVec) {

  // Computes the smallest eigenvalues and the corresponding eigenvectors
  // of the generalized eigenvalue problem
  // 
  //      K X = M X Lambda
  // 
  // using ModifiedARPACK (mode 3).
  //
  // The convergence test is performed outisde of ARPACK
  //
  //                      || Kx - Mx lambda || < tol*lambda
  //
  // The norm ||.|| can be specified by the user through the array normWeight.
  // By default, the L2 Euclidean norm is used.
  //
  // Note that if M is not specified, then  K X = X Lambda is solved.
  // (using the mode for generalized eigenvalue problem).
  // 
  // Input variables:
  // 
  // numEigen  (integer) = Number of eigenmodes requested
  // 
  // Q (Epetra_MultiVector) = Initial search space
  //                   The number of columns of Q defines the size of search space (=NCV).
  //                   The rows of X are distributed across processors.
  //                   As a rule of thumb in ARPACK User's guide, NCV >= 2*numEigen.
  //                   At exit, the first numEigen locations contain the eigenvectors requested.
  // 
  // lambda (array of doubles) = Converged eigenvalues
  //                   The length of this array is equal to the number of columns in Q.
  //                   At exit, the first numEigen locations contain the eigenvalues requested.
  // 
  // startingEV (integer) = Number of eigenmodes already stored in Q
  //                   A linear combination of these vectors is made to define the starting
  //                   vector, placed in resid.
  //
  // orthoVec (Pointer to Epetra_MultiVector) = Space to be orthogonal to
  //                   The computation is performed in the orthogonal of the space spanned
  //                   by the columns vectors in orthoVec.
  //
  // Return information on status of computation
  // 
  // info >=   0 >> Number of converged eigenpairs at the end of computation
  // 
  // // Failure due to input arguments
  // 
  // info = -  1 >> The stiffness matrix K has not been specified.
  // info = -  2 >> The maps for the matrix K and the matrix M differ.
  // info = -  3 >> The maps for the matrix K and the preconditioner P differ.
  // info = -  4 >> The maps for the vectors and the matrix K differ.
  // info = -  5 >> Q is too small for the number of eigenvalues requested.
  // info = -  6 >> Q is too small for the computation parameters.
  // 
  // info = -  8 >> numEigen must be smaller than the dimension of the matrix.
  //
  // info = - 30 >> MEMORY
  //
  // See ARPACK documentation for the meaning of INFO

  if (numEigen <= startingEV) {
    return numEigen;
  }

  int info = myVerify.inputArguments(numEigen, K, M, 0, Q, minimumSpaceDimension(numEigen));
  if (info < 0)
    return info;

  int myPid = MyComm.MyPID();

  int localSize = Q.MyLength();
  int NCV = Q.NumVectors();
  int knownEV = 0;

  if (NCV > Q.GlobalLength()) {
    if (numEigen >= Q.GlobalLength()) {
      cerr << endl;
      cerr << " !! The number of requested eigenvalues must be smaller than the dimension";
      cerr << " of the matrix !!\n";
      cerr << endl;
      return -8;
    }
    NCV = Q.GlobalLength();
  }

  // Get the weight for approximating the M-inverse norm
  Epetra_Vector *vectWeight = 0;
  if (normWeight) {
    vectWeight = new Epetra_Vector(View, Q.Map(), normWeight);
  }

  int localVerbose = verbose*(myPid == 0);

  // Define data for ARPACK
  //
  // UH (10/17/03) Note that workl is also used 
  //               * to store the eigenvectors of the tridiagonal matrix
  //               * as a workspace for DSTEQR
  //               * as a workspace for recovering the global eigenvectors
//.........这里部分代码省略.........