示例#1
0
// ================================================ ====== ==== ==== == =
// Apply the preconditioner to an Epetra_MultiVector X, puts the result in Y
int ML_Epetra::RefMaxwellPreconditioner::ApplyInverse(const Epetra_MultiVector& B, Epetra_MultiVector& X_) const
{
  int rv;
  /* Sanity Checks */
  if (!B.Map().SameAs(*DomainMap_)) ML_CHK_ERR(-1);
  if (B.NumVectors() != X_.NumVectors()) ML_CHK_ERR(-1);

  /* Check for zero RHS */
  bool norm0=true;
  double *norm=new double[B.NumVectors()];
  B.Norm2(norm);
  for(int i=0;norm0==true && i<B.NumVectors();i++) norm0=norm0 && (norm[i]==0);
  delete [] norm;
  if(norm0) return 0;

  /* Build new work vector X */
  Epetra_MultiVector X(X_.Map(),X_.NumVectors());
  X.PutScalar(0);

  /* What mode to run in? */
  if(mode=="212") rv=ApplyInverse_Implicit_212(B,X);
  else if(mode=="additive") rv=ApplyInverse_Implicit_Additive(B,X);
  else if(mode=="121") rv=ApplyInverse_Implicit_121(B,X);
  else {fprintf(stderr,"%s","RefMaxwellPreconditioner ERROR: Invalid ApplyInverse mode set in Teuchos list");ML_CHK_ERR(-2);}
  ML_CHK_ERR(rv);

  /* Copy work vector to output */
  X_=X;

  /* Timer Stuff */
#ifdef ML_TIMING
  ML_Epetra::RefMaxwellPreconditioner* This = const_cast<ML_Epetra::RefMaxwellPreconditioner *>(this);
  if(FirstApplication_){
    This->FirstApplication_=false;
    This->FirstApplicationTime_=ApplicationTime_;
  }/*end if*/
  This->NumApplications_++;
#endif

  return 0;
}/*end ApplyInverse*/
示例#2
0
int main(int argc, char *argv[])
{
#ifdef HAVE_MPI
    Teuchos::GlobalMPISession mpiSession(&argc, &argv, 0);
    Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
    Epetra_SerialComm Comm;
#endif
    int nProcs, myPID ;
    Teuchos::ParameterList pLUList ;        // ParaLU parameters
    Teuchos::ParameterList isoList ;        // Isorropia parameters
    Teuchos::ParameterList shyLUList ;    // shyLU parameters
    Teuchos::ParameterList ifpackList ;    // shyLU parameters
    string ipFileName = "ShyLU.xml";       // TODO : Accept as i/p

    nProcs = mpiSession.getNProc();
    myPID = Comm.MyPID();

    if (myPID == 0)
    {
        cout <<"Parallel execution: nProcs="<< nProcs << endl;
    }

    // =================== Read input xml file =============================
    Teuchos::updateParametersFromXmlFile(ipFileName, &pLUList);
    isoList = pLUList.sublist("Isorropia Input");
    shyLUList = pLUList.sublist("ShyLU Input");
    shyLUList.set("Outer Solver Library", "AztecOO");
    // Get matrix market file name
    string MMFileName = Teuchos::getParameter<string>(pLUList, "mm_file");
    string prec_type = Teuchos::getParameter<string>(pLUList, "preconditioner");
    int maxiters = Teuchos::getParameter<int>(pLUList, "Outer Solver MaxIters");
    double tol = Teuchos::getParameter<double>(pLUList, "Outer Solver Tolerance");
    string rhsFileName = pLUList.get<string>("rhs_file", "");

    if (myPID == 0)
    {
        cout << "Input :" << endl;
        cout << "ParaLU params " << endl;
        pLUList.print(std::cout, 2, true, true);
        cout << "Matrix market file name: " << MMFileName << endl;
    }

    // ==================== Read input Matrix ==============================
    Epetra_CrsMatrix *A;
    Epetra_MultiVector *b1;

    int err = EpetraExt::MatrixMarketFileToCrsMatrix(MMFileName.c_str(), Comm,
                                                        A);
    //EpetraExt::MatlabFileToCrsMatrix(MMFileName.c_str(), Comm, A);
    //assert(err != 0);
    //cout <<"Done reading the matrix"<< endl;
    int n = A->NumGlobalRows();
    //cout <<"n="<< n << endl;

    // Create input vectors
    Epetra_Map vecMap(n, 0, Comm);
    if (rhsFileName != "")
    {
        err = EpetraExt::MatrixMarketFileToMultiVector(rhsFileName.c_str(),
                                         vecMap, b1);
    }
    else
    {
        b1 = new Epetra_MultiVector(vecMap, 1, false);
        b1->PutScalar(1.0);
    }

    Epetra_MultiVector x(vecMap, 1);
    //cout << "Created the vectors" << endl;

    // Partition the matrix with hypergraph partitioning and redisstribute
    Isorropia::Epetra::Partitioner *partitioner = new
                            Isorropia::Epetra::Partitioner(A, isoList, false);
    partitioner->partition();
    Isorropia::Epetra::Redistributor rd(partitioner);

    Epetra_CrsMatrix *newA;
    Epetra_MultiVector *newX, *newB; 
    rd.redistribute(*A, newA);
    delete A;
    A = newA;

    rd.redistribute(x, newX);
    rd.redistribute(*b1, newB);

    Epetra_LinearProblem problem(A, newX, newB);

    AztecOO solver(problem);

    ifpackList ;
    Ifpack_Preconditioner *prec;
    ML_Epetra::MultiLevelPreconditioner *MLprec;
    if (prec_type.compare("ShyLU") == 0)
    {
        prec = new Ifpack_ShyLU(A);
        prec->SetParameters(shyLUList);
        prec->Initialize();
        prec->Compute();
        //(dynamic_cast<Ifpack_ShyLU *>(prec))->JustTryIt();
        //cout << " Going to set it in solver" << endl ;
        solver.SetPrecOperator(prec);
        //cout << " Done setting the solver" << endl ;
    }
    else if (prec_type.compare("ILU") == 0)
    {
        ifpackList.set( "fact: level-of-fill", 1 );
        prec = new Ifpack_ILU(A);
        prec->SetParameters(ifpackList);
        prec->Initialize();
        prec->Compute();
        solver.SetPrecOperator(prec);
    }
    else if (prec_type.compare("ILUT") == 0)
    {
        ifpackList.set( "fact: ilut level-of-fill", 2 );
        ifpackList.set( "fact: drop tolerance", 1e-8);
        prec = new Ifpack_ILUT(A);
        prec->SetParameters(ifpackList);
        prec->Initialize();
        prec->Compute();
        solver.SetPrecOperator(prec);
    }
    else if (prec_type.compare("ML") == 0)
    {
        Teuchos::ParameterList mlList; // TODO : Take it from i/p
        MLprec = new ML_Epetra::MultiLevelPreconditioner(*A, mlList, true);
        solver.SetPrecOperator(MLprec);
    }

    solver.SetAztecOption(AZ_solver, AZ_gmres);
    solver.SetMatrixName(333);
    //solver.SetAztecOption(AZ_output, 1);
    //solver.SetAztecOption(AZ_conv, AZ_Anorm);
    //cout << "Going to iterate for the global problem" << endl;

    solver.Iterate(maxiters, tol);

    // compute ||Ax - b||
    double Norm;
    Epetra_MultiVector Ax(vecMap, 1);

    Epetra_MultiVector *newAx; 
    rd.redistribute(Ax, newAx);
    A->Multiply(false, *newX, *newAx);
    newAx->Update(1.0, *newB, -1.0);
    newAx->Norm2(&Norm);
    double ANorm = A->NormOne();

    cout << "|Ax-b |/|A| = " << Norm/ANorm << endl;

    delete newAx;
    if (prec_type.compare("ML") == 0)
    {
        delete MLprec;
    }
    else
    {
        delete prec;
    }

    delete b1;
    delete newX;
    delete newB;
    delete A;
    delete partitioner;
}
//
//  Amesos_TestMultiSolver.cpp reads in a matrix in Harwell-Boeing format, 
//  calls one of the sparse direct solvers, using blocked right hand sides
//  and computes the error and residual.  
//
//  TestSolver ignores the Harwell-Boeing right hand sides, creating
//  random right hand sides instead.  
//
//  Amesos_TestMultiSolver can test either A x = b or A^T x = b.
//  This can be a bit confusing because sparse direct solvers 
//  use compressed column storage - the transpose of Trilinos'
//  sparse row storage.
//
//  Matrices:
//    readA - Serial.  As read from the file.
//    transposeA - Serial.  The transpose of readA.
//    serialA - if (transpose) then transposeA else readA 
//    distributedA - readA distributed to all processes
//    passA - if ( distributed ) then distributedA else serialA
//
//
int Amesos_TestMultiSolver( Epetra_Comm &Comm, char *matrix_file, int numsolves, 
		      SparseSolverType SparseSolver, bool transpose,
		      int special, AMESOS_MatrixType matrix_type ) {


  int iam = Comm.MyPID() ;

  
  //  int hatever;
  //  if ( iam == 0 )  std::cin >> hatever ; 
  Comm.Barrier();


  Epetra_Map * readMap;
  Epetra_CrsMatrix * readA; 
  Epetra_Vector * readx; 
  Epetra_Vector * readb;
  Epetra_Vector * readxexact;
   
  std::string FileName = matrix_file ;
  int FN_Size = FileName.size() ; 
  std::string LastFiveBytes = FileName.substr( EPETRA_MAX(0,FN_Size-5), FN_Size );
  std::string LastFourBytes = FileName.substr( EPETRA_MAX(0,FN_Size-4), FN_Size );
  bool NonContiguousMap = false; 

  if ( LastFiveBytes == ".triU" ) { 
    NonContiguousMap = true; 
    // Call routine to read in unsymmetric Triplet matrix
    EPETRA_CHK_ERR( Trilinos_Util_ReadTriples2Epetra( matrix_file, false, Comm, readMap, readA, readx, 
						      readb, readxexact, NonContiguousMap ) );
  } else {
    if ( LastFiveBytes == ".triS" ) { 
      NonContiguousMap = true; 
      // Call routine to read in symmetric Triplet matrix
      EPETRA_CHK_ERR( Trilinos_Util_ReadTriples2Epetra( matrix_file, true, Comm, 
							readMap, readA, readx, 
							readb, readxexact, NonContiguousMap ) );
    } else {
      if (  LastFourBytes == ".mtx" ) { 
	EPETRA_CHK_ERR( Trilinos_Util_ReadMatrixMarket2Epetra( matrix_file, Comm, readMap, 
							       readA, readx, readb, readxexact) );
      } else {
	// Call routine to read in HB problem
	Trilinos_Util_ReadHb2Epetra( matrix_file, Comm, readMap, readA, readx, 
						     readb, readxexact) ;
      }
    }
  }

  Epetra_CrsMatrix transposeA(Copy, *readMap, 0);
  Epetra_CrsMatrix *serialA ; 

  if ( transpose ) {
    assert( CrsMatrixTranspose( readA, &transposeA ) == 0 ); 
    serialA = &transposeA ; 
  } else {
    serialA = readA ; 
  }

  // Create uniform distributed map
  Epetra_Map map(readMap->NumGlobalElements(), 0, Comm);
  Epetra_Map* map_;

  if( NonContiguousMap ) {
    //
    //  map gives us NumMyElements and MyFirstElement;
    //
    int NumGlobalElements =  readMap->NumGlobalElements();
    int NumMyElements = map.NumMyElements();
    int MyFirstElement = map.MinMyGID();
    std::vector<int> MapMap_( NumGlobalElements );
    readMap->MyGlobalElements( &MapMap_[0] ) ;
    Comm.Broadcast( &MapMap_[0], NumGlobalElements, 0 ) ; 
    map_ = new Epetra_Map( NumGlobalElements, NumMyElements, &MapMap_[MyFirstElement], 0, Comm);
  } else {
    map_ = new Epetra_Map( map ) ; 
  }


  // Create Exporter to distribute read-in matrix and vectors
  Epetra_Export exporter(*readMap, *map_);
  Epetra_CrsMatrix A(Copy, *map_, 0);

  Epetra_RowMatrix * passA = 0; 
  Epetra_MultiVector * passx = 0; 
  Epetra_MultiVector * passb = 0;
  Epetra_MultiVector * passxexact = 0;
  Epetra_MultiVector * passresid = 0;
  Epetra_MultiVector * passtmp = 0;

  Epetra_MultiVector x(*map_,numsolves);
  Epetra_MultiVector b(*map_,numsolves);
  Epetra_MultiVector xexact(*map_,numsolves);
  Epetra_MultiVector resid(*map_,numsolves);
  Epetra_MultiVector tmp(*map_,numsolves);

  Epetra_MultiVector serialx(*readMap,numsolves);
  Epetra_MultiVector serialb(*readMap,numsolves);
  Epetra_MultiVector serialxexact(*readMap,numsolves);
  Epetra_MultiVector serialresid(*readMap,numsolves);
  Epetra_MultiVector serialtmp(*readMap,numsolves);

  bool distribute_matrix = ( matrix_type == AMESOS_Distributed ) ; 
  if ( distribute_matrix ) { 
    //
    //  Initialize x, b and xexact to the values read in from the file
    //
    
    A.Export(*serialA, exporter, Add);
    Comm.Barrier();

    assert(A.FillComplete()==0);    
    Comm.Barrier();

    passA = &A; 
    passx = &x; 
    passb = &b;
    passxexact = &xexact;
    passresid = &resid;
    passtmp = &tmp;
  } else { 
    passA = serialA; 
    passx = &serialx; 
    passb = &serialb;
    passxexact = &serialxexact;
    passresid = &serialresid;
    passtmp = &serialtmp;
  }

  passxexact->SetSeed(131) ; 
  passxexact->Random();
  passx->SetSeed(11231) ; 
  passx->Random();

  passb->PutScalar( 0.0 );
  passA->Multiply( transpose, *passxexact, *passb ) ; 

  Epetra_MultiVector CopyB( *passb ) ;

  double Anorm = passA->NormInf() ; 
  SparseDirectTimingVars::SS_Result.Set_Anorm(Anorm) ;

  Epetra_LinearProblem Problem(  (Epetra_RowMatrix *) passA, 
				 (Epetra_MultiVector *) passx, 
				 (Epetra_MultiVector *) passb );

  double max_resid = 0.0;
  for ( int j = 0 ; j < special+1 ; j++ ) { 
    
    Epetra_Time TotalTime( Comm ) ; 
    if ( false ) { 
#ifdef TEST_UMFPACK

      unused code

    } else if ( SparseSolver == UMFPACK ) { 
      UmfpackOO umfpack( (Epetra_RowMatrix *) passA, 
			 (Epetra_MultiVector *) passx, 
			 (Epetra_MultiVector *) passb ) ; 
    
      umfpack.SetTrans( transpose ) ; 
      umfpack.Solve() ; 
#endif
#ifdef TEST_SUPERLU
    } else if ( SparseSolver == SuperLU ) { 
      SuperluserialOO superluserial( (Epetra_RowMatrix *) passA, 
				     (Epetra_MultiVector *) passx, 
				     (Epetra_MultiVector *) passb ) ; 

      superluserial.SetPermc( SuperLU_permc ) ; 
      superluserial.SetTrans( transpose ) ; 
      superluserial.SetUseDGSSV( special == 0 ) ; 
      superluserial.Solve() ; 
#endif
#ifdef HAVE_AMESOS_SLUD
    } else if ( SparseSolver == SuperLUdist ) { 
      SuperludistOO superludist( Problem ) ; 
      superludist.SetTrans( transpose ) ; 
      EPETRA_CHK_ERR( superludist.Solve( true ) ) ;
#endif 
#ifdef HAVE_AMESOS_SLUD2
    } else if ( SparseSolver == SuperLUdist2 ) { 
      Superludist2_OO superludist2( Problem ) ; 
      superludist2.SetTrans( transpose ) ; 
      EPETRA_CHK_ERR( superludist2.Solve( true ) ) ;
#endif 
#ifdef TEST_SPOOLES
    } else if ( SparseSolver == SPOOLES ) { 
      SpoolesOO spooles( (Epetra_RowMatrix *) passA, 
			 (Epetra_MultiVector *) passx, 
			 (Epetra_MultiVector *) passb ) ; 
    
      spooles.SetTrans( transpose ) ; 
      spooles.Solve() ; 
#endif
#ifdef HAVE_AMESOS_DSCPACK
    } else if ( SparseSolver == DSCPACK ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Dscpack dscpack( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( dscpack.SetParameters( ParamList ) ); 
    
      EPETRA_CHK_ERR( dscpack.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_UMFPACK
    } else if ( SparseSolver == UMFPACK ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Umfpack umfpack( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( umfpack.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( umfpack.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( umfpack.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_KLU
    } else if ( SparseSolver == KLU ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Klu klu( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( klu.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( klu.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( klu.SymbolicFactorization(  ) ); 
      EPETRA_CHK_ERR( klu.NumericFactorization(  ) ); 
      EPETRA_CHK_ERR( klu.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_PARAKLETE
    } else if ( SparseSolver == PARAKLETE ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Paraklete paraklete( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( paraklete.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( paraklete.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( paraklete.SymbolicFactorization(  ) ); 
      EPETRA_CHK_ERR( paraklete.NumericFactorization(  ) ); 
      EPETRA_CHK_ERR( paraklete.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_SLUS
    } else if ( SparseSolver == SuperLU ) { 
      Epetra_SLU superluserial( &Problem ) ; 
      EPETRA_CHK_ERR( superluserial.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( superluserial.SymbolicFactorization(  ) ); 
      EPETRA_CHK_ERR( superluserial.NumericFactorization(  ) ); 

      EPETRA_CHK_ERR( superluserial.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_LAPACK
    } else if ( SparseSolver == LAPACK ) { 
      Teuchos::ParameterList ParamList ;
      ParamList.set( "MaxProcs", -3 );
      Amesos_Lapack lapack( Problem ) ; 
      EPETRA_CHK_ERR( lapack.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( lapack.SymbolicFactorization(  ) ); 
      EPETRA_CHK_ERR( lapack.NumericFactorization(  ) ); 
      EPETRA_CHK_ERR( lapack.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_TAUCS
    } else if ( SparseSolver == TAUCS ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Taucs taucs( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( taucs.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( taucs.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( taucs.SymbolicFactorization( ) ); 
      EPETRA_CHK_ERR( taucs.NumericFactorization( ) ); 
      EPETRA_CHK_ERR( taucs.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_PARDISO
    } else if ( SparseSolver == PARDISO ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Pardiso pardiso( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( pardiso.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( pardiso.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( pardiso.SymbolicFactorization( ) ); 
      EPETRA_CHK_ERR( pardiso.NumericFactorization( ) ); 
      EPETRA_CHK_ERR( pardiso.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_PARKLETE
    } else if ( SparseSolver == PARKLETE ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Parklete parklete( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( parklete.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( parklete.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( parklete.SymbolicFactorization( ) ); 
      EPETRA_CHK_ERR( parklete.NumericFactorization( ) ); 
      EPETRA_CHK_ERR( parklete.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_MUMPS
    } else if ( SparseSolver == MUMPS ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Mumps mumps( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( mumps.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( mumps.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( mumps.SymbolicFactorization( ) ); 
      EPETRA_CHK_ERR( mumps.NumericFactorization( ) ); 
      EPETRA_CHK_ERR( mumps.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_SCALAPACK
    } else if ( SparseSolver == SCALAPACK ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Scalapack scalapack( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( scalapack.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( scalapack.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( scalapack.SymbolicFactorization( ) ); 
      EPETRA_CHK_ERR( scalapack.NumericFactorization( ) ); 
      EPETRA_CHK_ERR( scalapack.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_SUPERLUDIST
    } else if ( SparseSolver == SUPERLUDIST ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Superludist superludist( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( superludist.SetParameters( ParamList ) ); 

      EPETRA_CHK_ERR( superludist.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( superludist.SymbolicFactorization(  ) ); 
      EPETRA_CHK_ERR( superludist.NumericFactorization(  ) ); 
      EPETRA_CHK_ERR( superludist.Solve( ) ); 
#endif
#ifdef HAVE_AMESOS_SUPERLU
    } else if ( SparseSolver == SUPERLU ) { 
      Teuchos::ParameterList ParamList ;
      Amesos_Superlu superlu( Problem ) ; 
      ParamList.set( "MaxProcs", -3 );
      EPETRA_CHK_ERR( superlu.SetParameters( ParamList ) ); 
      EPETRA_CHK_ERR( superlu.SetUseTranspose( transpose ) ); 
    
      EPETRA_CHK_ERR( superlu.SymbolicFactorization(  ) ); 
      EPETRA_CHK_ERR( superlu.NumericFactorization(  ) ); 
      EPETRA_CHK_ERR( superlu.Solve( ) ); 
#endif
#ifdef TEST_SPOOLESSERIAL 
    } else if ( SparseSolver == SPOOLESSERIAL ) { 
      SpoolesserialOO spoolesserial( (Epetra_RowMatrix *) passA, 
				     (Epetra_MultiVector *) passx, 
				     (Epetra_MultiVector *) passb ) ; 
    
      spoolesserial.Solve() ;
#endif
    } else { 
      SparseDirectTimingVars::log_file << "Solver not implemented yet" << std::endl ;
      std::cerr << "\n\n####################  Requested solver not available (Or not tested with blocked RHS) on this platform #####################\n" << std::endl ;
    }

    SparseDirectTimingVars::SS_Result.Set_Total_Time( TotalTime.ElapsedTime() ); 
    //    SparseDirectTimingVars::SS_Result.Set_First_Time( 0.0 ); 
    //    SparseDirectTimingVars::SS_Result.Set_Middle_Time( 0.0 ); 
    //    SparseDirectTimingVars::SS_Result.Set_Last_Time( 0.0 ); 

    //
    //  Compute the error = norm(xcomp - xexact )
    //
    std::vector <double> error(numsolves) ; 
    double max_error = 0.0;
  
    passresid->Update(1.0, *passx, -1.0, *passxexact, 0.0);

    passresid->Norm2(&error[0]);
    for ( int i = 0 ; i< numsolves; i++ ) 
      if ( error[i] > max_error ) max_error = error[i] ; 
    SparseDirectTimingVars::SS_Result.Set_Error(max_error) ;

    //  passxexact->Norm2(&error[0] ) ; 
    //  passx->Norm2(&error ) ; 

    //
    //  Compute the residual = norm(Ax - b)
    //
    std::vector <double> residual(numsolves) ; 
  
    passtmp->PutScalar(0.0);
    passA->Multiply( transpose, *passx, *passtmp);
    passresid->Update(1.0, *passtmp, -1.0, *passb, 0.0); 
    //    passresid->Update(1.0, *passtmp, -1.0, CopyB, 0.0); 
    passresid->Norm2(&residual[0]);

    for ( int i = 0 ; i< numsolves; i++ ) 
      if ( residual[i] > max_resid ) max_resid = residual[i] ; 


    SparseDirectTimingVars::SS_Result.Set_Residual(max_resid) ;
    
    std::vector <double> bnorm(numsolves); 
    passb->Norm2( &bnorm[0] ) ; 
    SparseDirectTimingVars::SS_Result.Set_Bnorm(bnorm[0]) ;

    std::vector <double> xnorm(numsolves); 
    passx->Norm2( &xnorm[0] ) ; 
    SparseDirectTimingVars::SS_Result.Set_Xnorm(xnorm[0]) ;


    if ( false && iam == 0 ) { 

      std::cout << " Amesos_TestMutliSolver.cpp " << std::endl ; 
      for ( int i = 0 ; i< numsolves && i < 10 ; i++ ) {
	std::cout << "i=" << i 
	     << " error = " << error[i] 
	     << " xnorm = " << xnorm[i] 
	     << " residual = " << residual[i] 
	     << " bnorm = " << bnorm[i] 
	     << std::endl ; 
      
      }
    
      std::cout << std::endl << " max_resid = " << max_resid ; 
      std::cout << " max_error = " << max_error << std::endl ; 
      std::cout << " Get_residual() again = " << SparseDirectTimingVars::SS_Result.Get_Residual() << std::endl ;

    }
  }
  delete readA;
  delete readx;
  delete readb;
  delete readxexact;
  delete readMap;
  delete map_;
  
  Comm.Barrier();

return 0 ;
}
示例#4
0
int main(int argc, char *argv[])
{
#ifdef HAVE_MPI
    Teuchos::GlobalMPISession mpiSession(&argc, &argv, 0);
    Epetra_MpiComm Comm(MPI_COMM_WORLD);
#else
    Epetra_SerialComm Comm;
#endif
    int nProcs, myPID ;
    Teuchos::ParameterList pLUList ;        // ParaLU parameters
    Teuchos::ParameterList isoList ;        // Isorropia parameters
    string ipFileName = "ShyLU.xml";       // TODO : Accept as i/p

    nProcs = mpiSession.getNProc();
    myPID = Comm.MyPID();

    if (myPID == 0)
    {
        cout <<"Parallel execution: nProcs="<< nProcs << endl;
    }

    // =================== Read input xml file =============================
    Teuchos::updateParametersFromXmlFile(ipFileName, &pLUList);
    isoList = pLUList.sublist("Isorropia Input");
    // Get matrix market file name
    string MMFileName = Teuchos::getParameter<string>(pLUList, "mm_file");
    string prec_type = Teuchos::getParameter<string>(pLUList, "preconditioner");

    if (myPID == 0)
    {
        cout << "Input :" << endl;
        cout << "ParaLU params " << endl;
        pLUList.print(std::cout, 2, true, true);
        cout << "Matrix market file name: " << MMFileName << endl;
    }

    // ==================== Read input Matrix ==============================
    Epetra_CrsMatrix *A;

    int err = EpetraExt::MatrixMarketFileToCrsMatrix(MMFileName.c_str(), Comm, A);
    //EpetraExt::MatlabFileToCrsMatrix(MMFileName.c_str(), Comm, A);
    //assert(err != 0);
    cout <<"Done reading the matrix"<< endl;
    int n = A->NumGlobalRows();
    cout <<"n="<< n << endl;

    // Create input vectors
    Epetra_Map vecMap(n, 0, Comm);
    Epetra_MultiVector x(vecMap, 1);
    Epetra_MultiVector b(vecMap, 1, false);
    b.PutScalar(1.0); // TODO : Accept it as input

    // Partition the matrix with hypergraph partitioning and redisstribute
    Isorropia::Epetra::Partitioner *partitioner = new
                            Isorropia::Epetra::Partitioner(A, isoList, false);
    partitioner->partition();
    Isorropia::Epetra::Redistributor rd(partitioner);

    Epetra_CrsMatrix *newA;
    Epetra_MultiVector *newX, *newB; 
    rd.redistribute(*A, newA);
    delete A;
    A = newA;

    rd.redistribute(x, newX);
    rd.redistribute(b, newB);

    Epetra_LinearProblem problem(A, newX, newB);

    Amesos Factory;
    char* SolverType = "Amesos_Klu";
    bool IsAvailable = Factory.Query(SolverType);

    Epetra_LinearProblem *LP = new Epetra_LinearProblem();
    LP->SetOperator(A);
    LP->SetLHS(newX);
    LP->SetRHS(newB);
    Amesos_BaseSolver *Solver = Factory.Create(SolverType, *LP);


    Solver->SymbolicFactorization();
  Teuchos::Time ftime("setup time");
      ftime.start();
    Solver->NumericFactorization();
    cout << "Numeric Factorization" << endl;
    Solver->Solve();
    cout << "Solve done" << endl;

    ftime.stop();
    cout << "Time to setup" << ftime.totalElapsedTime() << endl;

    // compute ||Ax - b||
    double Norm;
    Epetra_MultiVector Ax(vecMap, 1);

    Epetra_MultiVector *newAx; 
    rd.redistribute(Ax, newAx);
    A->Multiply(false, *newX, *newAx);
    newAx->Update(1.0, *newB, -1.0);
    newAx->Norm2(&Norm);
    double ANorm = A->NormOne();

    cout << "|Ax-b |/|A| = " << Norm/ANorm << endl;

    delete newAx;
    delete newX;
    delete newB;
    delete A;
    delete partitioner;
}