tempest/resources/3rdparty/gmm-4.2/include/gmm/gmm_MUMPS_interface.h

/* -*- c++ -*- (enables emacs c++ mode) */
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/**@file gmm_MUMPS_interface.h
   @author Yves Renard <Yves.Renard@insa-lyon.fr>,
   @author Julien Pommier <Julien.Pommier@insa-toulouse.fr>
   @date December 8, 2005.
   @brief Interface with MUMPS (LU direct solver for sparse matrices).
*/
#if defined(GMM_USES_MUMPS) || defined(HAVE_DMUMPS_C_H)

#ifndef GMM_MUMPS_INTERFACE_H
#define GMM_MUMPS_INTERFACE_H

#include "gmm_kernel.h"


extern "C" {

#include <smumps_c.h>
#undef F_INT
#undef F_DOUBLE
#undef F_DOUBLE2
#include <dmumps_c.h>
#undef F_INT
#undef F_DOUBLE
#undef F_DOUBLE2
#include <cmumps_c.h>
#undef F_INT
#undef F_DOUBLE
#undef F_DOUBLE2
#include <zmumps_c.h>
#undef F_INT
#undef F_DOUBLE
#undef F_DOUBLE2

}

namespace gmm {

  template <typename T> struct ij_sparse_matrix {
    std::vector<int> irn;
    std::vector<int> jcn;
    std::vector<T>        a;
    
    template <typename L> void store(const L& l, size_type i) {
       typename linalg_traits<L>::const_iterator it = vect_const_begin(l),
         ite = vect_const_end(l);
       for (; it != ite; ++it)
         { irn.push_back((int)i + 1); jcn.push_back((int)it.index() + 1); a.push_back(*it); }
    }

    template <typename L> void build_from(const L& l, row_major) {
      for (size_type i = 0; i < mat_nrows(l); ++i)
        store(mat_const_row(l, i), i);
    }

    template <typename L> void build_from(const L& l, col_major) {
      for (size_type i = 0; i < mat_ncols(l); ++i)
        store(mat_const_col(l, i), i);
      irn.swap(jcn);
    }

    template <typename L> ij_sparse_matrix(const L& A) {
      size_type nz = nnz(A);
      irn.reserve(nz); jcn.reserve(nz); a.reserve(nz);
      build_from(A,  typename principal_orientation_type<typename
               linalg_traits<L>::sub_orientation>::potype());
    }
  };

  /* ********************************************************************* */
  /*   MUMPS solve interface                                               */
  /* ********************************************************************* */


  template <typename T> struct mumps_interf {};

  template <> struct mumps_interf<float> {
    typedef SMUMPS_STRUC_C  MUMPS_STRUC_C;
    typedef float value_type;

    static void mumps_c(MUMPS_STRUC_C &id) { smumps_c(&id); }
  };

  template <> struct mumps_interf<double> {
    typedef DMUMPS_STRUC_C  MUMPS_STRUC_C;
    typedef double value_type;
    static void mumps_c(MUMPS_STRUC_C &id) { dmumps_c(&id); }
  };

  template <> struct mumps_interf<std::complex<float> > {
    typedef CMUMPS_STRUC_C  MUMPS_STRUC_C;
    typedef mumps_complex value_type;
    static void mumps_c(MUMPS_STRUC_C &id) { cmumps_c(&id); }
  };

  template <> struct mumps_interf<std::complex<double> > {
    typedef ZMUMPS_STRUC_C  MUMPS_STRUC_C;
    typedef mumps_double_complex value_type;
    static void mumps_c(MUMPS_STRUC_C &id) { zmumps_c(&id); }
  };


  /** MUMPS solve interface  
   *  Works only with sparse or skyline matrices
   */
  template <typename MAT, typename VECTX, typename VECTB>
  bool MUMPS_solve(const MAT &A, const VECTX &X_, const VECTB &B) {
    VECTX &X = const_cast<VECTX &>(X_);

    typedef typename linalg_traits<MAT>::value_type T;
    typedef typename mumps_interf<T>::value_type MUMPS_T;
    GMM_ASSERT2(gmm::mat_nrows(A) == gmm::mat_ncols(A), "Non square matrix");
  
    std::vector<T> rhs(gmm::vect_size(B)); gmm::copy(B, rhs);
  
    ij_sparse_matrix<T> AA(A);
  
    const int JOB_INIT = -1;
    const int JOB_END = -2;
    const int USE_COMM_WORLD = -987654;

    typename mumps_interf<T>::MUMPS_STRUC_C id;

#ifdef GMM_USES_MPI
    int rank;
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);
#endif
    
    id.job = JOB_INIT;
    id.par = 1;
    id.sym = 0;
    id.comm_fortran = USE_COMM_WORLD;
    mumps_interf<T>::mumps_c(id);
    
#ifdef GMM_USES_MPI
    if (rank == 0) {
#endif
      id.n = (int)gmm::mat_nrows(A);
      id.nz = (int)AA.irn.size();
      id.irn = &(AA.irn[0]);
      id.jcn = &(AA.jcn[0]);
      id.a = (MUMPS_T*)(&(AA.a[0]));
      id.rhs = (MUMPS_T*)(&(rhs[0]));
#ifdef GMM_USES_MPI
    }
#endif

#define ICNTL(I) icntl[(I)-1]
    id.ICNTL(1) = -1; // output stream for error messages
    id.ICNTL(2) = -1; // output stream for other messages
    id.ICNTL(3) = -1; // output stream for global information
    id.ICNTL(4) = 0;  // verbosity level
    
    id.ICNTL(14) += 80; /* small boost to the workspace size as we have encountered some problem
                           who did not fit in the default settings of mumps.. 
                           by default, ICNTL(14) = 15 or 20
                       */
    //cout << "ICNTL(14): " << id.ICNTL(14) << "\n";

    // id.ICNTL(22) = 1;   /* enables out-of-core support */

    id.job = 6;
    mumps_interf<T>::mumps_c(id);
    bool ok = mumps_error_check(id);

    id.job = JOB_END;
    mumps_interf<T>::mumps_c(id);

    gmm::copy(rhs, X);

    return ok;

#undef ICNTL

  }



  /** MUMPS solve interface for distributed matrices 
   *  Works only with sparse or skyline matrices
   */
  template <typename MAT, typename VECTX, typename VECTB>
  bool MUMPS_distributed_matrix_solve(const MAT &A, const VECTX &X_,
                                      const VECTB &B) {
    VECTX &X = const_cast<VECTX &>(X_);

    typedef typename linalg_traits<MAT>::value_type T;
    typedef typename mumps_interf<T>::value_type MUMPS_T;
    GMM_ASSERT2(gmm::mat_nrows(A) == gmm::mat_ncols(A), "Non-square matrix");
  
    std::vector<T> rhs(gmm::vect_size(B)); gmm::copy(B, rhs);

    ij_sparse_matrix<T> AA(A);
  
    const int JOB_INIT = -1;
    const int JOB_END = -2;
    const int USE_COMM_WORLD = -987654;

    typename mumps_interf<T>::MUMPS_STRUC_C id;

#ifdef GMM_USES_MPI
    int rank;
    MPI_Comm_rank(MPI_COMM_WORLD, &rank);
#endif
    
    id.job = JOB_INIT;
    id.par = 1;
    id.sym = 0;
    id.comm_fortran = USE_COMM_WORLD;
    mumps_interf<T>::mumps_c(id);
    
    id.n = gmm::mat_nrows(A);
    id.nz_loc = AA.irn.size();
    id.irn_loc = &(AA.irn[0]);
    id.jcn_loc = &(AA.jcn[0]);
    id.a_loc = (MUMPS_T*)(&(AA.a[0]));

#ifdef GMM_USES_MPI
    if (rank == 0) {
#endif
      id.rhs = (MUMPS_T*)(&(rhs[0]));
#ifdef GMM_USES_MPI
    }
#endif

#define ICNTL(I) icntl[(I)-1]
    id.ICNTL(1) = -1; // output stream for error messages
    id.ICNTL(2) = 6;  // id.ICNTL(2) = -1; // output stream for other messages
    id.ICNTL(3) = 6;  // id.ICNTL(3) = -1; // output stream for global information
    id.ICNTL(4) = 2;  // verbosity level

    id.ICNTL(5) = 0;  // assembled input matrix (default)
    id.ICNTL(18) = 3; // strategy for distributed input matrix

    id.job = 6;
    mumps_interf<T>::mumps_c(id);
    bool ok = mumps_error_check(id);

    id.job = JOB_END;
    mumps_interf<T>::mumps_c(id);
#ifdef GMM_USES_MPI
    MPI_Bcast(&(rhs[0]),id.n,gmm::mpi_type(T()),0,MPI_COMM_WORLD);
#endif
    gmm::copy(rhs, X);

    return ok;

#undef ICNTL

  }


  template <typename MUMPS_STRUCT>
  static inline bool mumps_error_check(MUMPS_STRUCT &id) {
#define INFO(I) info[(I)-1]
    if (id.INFO(1) < 0) {
      switch (id.INFO(1)) {
        case -2:
          GMM_ASSERT1(false, "Solve with MUMPS failed: NZ = " << id.INFO(2)
                      << " is out of range");
        case -6 : case -10 :
          GMM_WARNING1("Solve with MUMPS failed: matrix is singular");
          return false;
        case -9:
          GMM_ASSERT1(false, "Solve with MUMPS failed: error "
                      << id.INFO(1) << ", increase ICNTL(14)");
        case -13 :
          GMM_ASSERT1(false, "Solve with MUMPS failed: not enough memory");
        default :
          GMM_ASSERT1(false, "Solve with MUMPS failed with error "
                      << id.INFO(1));
      }
    }
    return true;
#undef INFO
  }


}

  
#endif // GMM_MUMPS_INTERFACE_H

#endif // GMM_USES_MUMPS