getfem_superlu.h

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/* -*- c++ -*- (enables emacs c++ mode) */
/*===========================================================================
 
 Copyright (C) 2004-2020 Julien Pommier
 
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/**@file getfem_superlu.h
   @author  Julien Pommier <Julien.Pommier@insa-toulouse.fr>
   @date August 2004.
   @brief SuperLU interface for getfem
   
   We do not use gmm_superlu_interface.h for a good reason. This file
   does not include any of the superlu headers, hence when getfem is
   installed, it does not need to install the superlu headers.
*/
 
#ifndef GETFEM_SUPERLU
#define GETFEM_SUPERLU
#ifndef GMM_USES_SUPERLU
#define GMM_USES_SUPERLU
#endif
#include "getfem_config.h"
#include "gmm/gmm_kernel.h"
 
namespace gmm {
 
  template<typename T>
  int SuperLU_solve(const gmm::csc_matrix<T> &A, T *X_, T *B, double& rcond_, int permc_spec = 3);
  /** solve a sparse linear system AX=B (float, double, complex<float>
      or complex<double>) via SuperLU.
 
      @param A the matrix (a copy is made if A is not a gmm::csc_matrix)
      @param X the solution.
      @param B the right hand side.
      @param rcond_ contains on output an estimate of the condition number of A.
      @param permc_spec specify the kind of renumbering than SuperLU should do.
  */
  template<typename MAT, typename V1, typename V2>
  int SuperLU_solve(const MAT &A, const V1& X, const V2& B, double& rcond_, int permc_spec = 3) {
    typedef typename gmm::linalg_traits<MAT>::value_type T;
    
    int m = int(mat_nrows(A)), n = int(mat_ncols(A));
    gmm::csc_matrix<T> csc_A(m,n); 
    gmm::copy(A,csc_A);
    std::vector<T> rhs(m), sol(m);
    gmm::copy(B, rhs);
    
    int info = SuperLU_solve(csc_A, &sol[0], &rhs[0], rcond_, permc_spec);
    gmm::copy(sol, const_cast<V1 &>(X));
    return info;
  }
  
  struct SuperLU_factor_impl_common;
 
  /** Factorization of a sparse matrix with SuperLU.
      
      This class can be used as a preconditioner for gmm iterative solvers.
  */
  template <class T> class SuperLU_factor {
    std::shared_ptr<SuperLU_factor_impl_common> impl;
  public :
    enum { LU_NOTRANSP, LU_TRANSP, LU_CONJUGATED };
 
    /** Do the factorization of the supplied sparse matrix. */
    template <class MAT> void build_with(const MAT &A,  int permc_spec = 3) {
      int m = int(mat_nrows(A)), n = int(mat_ncols(A));
      gmm::csc_matrix<T> csc_A(m,n); 
      gmm::copy(A,csc_A);
      build_with(csc_A, permc_spec);
    }
    void build_with(const gmm::csc_matrix<T> &A, int permc_spec = 3);
    template <typename VECTX, typename VECTB> 
    /** After factorization, do the triangular solves.
       transp = LU_NOTRANSP   -> solves Ax = B
       transp = LU_TRANSP     -> solves A'x = B
       transp = LU_CONJUGATED -> solves conj(A)X = B 
    */
    void solve(const VECTX &X, const VECTB &B, int transp=LU_NOTRANSP) const {
      gmm::copy(B, rhs());
      solve(transp);
      gmm::copy(sol(),const_cast<VECTX &>(X));
    }
    void solve(int transp=LU_NOTRANSP) const;
    std::vector<T> &sol() const;
    std::vector<T> &rhs() const;
    SuperLU_factor();
    float memsize() const;
    SuperLU_factor(const SuperLU_factor& other);
    SuperLU_factor& operator=(const SuperLU_factor& other);
  };
 
  template <typename T, typename V1, typename V2> inline
  void mult(const SuperLU_factor<T>& P, const V1 &v1, const V2 &v2) {
    P.solve(v2,v1);
  }
 
  template <typename T, typename V1, typename V2> inline
  void transposed_mult(const SuperLU_factor<T>& P,const V1 &v1,const V2 &v2) {
    P.solve(v2, v1, SuperLU_factor<T>::LU_TRANSP);
  }
}
 
extern "C" void set_superlu_callback(int (*cb)());
 
#endif