#if !defined(__MPIAIJ_H)
#define __MPIAIJ_H

#include <../src/mat/impls/aij/seq/aij.h>

typedef struct { /* used by MatCreateMPIAIJSumSeqAIJ for reusing the merged matrix */
  PetscLayout rowmap;
  PetscInt    **buf_ri,**buf_rj;
  PetscMPIInt *len_s,*len_r,*id_r;    /* array of length of comm->size, store send/recv matrix values */
  PetscMPIInt nsend,nrecv;
  PetscInt    *bi,*bj;    /* i and j array of the local portion of mpi C (matrix product) - rename to ci, cj! */
  PetscInt    *owners_co,*coi,*coj;    /* i and j array of (p->B)^T*A*P - used in the communication */
} Mat_Merge_SeqsToMPI;

typedef struct { /* used by MatPtAPXXX_MPIAIJ_MPIAIJ() and MatMatMultXXX_MPIAIJ_MPIAIJ() */
  PetscInt               *startsj_s,*startsj_r;    /* used by MatGetBrowsOfAoCols_MPIAIJ */
  PetscScalar            *bufa;                    /* used by MatGetBrowsOfAoCols_MPIAIJ */
  Mat                     P_loc,P_oth;             /* partial B_seq -- intend to replace B_seq */
  PetscInt                *api,*apj;               /* symbolic i and j arrays of the local product A_loc*B_seq */
  PetscScalar             *apv;
  MatReuse                reuse;                   /* flag to skip MatGetBrowsOfAoCols_MPIAIJ() and MatMPIAIJGetLocalMat() in 1st call of MatPtAPNumeric_MPIAIJ_MPIAIJ() */
  PetscScalar             *apa;                    /* tmp array for store a row of A*P used in MatMatMult() */
  Mat                     A_loc;                   /* used by MatTransposeMatMult(), contains api and apj */
  ISLocalToGlobalMapping  ltog;                    /* mapping from local column indices to global column indices for A_loc */
  Mat                     Pt;                      /* used by MatTransposeMatMult(), Pt = P^T */
  Mat                     Rd,Ro,AP_loc,C_loc,C_oth;
  PetscInt                algType;                 /* implementation algorithm */
  PetscSF                 sf;                      /* use it to communicate remote part of C */
  PetscInt                *c_othi,*c_rmti;

  Mat_Merge_SeqsToMPI *merge;
} Mat_APMPI;

typedef struct {
  Mat A,B;                             /* local submatrices: A (diag part),
                                           B (off-diag part) */
  PetscMPIInt size;                     /* size of communicator */
  PetscMPIInt rank;                     /* rank of proc in communicator */

  /* The following variables are used for matrix assembly */
  PetscBool   donotstash;               /* PETSC_TRUE if off processor entries dropped */
  MPI_Request *send_waits;              /* array of send requests */
  MPI_Request *recv_waits;              /* array of receive requests */
  PetscInt    nsends,nrecvs;           /* numbers of sends and receives */
  PetscScalar *svalues,*rvalues;       /* sending and receiving data */
  PetscInt    rmax;                     /* maximum message length */
#if defined(PETSC_USE_CTABLE)
  PetscTable colmap;
#else
  PetscInt *colmap;                     /* local col number of off-diag col */
#endif
  PetscInt *garray;                     /* global index of all off-processor columns */

  /* The following variables are used for matrix-vector products */
  Vec        lvec;                 /* local vector */
  Vec        diag;
  VecScatter Mvctx,Mvctx_mpi1;     /* scatter context for vector */
  PetscBool  Mvctx_mpi1_flg;       /* if true, additional Mvctx_mpi1 is requested for mat-mat ops, default false */
  PetscBool  roworiented;          /* if true, row-oriented input, default true */

  /* The following variables are for MatGetRow() */
  PetscInt    *rowindices;         /* column indices for row */
  PetscScalar *rowvalues;          /* nonzero values in row */
  PetscBool   getrowactive;        /* indicates MatGetRow(), not restored */

  /* Used by MatDistribute_MPIAIJ() to allow reuse of previous matrix allocation  and nonzero pattern */
  PetscInt *ld;                    /* number of entries per row left of diagona block */

  /* Used by MPICUSPARSE classes */
  void * spptr;

} Mat_MPIAIJ;

PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat);

PETSC_INTERN PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat,MatAssemblyType);

PETSC_INTERN PetscErrorCode MatSetUpMultiply_MPIAIJ(Mat);
PETSC_INTERN PetscErrorCode MatDisAssemble_MPIAIJ(Mat);
PETSC_INTERN PetscErrorCode MatDuplicate_MPIAIJ(Mat,MatDuplicateOption,Mat*);
PETSC_INTERN PetscErrorCode MatIncreaseOverlap_MPIAIJ(Mat,PetscInt,IS [],PetscInt);
PETSC_INTERN PetscErrorCode MatIncreaseOverlap_MPIAIJ_Scalable(Mat,PetscInt,IS [],PetscInt);
PETSC_INTERN PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat,ISColoring,MatFDColoring);
PETSC_INTERN PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat,ISColoring,MatFDColoring);
PETSC_INTERN PetscErrorCode MatCreateSubMatrices_MPIAIJ (Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
PETSC_INTERN PetscErrorCode MatCreateSubMatricesMPI_MPIAIJ (Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_All(Mat,MatCreateSubMatrixOption,MatReuse,Mat *[]);
PETSC_INTERN PetscErrorCode MatView_MPIAIJ(Mat,PetscViewer);

PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat,IS,IS,MatReuse,Mat*);
PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat,IS,IS,PetscInt,MatReuse,Mat*);
PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat,IS,IS,IS,MatReuse,Mat*);
PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat,IS,IS,MatReuse,Mat*);
PETSC_INTERN PetscErrorCode MatGetMultiProcBlock_MPIAIJ(Mat,MPI_Comm,MatReuse,Mat*);

PETSC_INTERN PetscErrorCode MatLoad_MPIAIJ(Mat,PetscViewer);
PETSC_INTERN PetscErrorCode MatLoad_MPIAIJ_Binary(Mat,PetscViewer);
PETSC_INTERN PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat);

PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIAIJ(Mat);
PETSC_INTERN PetscErrorCode MatProductSymbolic_AB_MPIAIJ_MPIAIJ(Mat);

PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_MPIAIJ_MPIAIJ(Mat);

PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_MPIAIJ_MPIAIJ(Mat);
PETSC_INTERN PetscErrorCode MatProductNumeric_RARt_MPIAIJ_MPIAIJ(Mat);

PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_seqMPI(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);
PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,Mat);

PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,Mat);

PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);

PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_allatonce(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_allatonce_merged(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_scalable(Mat,Mat,Mat);
PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_allatonce(Mat,Mat,Mat);
PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_allatonce_merged(Mat,Mat,Mat);

#if defined(PETSC_HAVE_HYPRE)
PETSC_INTERN PetscErrorCode MatPtAPSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat);
#endif

PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ(Mat);
PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ_PtAP(void*);
PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ_MatMatMult(void*);

PETSC_INTERN PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat,Mat,MatReuse,PetscInt**,PetscInt**,MatScalar**,Mat*);
PETSC_INTERN PetscErrorCode MatSetValues_MPIAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar [],InsertMode);
PETSC_INTERN PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]);
PETSC_INTERN PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat,const PetscInt[],const PetscInt[]);
PETSC_INTERN PetscErrorCode MatSetOption_MPIAIJ(Mat,MatOption,PetscBool);

PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);
PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,Mat);
PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_matmatmult(Mat,Mat,Mat);
PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIDense(Mat,Mat,PetscReal,Mat);
PETSC_INTERN PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat,Mat*);

PETSC_INTERN PetscErrorCode MatSetFromOptions_MPIAIJ(PetscOptionItems*,Mat);
PETSC_INTERN PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]);

#if !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_REAL_SINGLE) && !defined(PETSC_USE_REAL___FLOAT128) && !defined(PETSC_USE_REAL___FP16)
PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_MPIAIJ_TFS(Mat,IS,IS,const MatFactorInfo*,Mat*);
#endif
PETSC_INTERN PetscErrorCode MatSolve_MPIAIJ(Mat,Vec,Vec);
PETSC_INTERN PetscErrorCode MatILUFactor_MPIAIJ(Mat,IS,IS,const MatFactorInfo*);

PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_MPIX_private(PetscInt,const PetscInt*,const PetscInt*,const PetscInt*,const PetscInt*,const PetscInt*,const PetscInt*,PetscInt*);

extern PetscErrorCode MatGetDiagonalBlock_MPIAIJ(Mat,Mat*);
extern PetscErrorCode MatDiagonalScaleLocal_MPIAIJ(Mat,Vec);

PETSC_INTERN PetscErrorCode MatGetSeqMats_MPIAIJ(Mat,Mat*,Mat*);
PETSC_INTERN PetscErrorCode MatSetSeqMats_MPIAIJ(Mat,IS,IS,IS,MatStructure,Mat,Mat);

/* compute apa = A[i,:]*P = Ad[i,:]*P_loc + Ao*[i,:]*P_oth using sparse axpy */
#define AProw_scalable(i,ad,ao,p_loc,p_oth,api,apj,apa) \
{\
  PetscInt    _anz,_pnz,_j,_k,*_ai,*_aj,_row,*_pi,*_pj,_nextp,*_apJ;\
  PetscScalar *_aa,_valtmp,*_pa;\
  _apJ = apj + api[i];\
  /* diagonal portion of A */\
  _ai  = ad->i;\
  _anz = _ai[i+1] - _ai[i];\
  _aj  = ad->j + _ai[i];\
  _aa  = ad->a + _ai[i];\
  for (_j=0; _j<_anz; _j++) {\
    _row = _aj[_j]; \
    _pi  = p_loc->i;                             \
    _pnz = _pi[_row+1] - _pi[_row];              \
    _pj  = p_loc->j + _pi[_row];                 \
    _pa  = p_loc->a + _pi[_row];                 \
    /* perform sparse axpy */                    \
    _valtmp = _aa[_j];                           \
    _nextp  = 0; \
    for (_k=0; _nextp<_pnz; _k++) {                    \
      if (_apJ[_k] == _pj[_nextp]) { /* column of AP == column of P */\
        apa[_k] += _valtmp*_pa[_nextp++];                             \
      } \
    }                                           \
    (void)PetscLogFlops(2.0*_pnz);              \
  }                                             \
  /* off-diagonal portion of A */               \
  if (p_oth){ \
    _ai  = ao->i;\
    _anz = _ai[i+1] - _ai[i];                   \
    _aj  = ao->j + _ai[i];                      \
    _aa  = ao->a + _ai[i];                      \
    for (_j=0; _j<_anz; _j++) {                 \
      _row = _aj[_j];    \
      _pi  = p_oth->i;                         \
      _pnz = _pi[_row+1] - _pi[_row];          \
      _pj  = p_oth->j + _pi[_row];             \
      _pa  = p_oth->a + _pi[_row];             \
      /* perform sparse axpy */                \
      _valtmp = _aa[_j];                       \
      _nextp  = 0; \
      for (_k=0; _nextp<_pnz; _k++) {          \
        if (_apJ[_k] == _pj[_nextp]) { /* column of AP == column of P */\
          apa[_k] += _valtmp*_pa[_nextp++];    \
        }                                      \
      }                                        \
      (void)PetscLogFlops(2.0*_pnz);           \
    } \
  }\
}

#define AProw_nonscalable(i,ad,ao,p_loc,p_oth,apa) \
{\
  PetscInt    _anz,_pnz,_j,_k,*_ai,*_aj,_row,*_pi,*_pj;\
  PetscScalar *_aa,_valtmp,*_pa;                       \
  /* diagonal portion of A */\
  _ai  = ad->i;\
  _anz = _ai[i+1] - _ai[i];\
  _aj  = ad->j + _ai[i];\
  _aa  = ad->a + _ai[i];\
  for (_j=0; _j<_anz; _j++) {\
    _row = _aj[_j]; \
    _pi  = p_loc->i;                        \
    _pnz = _pi[_row+1] - _pi[_row];         \
    _pj  = p_loc->j + _pi[_row];            \
    _pa  = p_loc->a + _pi[_row];            \
    /* perform dense axpy */                \
    _valtmp = _aa[_j];                      \
    for (_k=0; _k<_pnz; _k++) {             \
      apa[_pj[_k]] += _valtmp*_pa[_k];      \
    }                                       \
    (void)PetscLogFlops(2.0*_pnz);          \
  }                                         \
  /* off-diagonal portion of A */           \
  if (p_oth){ \
    _ai  = ao->i;\
    _anz = _ai[i+1] - _ai[i];               \
    _aj  = ao->j + _ai[i];                  \
    _aa  = ao->a + _ai[i];                  \
    for (_j=0; _j<_anz; _j++) {             \
      _row = _aj[_j];    \
      _pi  = p_oth->i;                      \
      _pnz = _pi[_row+1] - _pi[_row];       \
      _pj  = p_oth->j + _pi[_row];          \
      _pa  = p_oth->a + _pi[_row];          \
      /* perform dense axpy */              \
      _valtmp = _aa[_j];                    \
      for (_k=0; _k<_pnz; _k++) {           \
        apa[_pj[_k]] += _valtmp*_pa[_k];    \
      }                                     \
      (void)PetscLogFlops(2.0*_pnz);        \
    }                                       \
  }\
}

#endif