Actual source code: mpiaij.h

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

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

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

     31:   Mat_Merge_SeqsToMPI *merge;
     32: } Mat_APMPI;

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

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

     54:   /* The following variables are used for matrix-vector products */
     55:   Vec        lvec;                 /* local vector */
     56:   Vec        diag;
     57:   VecScatter Mvctx;                /* scatter context for vector */
     58:   PetscBool  roworiented;          /* if true, row-oriented input, default true */

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

     65:   PetscInt *ld;                    /* number of entries per row left of diagonal block */

     67:   /* Used by device classes */
     68:   void * spptr;

     70: } Mat_MPIAIJ;

     72: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat);

     74: PETSC_INTERN PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat,MatAssemblyType);

     76: PETSC_INTERN PetscErrorCode MatSetUpMultiply_MPIAIJ(Mat);
     77: PETSC_INTERN PetscErrorCode MatDisAssemble_MPIAIJ(Mat);
     78: PETSC_INTERN PetscErrorCode MatDuplicate_MPIAIJ(Mat,MatDuplicateOption,Mat*);
     79: PETSC_INTERN PetscErrorCode MatIncreaseOverlap_MPIAIJ(Mat,PetscInt,IS [],PetscInt);
     80: PETSC_INTERN PetscErrorCode MatIncreaseOverlap_MPIAIJ_Scalable(Mat,PetscInt,IS [],PetscInt);
     81: PETSC_INTERN PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat,ISColoring,MatFDColoring);
     82: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat,ISColoring,MatFDColoring);
     83: PETSC_INTERN PetscErrorCode MatCreateSubMatrices_MPIAIJ (Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
     84: PETSC_INTERN PetscErrorCode MatCreateSubMatricesMPI_MPIAIJ (Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
     85: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_All(Mat,MatCreateSubMatrixOption,MatReuse,Mat *[]);
     86: PETSC_INTERN PetscErrorCode MatView_MPIAIJ(Mat,PetscViewer);

     88: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat,IS,IS,MatReuse,Mat*);
     89: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat,IS,IS,PetscInt,MatReuse,Mat*);
     90: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat,IS,IS,IS,MatReuse,Mat*);
     91: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat,IS,IS,MatReuse,Mat*);
     92: PETSC_INTERN PetscErrorCode MatGetMultiProcBlock_MPIAIJ(Mat,MPI_Comm,MatReuse,Mat*);

     94: PETSC_INTERN PetscErrorCode MatLoad_MPIAIJ(Mat,PetscViewer);
     95: PETSC_INTERN PetscErrorCode MatLoad_MPIAIJ_Binary(Mat,PetscViewer);
     96: PETSC_INTERN PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat);

     98: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIAIJ(Mat);
     99: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_MPIAIJBACKEND(Mat);
    100: PETSC_INTERN PetscErrorCode MatProductSymbolic_MPIAIJBACKEND(Mat);
    101: PETSC_INTERN PetscErrorCode MatProductSymbolic_AB_MPIAIJ_MPIAIJ(Mat);

    103: PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_MPIAIJ_MPIAIJ(Mat);

    105: PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_MPIAIJ_MPIAIJ(Mat);
    106: PETSC_INTERN PetscErrorCode MatProductNumeric_RARt_MPIAIJ_MPIAIJ(Mat);

    108: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,PetscReal,Mat);
    109: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_seqMPI(Mat,Mat,PetscReal,Mat);
    110: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat);
    111: PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);
    112: PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,Mat);

    114: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,PetscReal,Mat);
    115: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,Mat);

    117: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat);
    118: PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);

    120: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable(Mat,Mat,PetscReal,Mat);
    121: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_allatonce(Mat,Mat,PetscReal,Mat);
    122: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_allatonce_merged(Mat,Mat,PetscReal,Mat);
    123: PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_scalable(Mat,Mat,Mat);
    124: PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_allatonce(Mat,Mat,Mat);
    125: PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_allatonce_merged(Mat,Mat,Mat);

    127: #if defined(PETSC_HAVE_HYPRE)
    128: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat);
    129: #endif
    130: PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIDense(Mat,MatType,MatReuse,Mat*);
    131: #if defined(PETSC_HAVE_SCALAPACK)
    132: PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
    133: #endif

    135: PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ(Mat);
    136: PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ_PtAP(void*);
    137: PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ_MatMatMult(void*);

    139: PETSC_INTERN PetscErrorCode MatGetBrowsOfAoCols_MPIAIJ(Mat,Mat,MatReuse,PetscInt**,PetscInt**,MatScalar**,Mat*);
    140: PETSC_INTERN PetscErrorCode MatSetValues_MPIAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar [],InsertMode);
    141: PETSC_INTERN PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat(Mat,const PetscInt[],const PetscInt[],const PetscScalar[]);
    142: PETSC_INTERN PetscErrorCode MatSetValues_MPIAIJ_CopyFromCSRFormat_Symbolic(Mat,const PetscInt[],const PetscInt[]);
    143: PETSC_INTERN PetscErrorCode MatSetOption_MPIAIJ(Mat,MatOption,PetscBool);

    145: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,PetscReal,Mat);
    146: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat);
    147: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);
    148: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,Mat);
    149: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_matmatmult(Mat,Mat,Mat);
    150: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIDense(Mat,Mat,PetscReal,Mat);
    151: PETSC_INTERN PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat,Mat*);

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

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

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

    164: extern PetscErrorCode MatGetDiagonalBlock_MPIAIJ(Mat,Mat*);
    165: extern PetscErrorCode MatDiagonalScaleLocal_MPIAIJ(Mat,Vec);

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

    170: /* compute apa = A[i,:]*P = Ad[i,:]*P_loc + Ao*[i,:]*P_oth using sparse axpy */
    171: #define AProw_scalable(i,ad,ao,p_loc,p_oth,api,apj,apa) \
    172: {\
    173:   PetscInt    _anz,_pnz,_j,_k,*_ai,*_aj,_row,*_pi,*_pj,_nextp,*_apJ;\
    174:   PetscScalar *_aa,_valtmp,*_pa;\
    175:   _apJ = apj + api[i];\
    176:   /* diagonal portion of A */\
    177:   _ai  = ad->i;\
    178:   _anz = _ai[i+1] - _ai[i];\
    179:   _aj  = ad->j + _ai[i];\
    180:   _aa  = ad->a + _ai[i];\
    181:   for (_j=0; _j<_anz; _j++) {\
    182:     _row = _aj[_j]; \
    183:     _pi  = p_loc->i;                             \
    184:     _pnz = _pi[_row+1] - _pi[_row];              \
    185:     _pj  = p_loc->j + _pi[_row];                 \
    186:     _pa  = p_loc->a + _pi[_row];                 \
    187:     /* perform sparse axpy */                    \
    188:     _valtmp = _aa[_j];                           \
    189:     _nextp  = 0; \
    190:     for (_k=0; _nextp<_pnz; _k++) {                    \
    191:       if (_apJ[_k] == _pj[_nextp]) { /* column of AP == column of P */\
    192:         apa[_k] += _valtmp*_pa[_nextp++];                             \
    193:       } \
    194:     }                                           \
    195:     (void)PetscLogFlops(2.0*_pnz);              \
    196:   }                                             \
    197:   /* off-diagonal portion of A */               \
    198:   if (p_oth){ \
    199:     _ai  = ao->i;\
    200:     _anz = _ai[i+1] - _ai[i];                   \
    201:     _aj  = ao->j + _ai[i];                      \
    202:     _aa  = ao->a + _ai[i];                      \
    203:     for (_j=0; _j<_anz; _j++) {                 \
    204:       _row = _aj[_j];    \
    205:       _pi  = p_oth->i;                         \
    206:       _pnz = _pi[_row+1] - _pi[_row];          \
    207:       _pj  = p_oth->j + _pi[_row];             \
    208:       _pa  = p_oth->a + _pi[_row];             \
    209:       /* perform sparse axpy */                \
    210:       _valtmp = _aa[_j];                       \
    211:       _nextp  = 0; \
    212:       for (_k=0; _nextp<_pnz; _k++) {          \
    213:         if (_apJ[_k] == _pj[_nextp]) { /* column of AP == column of P */\
    214:           apa[_k] += _valtmp*_pa[_nextp++];    \
    215:         }                                      \
    216:       }                                        \
    217:       (void)PetscLogFlops(2.0*_pnz);           \
    218:     } \
    219:   }\
    220: }

    222: #define AProw_nonscalable(i,ad,ao,p_loc,p_oth,apa) \
    223: {\
    224:   PetscInt    _anz,_pnz,_j,_k,*_ai,*_aj,_row,*_pi,*_pj;\
    225:   PetscScalar *_aa,_valtmp,*_pa;                       \
    226:   /* diagonal portion of A */\
    227:   _ai  = ad->i;\
    228:   _anz = _ai[i+1] - _ai[i];\
    229:   _aj  = ad->j + _ai[i];\
    230:   _aa  = ad->a + _ai[i];\
    231:   for (_j=0; _j<_anz; _j++) {\
    232:     _row = _aj[_j]; \
    233:     _pi  = p_loc->i;                        \
    234:     _pnz = _pi[_row+1] - _pi[_row];         \
    235:     _pj  = p_loc->j + _pi[_row];            \
    236:     _pa  = p_loc->a + _pi[_row];            \
    237:     /* perform dense axpy */                \
    238:     _valtmp = _aa[_j];                      \
    239:     for (_k=0; _k<_pnz; _k++) {             \
    240:       apa[_pj[_k]] += _valtmp*_pa[_k];      \
    241:     }                                       \
    242:     (void)PetscLogFlops(2.0*_pnz);          \
    243:   }                                         \
    244:   /* off-diagonal portion of A */           \
    245:   if (p_oth){ \
    246:     _ai  = ao->i;\
    247:     _anz = _ai[i+1] - _ai[i];               \
    248:     _aj  = ao->j + _ai[i];                  \
    249:     _aa  = ao->a + _ai[i];                  \
    250:     for (_j=0; _j<_anz; _j++) {             \
    251:       _row = _aj[_j];    \
    252:       _pi  = p_oth->i;                      \
    253:       _pnz = _pi[_row+1] - _pi[_row];       \
    254:       _pj  = p_oth->j + _pi[_row];          \
    255:       _pa  = p_oth->a + _pi[_row];          \
    256:       /* perform dense axpy */              \
    257:       _valtmp = _aa[_j];                    \
    258:       for (_k=0; _k<_pnz; _k++) {           \
    259:         apa[_pj[_k]] += _valtmp*_pa[_k];    \
    260:       }                                     \
    261:       (void)PetscLogFlops(2.0*_pnz);        \
    262:     }                                       \
    263:   }\
    264: }

    266: #endif