Actual source code: mpiaij.h

petsc-3.10.5 2019-03-28
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  5:  #include <../src/mat/impls/aij/seq/aij.h>

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

 18: typedef struct { /* used by MatPtAP_MPIAIJ_MPIAIJ() and MatMatMult_MPIAIJ_MPIAIJ() */
 19:   PetscInt    *startsj_s,*startsj_r;    /* used by MatGetBrowsOfAoCols_MPIAIJ */
 20:   PetscScalar *bufa;                    /* used by MatGetBrowsOfAoCols_MPIAIJ */
 21:   Mat         P_loc,P_oth;     /* partial B_seq -- intend to replace B_seq */
 22:   PetscInt    *api,*apj;       /* symbolic i and j arrays of the local product A_loc*B_seq */
 23:   PetscScalar *apv;
 24:   MatReuse    reuse;           /* flag to skip MatGetBrowsOfAoCols_MPIAIJ() and MatMPIAIJGetLocalMat() in 1st call of MatPtAPNumeric_MPIAIJ_MPIAIJ() */
 25:   PetscScalar *apa;            /* tmp array for store a row of A*P used in MatMatMult() */
 26:   Mat         A_loc;           /* used by MatTransposeMatMult(), contains api and apj */
 27:   Mat         Pt;              /* used by MatTransposeMatMult(), Pt = P^T */
 28:   PetscBool   scalable;        /* flag determines scalable or non-scalable implementation */
 29:   Mat         Rd,Ro,AP_loc,C_loc,C_oth;
 30:   PetscInt    algType;         /* implementation algorithm */

 32:   Mat_Merge_SeqsToMPI *merge;
 33:   PetscErrorCode (*destroy)(Mat);
 34:   PetscErrorCode (*duplicate)(Mat,MatDuplicateOption,Mat*);
 35:   PetscErrorCode (*view)(Mat,PetscViewer);
 36: } Mat_PtAPMPI;

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

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

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

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

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

 73:   /* Used by MatMatMult() and MatPtAP() */
 74:   Mat_PtAPMPI *ptap;

 76:   /* used by MatMatMatMult() */
 77:   Mat_MatMatMatMult *matmatmatmult;

 79:   /* Used by MPICUSP and MPICUSPARSE classes */
 80:   void * spptr;

 82: } Mat_MPIAIJ;

 84: PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJ(Mat);

 86: PETSC_INTERN PetscErrorCode MatAssemblyEnd_MPIAIJ(Mat,MatAssemblyType);

 88: PETSC_INTERN PetscErrorCode MatSetUpMultiply_MPIAIJ(Mat);
 89: PETSC_INTERN PetscErrorCode MatDisAssemble_MPIAIJ(Mat);
 90: PETSC_INTERN PetscErrorCode MatDuplicate_MPIAIJ(Mat,MatDuplicateOption,Mat*);
 91: PETSC_INTERN PetscErrorCode MatIncreaseOverlap_MPIAIJ(Mat,PetscInt,IS [],PetscInt);
 92: PETSC_INTERN PetscErrorCode MatIncreaseOverlap_MPIAIJ_Scalable(Mat,PetscInt,IS [],PetscInt);
 93: PETSC_INTERN PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat,ISColoring,MatFDColoring);
 94: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat,ISColoring,MatFDColoring);
 95: PETSC_INTERN PetscErrorCode MatCreateSubMatrices_MPIAIJ (Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
 96: PETSC_INTERN PetscErrorCode MatCreateSubMatricesMPI_MPIAIJ (Mat,PetscInt,const IS[],const IS[],MatReuse,Mat *[]);
 97: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_All(Mat,MatCreateSubMatrixOption,MatReuse,Mat *[]);


100: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ(Mat,IS,IS,MatReuse,Mat*);
101: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_nonscalable(Mat,IS,IS,PetscInt,MatReuse,Mat*);
102: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowDist(Mat,IS,IS,IS,MatReuse,Mat*);
103: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_MPIAIJ_SameRowColDist(Mat,IS,IS,MatReuse,Mat*);
104: PETSC_INTERN PetscErrorCode MatGetMultiProcBlock_MPIAIJ(Mat,MPI_Comm,MatReuse,Mat*);

106: PETSC_INTERN PetscErrorCode MatLoad_MPIAIJ(Mat,PetscViewer);
107: PETSC_INTERN PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat);
108: PETSC_INTERN PetscErrorCode MatMatMult_MPIDense_MPIAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
109: PETSC_INTERN PetscErrorCode MatMatMult_MPIAIJ_MPIAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
110: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,PetscReal,Mat*);
111: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ_seqMPI(Mat,Mat,PetscReal,Mat*);
112: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat*);
113: PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);
114: PETSC_INTERN PetscErrorCode MatMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,Mat);

116: PETSC_INTERN PetscErrorCode MatMatMatMult_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
117: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,PetscReal,Mat*);
118: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_MPIAIJ_MPIAIJ_MPIAIJ(Mat,Mat,Mat,Mat);

120: PETSC_INTERN PetscErrorCode MatPtAP_MPIAIJ_MPIAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
121: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat*);
122: PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);

124: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_MPIAIJ_MPIAIJ_scalable(Mat,Mat,PetscReal,Mat*);
125: PETSC_INTERN PetscErrorCode MatPtAPNumeric_MPIAIJ_MPIAIJ_scalable(Mat,Mat,Mat);


128: #if defined(PETSC_HAVE_HYPRE)
129: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat*);
130: #endif

132: PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ_PtAP(Mat);
133: PETSC_INTERN PetscErrorCode MatDestroy_MPIAIJ(Mat);

135: PETSC_INTERN PetscErrorCode MatRARt_MPIAIJ_MPIAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);

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

145: PETSC_INTERN PetscErrorCode MatTransposeMatMult_MPIAIJ_MPIAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
146: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,PetscReal,Mat*);
147: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIAIJ(Mat,Mat,PetscReal,Mat*);
148: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ(Mat,Mat,Mat);
149: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_nonscalable(Mat,Mat,Mat);
150: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIAIJ_matmatmult(Mat,Mat,Mat);
151: PETSC_INTERN PetscErrorCode MatTransposeMatMult_MPIAIJ_MPIDense(Mat,Mat,MatReuse,PetscReal,Mat*);
152: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_MPIAIJ_MPIDense(Mat,Mat,PetscReal,Mat*);
153: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_MPIAIJ_MPIDense(Mat,Mat,Mat);
154: PETSC_INTERN PetscErrorCode MatGetSeqNonzeroStructure_MPIAIJ(Mat,Mat*);

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

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

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

167: extern PetscErrorCode MatGetDiagonalBlock_MPIAIJ(Mat,Mat*);
168: extern PetscErrorCode MatDiagonalScaleLocal_MPIAIJ(Mat,Vec);

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

173: /* compute apa = A[i,:]*P = Ad[i,:]*P_loc + Ao*[i,:]*P_oth using sparse axpy */
174: #define AProw_scalable(i,ad,ao,p_loc,p_oth,api,apj,apa) \
175: {\
176:   PetscInt    _anz,_pnz,_j,_k,*_ai,*_aj,_row,*_pi,*_pj,_nextp,*_apJ;      \
177:   PetscScalar *_aa,_valtmp,*_pa;                             \
178:   _apJ = apj + api[i];\
179:   /* diagonal portion of A */\
180:   _ai  = ad->i;\
181:   _anz = _ai[i+1] - _ai[i];\
182:   _aj  = ad->j + _ai[i];\
183:   _aa  = ad->a + _ai[i];\
184:   for (_j=0; _j<_anz; _j++) {\
185:     _row = _aj[_j]; \
186:     _pi  = p_loc->i;                                 \
187:     _pnz = _pi[_row+1] - _pi[_row];         \
188:     _pj  = p_loc->j + _pi[_row];                 \
189:     _pa  = p_loc->a + _pi[_row];                 \
190:     /* perform sparse axpy */                    \
191:     _valtmp = _aa[_j];                           \
192:     _nextp  = 0; \
193:     for (_k=0; _nextp<_pnz; _k++) {                    \
194:       if (_apJ[_k] == _pj[_nextp]) { /* column of AP == column of P */   \
195:         apa[_k] += _valtmp*_pa[_nextp++];                                \
196:       } \
197:     }                                           \
198:     (void)PetscLogFlops(2.0*_pnz);              \
199:   }                                             \
200:   /* off-diagonal portion of A */               \
201:   _ai  = ao->i;\
202:   _anz = _ai[i+1] - _ai[i];                     \
203:   _aj  = ao->j + _ai[i];                         \
204:   _aa  = ao->a + _ai[i];                         \
205:   for (_j=0; _j<_anz; _j++) {                      \
206:     _row = _aj[_j];    \
207:     _pi  = p_oth->i;                         \
208:     _pnz = _pi[_row+1] - _pi[_row];          \
209:     _pj  = p_oth->j + _pi[_row];                  \
210:     _pa  = p_oth->a + _pi[_row];                  \
211:     /* perform sparse axpy */                     \
212:     _valtmp = _aa[_j];                             \
213:     _nextp  = 0; \
214:     for (_k=0; _nextp<_pnz; _k++) {                     \
215:       if (_apJ[_k] == _pj[_nextp]) { /* column of AP == column of P */\
216:         apa[_k] += _valtmp*_pa[_nextp++];                       \
217:       }                                                     \
218:     }                                            \
219:     (void)PetscLogFlops(2.0*_pnz);               \
220:   } \
221: }

223: #define AProw_nonscalable(i,ad,ao,p_loc,p_oth,apa) \
224: {\
225:   PetscInt    _anz,_pnz,_j,_k,*_ai,*_aj,_row,*_pi,*_pj;      \
226:   PetscScalar *_aa,_valtmp,*_pa;                             \
227:   /* diagonal portion of A */\
228:   _ai  = ad->i;\
229:   _anz = _ai[i+1] - _ai[i];\
230:   _aj  = ad->j + _ai[i];\
231:   _aa  = ad->a + _ai[i];\
232:   for (_j=0; _j<_anz; _j++) {\
233:     _row = _aj[_j]; \
234:     _pi  = p_loc->i;                                 \
235:     _pnz = _pi[_row+1] - _pi[_row];         \
236:     _pj  = p_loc->j + _pi[_row];                 \
237:     _pa  = p_loc->a + _pi[_row];                 \
238:     /* perform dense axpy */                    \
239:     _valtmp = _aa[_j];                           \
240:     for (_k=0; _k<_pnz; _k++) {                    \
241:       apa[_pj[_k]] += _valtmp*_pa[_k];               \
242:     }                                           \
243:     (void)PetscLogFlops(2.0*_pnz);              \
244:   }                                             \
245:   /* off-diagonal portion of A */               \
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: }

265: #endif