Actual source code: aij.h

  1: #ifndef PETSC_MATAIJ_IMPL_H
  2: #define PETSC_MATAIJ_IMPL_H

  4: #include <petsc/private/matimpl.h>
  5: #include <petsc/private/hashmapi.h>
  6: #include <petsc/private/hashmapijv.h>

  8: /*
  9:  Used by MatCreateSubMatrices_MPIXAIJ_Local()
 10: */
 11: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
 12:   PetscInt   id; /* index of submats, only submats[0] is responsible for deleting some arrays below */
 13:   PetscInt   nrqs, nrqr;
 14:   PetscInt **rbuf1, **rbuf2, **rbuf3, **sbuf1, **sbuf2;
 15:   PetscInt **ptr;
 16:   PetscInt  *tmp;
 17:   PetscInt  *ctr;
 18:   PetscInt  *pa; /* proc array */
 19:   PetscInt  *req_size, *req_source1, *req_source2;
 20:   PetscBool  allcolumns, allrows;
 21:   PetscBool  singleis;
 22:   PetscInt  *row2proc; /* row to proc map */
 23:   PetscInt   nstages;
 24: #if defined(PETSC_USE_CTABLE)
 25:   PetscHMapI cmap, rmap;
 26:   PetscInt  *cmap_loc, *rmap_loc;
 27: #else
 28:   PetscInt *cmap, *rmap;
 29: #endif
 30:   PetscErrorCode (*destroy)(Mat);
 31: } Mat_SubSppt;

 33: /* Operations provided by MATSEQAIJ and its subclasses */
 34: typedef struct {
 35:   PetscErrorCode (*getarray)(Mat, PetscScalar **);
 36:   PetscErrorCode (*restorearray)(Mat, PetscScalar **);
 37:   PetscErrorCode (*getarrayread)(Mat, const PetscScalar **);
 38:   PetscErrorCode (*restorearrayread)(Mat, const PetscScalar **);
 39:   PetscErrorCode (*getarraywrite)(Mat, PetscScalar **);
 40:   PetscErrorCode (*restorearraywrite)(Mat, PetscScalar **);
 41:   PetscErrorCode (*getcsrandmemtype)(Mat, const PetscInt **, const PetscInt **, PetscScalar **, PetscMemType *);
 42: } Mat_SeqAIJOps;

 44: /*
 45:     Struct header shared by SeqAIJ, SeqBAIJ and SeqSBAIJ matrix formats
 46: */
 47: #define SEQAIJHEADER(datatype) \
 48:   PetscBool         roworiented;  /* if true, row-oriented input, default */ \
 49:   PetscInt          nonew;        /* 1 don't add new nonzeros, -1 generate error on new */ \
 50:   PetscInt          nounused;     /* -1 generate error on unused space */ \
 51:   PetscBool         singlemalloc; /* if true a, i, and j have been obtained with one big malloc */ \
 52:   PetscInt          maxnz;        /* allocated nonzeros */ \
 53:   PetscInt         *imax;         /* maximum space allocated for each row */ \
 54:   PetscInt         *ilen;         /* actual length of each row */ \
 55:   PetscInt         *ipre;         /* space preallocated for each row by user */ \
 56:   PetscBool         free_imax_ilen; \
 57:   PetscInt          reallocs;           /* number of mallocs done during MatSetValues() \
 58:                                         as more values are set than were prealloced */ \
 59:   PetscInt          rmax;               /* max nonzeros in any row */ \
 60:   PetscBool         keepnonzeropattern; /* keeps matrix structure same in calls to MatZeroRows()*/ \
 61:   PetscBool         ignorezeroentries; \
 62:   PetscBool         free_ij;       /* free the column indices j and row offsets i when the matrix is destroyed */ \
 63:   PetscBool         free_a;        /* free the numerical values when matrix is destroy */ \
 64:   Mat_CompressedRow compressedrow; /* use compressed row format */ \
 65:   PetscInt          nz;            /* nonzeros */ \
 66:   PetscInt         *i;             /* pointer to beginning of each row */ \
 67:   PetscInt         *j;             /* column values: j + i[k] - 1 is start of row k */ \
 68:   PetscInt         *diag;          /* pointers to diagonal elements */ \
 69:   PetscInt          nonzerorowcnt; /* how many rows have nonzero entries */ \
 70:   PetscBool         free_diag; \
 71:   datatype         *a;              /* nonzero elements */ \
 72:   PetscScalar      *solve_work;     /* work space used in MatSolve */ \
 73:   IS                row, col, icol; /* index sets, used for reorderings */ \
 74:   PetscBool         pivotinblocks;  /* pivot inside factorization of each diagonal block */ \
 75:   Mat               parent;         /* set if this matrix was formed with MatDuplicate(...,MAT_SHARE_NONZERO_PATTERN,....); \
 76:                                          means that this shares some data structures with the parent including diag, ilen, imax, i, j */ \
 77:   Mat_SubSppt      *submatis1;      /* used by MatCreateSubMatrices_MPIXAIJ_Local */ \
 78:   Mat_SeqAIJOps     ops[1]          /* operations for SeqAIJ and its subclasses */

 80: typedef struct {
 81:   MatTransposeColoring matcoloring;
 82:   Mat                  Bt_den;  /* dense matrix of B^T */
 83:   Mat                  ABt_den; /* dense matrix of A*B^T */
 84:   PetscBool            usecoloring;
 85: } Mat_MatMatTransMult;

 87: typedef struct { /* used by MatTransposeMatMult() */
 88:   Mat At;        /* transpose of the first matrix */
 89:   Mat mA;        /* maij matrix of A */
 90:   Vec bt, ct;    /* vectors to hold locally transposed arrays of B and C */
 91:   /* used by PtAP */
 92:   void *data;
 93:   PetscErrorCode (*destroy)(void *);
 94: } Mat_MatTransMatMult;

 96: typedef struct {
 97:   PetscInt    *api, *apj; /* symbolic structure of A*P */
 98:   PetscScalar *apa;       /* temporary array for storing one row of A*P */
 99: } Mat_AP;

101: typedef struct {
102:   MatTransposeColoring matcoloring;
103:   Mat                  Rt;   /* sparse or dense matrix of R^T */
104:   Mat                  RARt; /* dense matrix of R*A*R^T */
105:   Mat                  ARt;  /* A*R^T used for the case -matrart_color_art */
106:   MatScalar           *work; /* work array to store columns of A*R^T used in MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqDense() */
107:   /* free intermediate products needed for PtAP */
108:   void *data;
109:   PetscErrorCode (*destroy)(void *);
110: } Mat_RARt;

112: typedef struct {
113:   Mat BC; /* temp matrix for storing B*C */
114: } Mat_MatMatMatMult;

116: /*
117:   MATSEQAIJ format - Compressed row storage (also called Yale sparse matrix
118:   format) or compressed sparse row (CSR).  The i[] and j[] arrays start at 0. For example,
119:   j[i[k]+p] is the pth column in row k.  Note that the diagonal
120:   matrix elements are stored with the rest of the nonzeros (not separately).
121: */

123: /* Info about i-nodes (identical nodes) helper class for SeqAIJ */
124: typedef struct {
125:   MatScalar *bdiag, *ibdiag, *ssor_work; /* diagonal blocks of matrix used for MatSOR_SeqAIJ_Inode() */
126:   PetscInt   bdiagsize;                  /* length of bdiag and ibdiag */
127:   PetscBool  ibdiagvalid;                /* do ibdiag[] and bdiag[] contain the most recent values */

129:   PetscBool        use;
130:   PetscInt         node_count;       /* number of inodes */
131:   PetscInt        *size;             /* size of each inode */
132:   PetscInt         limit;            /* inode limit */
133:   PetscInt         max_limit;        /* maximum supported inode limit */
134:   PetscBool        checked;          /* if inodes have been checked for */
135:   PetscObjectState mat_nonzerostate; /* non-zero state when inodes were checked for */
136: } Mat_SeqAIJ_Inode;

138: PETSC_INTERN PetscErrorCode MatView_SeqAIJ_Inode(Mat, PetscViewer);
139: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ_Inode(Mat, MatAssemblyType);
140: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_Inode(Mat);
141: PETSC_INTERN PetscErrorCode MatCreate_SeqAIJ_Inode(Mat);
142: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ_Inode(Mat, MatOption, PetscBool);
143: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ_Inode(Mat, MatDuplicateOption, Mat *);
144: PETSC_INTERN PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat, Mat, MatDuplicateOption, PetscBool);
145: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode(Mat, Mat, const MatFactorInfo *);
146: PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat, PetscScalar **);
147: PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat, PetscScalar **);

149: typedef struct {
150:   SEQAIJHEADER(MatScalar);
151:   Mat_SeqAIJ_Inode inode;
152:   MatScalar       *saved_values; /* location for stashing nonzero values of matrix */

154:   PetscScalar *idiag, *mdiag, *ssor_work; /* inverse of diagonal entries, diagonal values and workspace for Eisenstat trick */
155:   PetscBool    idiagvalid;                /* current idiag[] and mdiag[] are valid */
156:   PetscScalar *ibdiag;                    /* inverses of block diagonals */
157:   PetscBool    ibdiagvalid;               /* inverses of block diagonals are valid. */
158:   PetscBool    diagonaldense;             /* all entries along the diagonal have been set; i.e. no missing diagonal terms */
159:   PetscScalar  fshift, omega;             /* last used omega and fshift */

161:   /* MatSetValuesCOO() related fields on host */
162:   PetscCount  coo_n; /* Number of entries in MatSetPreallocationCOO() */
163:   PetscCount  Atot;  /* Total number of valid (i.e., w/ non-negative indices) entries in the COO array */
164:   PetscCount *jmap;  /* perm[jmap[i]..jmap[i+1]) give indices of entries in v[] associated with i-th nonzero of the matrix */
165:   PetscCount *perm;  /* The permutation array in sorting (i,j) by row and then by col */

167:   /* MatSetValues() via hash related fields */
168:   PetscHMapIJV   ht;
169:   PetscInt      *dnz;
170:   struct _MatOps cops;
171: } Mat_SeqAIJ;

173: /*
174:   Frees the a, i, and j arrays from the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
175: */
176: static inline PetscErrorCode MatSeqXAIJFreeAIJ(Mat AA, MatScalar **a, PetscInt **j, PetscInt **i)
177: {
178:   Mat_SeqAIJ *A = (Mat_SeqAIJ *)AA->data;

180:   PetscFunctionBegin;
181:   if (A->singlemalloc) {
182:     PetscCall(PetscFree3(*a, *j, *i));
183:   } else {
184:     if (A->free_a) PetscCall(PetscFree(*a));
185:     if (A->free_ij) PetscCall(PetscFree(*j));
186:     if (A->free_ij) PetscCall(PetscFree(*i));
187:   }
188:   PetscFunctionReturn(PETSC_SUCCESS);
189: }
190: /*
191:     Allocates larger a, i, and j arrays for the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
192:     This is a macro because it takes the datatype as an argument which can be either a Mat or a MatScalar
193: */
194: #define MatSeqXAIJReallocateAIJ(Amat, AM, BS2, NROW, ROW, COL, RMAX, AA, AI, AJ, RP, AP, AIMAX, NONEW, datatype) \
195:   if (NROW >= RMAX) { \
196:     Mat_SeqAIJ *Ain = (Mat_SeqAIJ *)Amat->data; \
197:     /* there is no extra room in row, therefore enlarge */ \
198:     PetscInt  CHUNKSIZE = 15, new_nz = AI[AM] + CHUNKSIZE, len, *new_i = NULL, *new_j = NULL; \
199:     datatype *new_a; \
200: \
201:     PetscCheck(NONEW != -2, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "New nonzero at (%" PetscInt_FMT ",%" PetscInt_FMT ") caused a malloc\nUse MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check", ROW, COL); \
202:     /* malloc new storage space */ \
203:     PetscCall(PetscMalloc3(BS2 *new_nz, &new_a, new_nz, &new_j, AM + 1, &new_i)); \
204: \
205:     /* copy over old data into new slots */ \
206:     for (ii = 0; ii < ROW + 1; ii++) new_i[ii] = AI[ii]; \
207:     for (ii = ROW + 1; ii < AM + 1; ii++) new_i[ii] = AI[ii] + CHUNKSIZE; \
208:     PetscCall(PetscArraycpy(new_j, AJ, AI[ROW] + NROW)); \
209:     len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
210:     PetscCall(PetscArraycpy(new_j + AI[ROW] + NROW + CHUNKSIZE, AJ + AI[ROW] + NROW, len)); \
211:     PetscCall(PetscArraycpy(new_a, AA, BS2 *(AI[ROW] + NROW))); \
212:     PetscCall(PetscArrayzero(new_a + BS2 * (AI[ROW] + NROW), BS2 * CHUNKSIZE)); \
213:     PetscCall(PetscArraycpy(new_a + BS2 * (AI[ROW] + NROW + CHUNKSIZE), AA + BS2 * (AI[ROW] + NROW), BS2 * len)); \
214:     /* free up old matrix storage */ \
215:     PetscCall(MatSeqXAIJFreeAIJ(A, &Ain->a, &Ain->j, &Ain->i)); \
216:     AA     = new_a; \
217:     Ain->a = (MatScalar *)new_a; \
218:     AI = Ain->i = new_i; \
219:     AJ = Ain->j       = new_j; \
220:     Ain->singlemalloc = PETSC_TRUE; \
221: \
222:     RP   = AJ + AI[ROW]; \
223:     AP   = AA + BS2 * AI[ROW]; \
224:     RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
225:     Ain->maxnz += BS2 * CHUNKSIZE; \
226:     Ain->reallocs++; \
227:   }

229: #define MatSeqXAIJReallocateAIJ_structure_only(Amat, AM, BS2, NROW, ROW, COL, RMAX, AI, AJ, RP, AIMAX, NONEW, datatype) \
230:   if (NROW >= RMAX) { \
231:     Mat_SeqAIJ *Ain = (Mat_SeqAIJ *)Amat->data; \
232:     /* there is no extra room in row, therefore enlarge */ \
233:     PetscInt CHUNKSIZE = 15, new_nz = AI[AM] + CHUNKSIZE, len, *new_i = NULL, *new_j = NULL; \
234: \
235:     PetscCheck(NONEW != -2, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "New nonzero at (%" PetscInt_FMT ",%" PetscInt_FMT ") caused a malloc\nUse MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check", ROW, COL); \
236:     /* malloc new storage space */ \
237:     PetscCall(PetscMalloc1(new_nz, &new_j)); \
238:     PetscCall(PetscMalloc1(AM + 1, &new_i)); \
239: \
240:     /* copy over old data into new slots */ \
241:     for (ii = 0; ii < ROW + 1; ii++) new_i[ii] = AI[ii]; \
242:     for (ii = ROW + 1; ii < AM + 1; ii++) new_i[ii] = AI[ii] + CHUNKSIZE; \
243:     PetscCall(PetscArraycpy(new_j, AJ, AI[ROW] + NROW)); \
244:     len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
245:     PetscCall(PetscArraycpy(new_j + AI[ROW] + NROW + CHUNKSIZE, AJ + AI[ROW] + NROW, len)); \
246: \
247:     /* free up old matrix storage */ \
248:     PetscCall(MatSeqXAIJFreeAIJ(A, &Ain->a, &Ain->j, &Ain->i)); \
249:     Ain->a = NULL; \
250:     AI = Ain->i = new_i; \
251:     AJ = Ain->j       = new_j; \
252:     Ain->singlemalloc = PETSC_FALSE; \
253:     Ain->free_a       = PETSC_FALSE; \
254: \
255:     RP   = AJ + AI[ROW]; \
256:     RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
257:     Ain->maxnz += BS2 * CHUNKSIZE; \
258:     Ain->reallocs++; \
259:   }

261: PETSC_INTERN PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat, PetscInt, const PetscInt *);
262: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_SeqAIJ(Mat, PetscCount, PetscInt[], PetscInt[]);
263: PETSC_INTERN PetscErrorCode MatResetPreallocationCOO_SeqAIJ(Mat);

265: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ(Mat, Mat, IS, IS, const MatFactorInfo *);
266: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_ilu0(Mat, Mat, IS, IS, const MatFactorInfo *);

268: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ(Mat, Mat, IS, const MatFactorInfo *);
269: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ(Mat, Mat, IS, const MatFactorInfo *);
270: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_inplace(Mat, Mat, const MatFactorInfo *);
271: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ(Mat, Mat, const MatFactorInfo *);
272: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ(Mat, MatDuplicateOption, Mat *);
273: PETSC_INTERN PetscErrorCode MatCopy_SeqAIJ(Mat, Mat, MatStructure);
274: PETSC_INTERN PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat, PetscBool *, PetscInt *);
275: PETSC_INTERN PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat);
276: PETSC_INTERN PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat, PetscInt *, PetscInt **);

278: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ(Mat, Vec, Vec);
279: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ_Inode(Mat, Vec, Vec);
280: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ(Mat, Vec, Vec, Vec);
281: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ_Inode(Mat, Vec, Vec, Vec);
282: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqAIJ(Mat, Vec, Vec);
283: PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat, Vec, Vec, Vec);
284: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec);
285: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ_Inode(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec);

287: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ(Mat, MatOption, PetscBool);

289: PETSC_INTERN PetscErrorCode MatGetSymbolicTranspose_SeqAIJ(Mat, PetscInt *[], PetscInt *[]);
290: PETSC_INTERN PetscErrorCode MatRestoreSymbolicTranspose_SeqAIJ(Mat, PetscInt *[], PetscInt *[]);
291: PETSC_INTERN PetscErrorCode MatGetSymbolicTransposeReduced_SeqAIJ(Mat, PetscInt, PetscInt, PetscInt *[], PetscInt *[]);
292: PETSC_INTERN PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat, Mat *);
293: PETSC_INTERN PetscErrorCode MatTranspose_SeqAIJ(Mat, MatReuse, Mat *);

295: PETSC_INTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt, PetscInt *, PetscInt *, PetscBool, PetscInt, PetscInt, PetscInt **, PetscInt **);
296: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ(Mat, Mat, IS, IS, const MatFactorInfo *);
297: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_inplace(Mat, Mat, const MatFactorInfo *);
298: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ(Mat, Mat, const MatFactorInfo *);
299: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(Mat, Mat, const MatFactorInfo *);
300: PETSC_INTERN PetscErrorCode MatLUFactor_SeqAIJ(Mat, IS, IS, const MatFactorInfo *);
301: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_inplace(Mat, Vec, Vec);
302: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ(Mat, Vec, Vec);
303: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode(Mat, Vec, Vec);
304: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering(Mat, Vec, Vec);
305: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ(Mat, Vec, Vec, Vec);
306: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ_inplace(Mat, Vec, Vec);
307: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ(Mat, Vec, Vec);
308: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ_inplace(Mat, Vec, Vec, Vec);
309: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ(Mat, Vec, Vec, Vec);
310: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ(Mat, Mat, Mat);
311: PETSC_INTERN PetscErrorCode MatEqual_SeqAIJ(Mat, Mat, PetscBool *);
312: PETSC_INTERN PetscErrorCode MatFDColoringCreate_SeqXAIJ(Mat, ISColoring, MatFDColoring);
313: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_SeqXAIJ(Mat, ISColoring, MatFDColoring);
314: PETSC_INTERN PetscErrorCode MatFDColoringSetUpBlocked_AIJ_Private(Mat, MatFDColoring, PetscInt);
315: PETSC_INTERN PetscErrorCode MatLoad_AIJ_HDF5(Mat, PetscViewer);
316: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ_Binary(Mat, PetscViewer);
317: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ(Mat, PetscViewer);
318: PETSC_INTERN PetscErrorCode RegisterApplyPtAPRoutines_Private(Mat);

320: #if defined(PETSC_HAVE_HYPRE)
321: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_Transpose_AIJ_AIJ(Mat);
322: #endif
323: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_SeqAIJ(Mat);

325: PETSC_INTERN PetscErrorCode MatProductSymbolic_SeqAIJ_SeqAIJ(Mat);
326: PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat);
327: PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_SeqAIJ_SeqAIJ(Mat);

329: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
330: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Sorted(Mat, Mat, PetscReal, Mat);
331: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat, Mat, PetscReal, Mat);
332: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable(Mat, Mat, PetscReal, Mat);
333: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable_fast(Mat, Mat, PetscReal, Mat);
334: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Heap(Mat, Mat, PetscReal, Mat);
335: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_BTHeap(Mat, Mat, PetscReal, Mat);
336: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_RowMerge(Mat, Mat, PetscReal, Mat);
337: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_LLCondensed(Mat, Mat, PetscReal, Mat);
338: #if defined(PETSC_HAVE_HYPRE)
339: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_AIJ_AIJ_wHYPRE(Mat, Mat, PetscReal, Mat);
340: #endif

342: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
343: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Sorted(Mat, Mat, Mat);

345: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat, Mat, Mat);
346: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Scalable(Mat, Mat, Mat);

348: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat, Mat, PetscReal, Mat);
349: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
350: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat, Mat, Mat);

352: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
353: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_matmattransposemult(Mat, Mat, PetscReal, Mat);
354: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_colorrart(Mat, Mat, PetscReal, Mat);
355: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
356: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_matmattransposemult(Mat, Mat, Mat);
357: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_colorrart(Mat, Mat, Mat);

359: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
360: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
361: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_MatTransMatMult(void *);

363: PETSC_INTERN PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
364: PETSC_INTERN PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
365: PETSC_INTERN PetscErrorCode MatTransposeColoringCreate_SeqAIJ(Mat, ISColoring, MatTransposeColoring);
366: PETSC_INTERN PetscErrorCode MatTransColoringApplySpToDen_SeqAIJ(MatTransposeColoring, Mat, Mat);
367: PETSC_INTERN PetscErrorCode MatTransColoringApplyDenToSp_SeqAIJ(MatTransposeColoring, Mat, Mat);

369: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Mat, Mat, Mat, PetscReal, Mat);
370: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ(Mat, Mat, Mat, Mat);

372: PETSC_INTERN PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat, PetscInt, PetscInt, PetscRandom);
373: PETSC_INTERN PetscErrorCode MatSetValues_SeqAIJ(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
374: PETSC_INTERN PetscErrorCode MatGetRow_SeqAIJ(Mat, PetscInt, PetscInt *, PetscInt **, PetscScalar **);
375: PETSC_INTERN PetscErrorCode MatRestoreRow_SeqAIJ(Mat, PetscInt, PetscInt *, PetscInt **, PetscScalar **);
376: PETSC_INTERN PetscErrorCode MatScale_SeqAIJ(Mat, PetscScalar);
377: PETSC_INTERN PetscErrorCode MatDiagonalScale_SeqAIJ(Mat, Vec, Vec);
378: PETSC_INTERN PetscErrorCode MatDiagonalSet_SeqAIJ(Mat, Vec, InsertMode);
379: PETSC_INTERN PetscErrorCode MatAXPY_SeqAIJ(Mat, PetscScalar, Mat, MatStructure);
380: PETSC_INTERN PetscErrorCode MatGetRowIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
381: PETSC_INTERN PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
382: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
383: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
384: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscInt *[], PetscBool *);
385: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscInt *[], PetscBool *);
386: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ(Mat);
387: PETSC_INTERN PetscErrorCode MatView_SeqAIJ(Mat, PetscViewer);

389: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat);
390: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal_Inode(Mat);
391: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode(Mat);
392: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode_FactorLU(Mat);

394: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat, Mat, PetscInt *);

396: #if defined(PETSC_HAVE_MATLAB)
397: PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject, void *);
398: PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject, void *);
399: #endif
400: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqSBAIJ(Mat, MatType, MatReuse, Mat *);
401: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
402: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat, MatType, MatReuse, Mat *);
403: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat, MatType, MatReuse, Mat *);
404: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat, MatType, MatReuse, Mat *);
405: #if defined(PETSC_HAVE_SCALAPACK)
406: PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
407: #endif
408: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat, MatType, MatReuse, Mat *);
409: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat, MatType, MatReuse, Mat *);
410: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJSELL(Mat, MatType, MatReuse, Mat *);
411: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat, MatType, MatReuse, Mat *);
412: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat, MatType, MatReuse, Mat *);
413: PETSC_INTERN PetscErrorCode MatReorderForNonzeroDiagonal_SeqAIJ(Mat, PetscReal, IS, IS);
414: PETSC_INTERN PetscErrorCode MatRARt_SeqAIJ_SeqAIJ(Mat, Mat, MatReuse, PetscReal, Mat *);
415: PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat);
416: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat, MatAssemblyType);
417: PETSC_EXTERN PetscErrorCode MatZeroEntries_SeqAIJ(Mat);

419: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt, const PetscInt *, const PetscInt *, const PetscInt *, const PetscInt *, PetscInt *);
420: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);
421: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);

423: PETSC_INTERN PetscErrorCode MatSetSeqMat_SeqAIJ(Mat, IS, IS, MatStructure, Mat);
424: PETSC_INTERN PetscErrorCode MatEliminateZeros_SeqAIJ(Mat A);
425: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *);
426: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat);
427: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Dummy(Mat);
428: PETSC_INTERN PetscErrorCode MatDestroySubMatrices_Dummy(PetscInt, Mat *[]);
429: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat, IS, IS, PetscInt, MatReuse, Mat *);

431: PETSC_INTERN PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat, ISLocalToGlobalMapping *);
432: PETSC_INTERN PetscErrorCode MatSetSeqAIJWithArrays_private(MPI_Comm, PetscInt, PetscInt, PetscInt[], PetscInt[], PetscScalar[], MatType, Mat);

434: /*
435:     PetscSparseDenseMinusDot - The inner kernel of triangular solves and Gauss-Siedel smoothing. \sum_i xv[i] * r[xi[i]] for CSR storage

437:   Input Parameters:
438: +  nnz - the number of entries
439: .  r - the array of vector values
440: .  xv - the matrix values for the row
441: -  xi - the column indices of the nonzeros in the row

443:   Output Parameter:
444: .  sum - negative the sum of results

446:   PETSc compile flags:
447: +   PETSC_KERNEL_USE_UNROLL_4
448: -   PETSC_KERNEL_USE_UNROLL_2

450:   Developer Note:
451:     The macro changes sum but not other parameters

453: .seealso: `PetscSparseDensePlusDot()`
454: */
455: #if defined(PETSC_KERNEL_USE_UNROLL_4)
456:   #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \
457:     { \
458:       if (nnz > 0) { \
459:         PetscInt nnz2 = nnz, rem = nnz & 0x3; \
460:         switch (rem) { \
461:         case 3: \
462:           sum -= *xv++ * r[*xi++]; \
463:         case 2: \
464:           sum -= *xv++ * r[*xi++]; \
465:         case 1: \
466:           sum -= *xv++ * r[*xi++]; \
467:           nnz2 -= rem; \
468:         } \
469:         while (nnz2 > 0) { \
470:           sum -= xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
471:           xv += 4; \
472:           xi += 4; \
473:           nnz2 -= 4; \
474:         } \
475:         xv -= nnz; \
476:         xi -= nnz; \
477:       } \
478:     }

480: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
481:   #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \
482:     { \
483:       PetscInt __i, __i1, __i2; \
484:       for (__i = 0; __i < nnz - 1; __i += 2) { \
485:         __i1 = xi[__i]; \
486:         __i2 = xi[__i + 1]; \
487:         sum -= (xv[__i] * r[__i1] + xv[__i + 1] * r[__i2]); \
488:       } \
489:       if (nnz & 0x1) sum -= xv[__i] * r[xi[__i]]; \
490:     }

492: #else
493:   #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \
494:     { \
495:       PetscInt __i; \
496:       for (__i = 0; __i < nnz; __i++) sum -= xv[__i] * r[xi[__i]]; \
497:     }
498: #endif

500: /*
501:     PetscSparseDensePlusDot - The inner kernel of matrix-vector product \sum_i xv[i] * r[xi[i]] for CSR storage

503:   Input Parameters:
504: +  nnz - the number of entries
505: .  r - the array of vector values
506: .  xv - the matrix values for the row
507: -  xi - the column indices of the nonzeros in the row

509:   Output Parameter:
510: .  sum - the sum of results

512:   PETSc compile flags:
513: +   PETSC_KERNEL_USE_UNROLL_4
514: -   PETSC_KERNEL_USE_UNROLL_2

516:   Developer Note:
517:     The macro changes sum but not other parameters

519: .seealso: `PetscSparseDenseMinusDot()`
520: */
521: #if defined(PETSC_KERNEL_USE_UNROLL_4)
522:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \
523:     { \
524:       if (nnz > 0) { \
525:         PetscInt nnz2 = nnz, rem = nnz & 0x3; \
526:         switch (rem) { \
527:         case 3: \
528:           sum += *xv++ * r[*xi++]; \
529:         case 2: \
530:           sum += *xv++ * r[*xi++]; \
531:         case 1: \
532:           sum += *xv++ * r[*xi++]; \
533:           nnz2 -= rem; \
534:         } \
535:         while (nnz2 > 0) { \
536:           sum += xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
537:           xv += 4; \
538:           xi += 4; \
539:           nnz2 -= 4; \
540:         } \
541:         xv -= nnz; \
542:         xi -= nnz; \
543:       } \
544:     }

546: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
547:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \
548:     { \
549:       PetscInt __i, __i1, __i2; \
550:       for (__i = 0; __i < nnz - 1; __i += 2) { \
551:         __i1 = xi[__i]; \
552:         __i2 = xi[__i + 1]; \
553:         sum += (xv[__i] * r[__i1] + xv[__i + 1] * r[__i2]); \
554:       } \
555:       if (nnz & 0x1) sum += xv[__i] * r[xi[__i]]; \
556:     }

558: #elif defined(PETSC_USE_AVX512_KERNELS) && defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) && !defined(PETSC_SKIP_IMMINTRIN_H_CUDAWORKAROUND)
559:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) PetscSparseDensePlusDot_AVX512_Private(&(sum), (r), (xv), (xi), (nnz))

561: #else
562:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \
563:     { \
564:       PetscInt __i; \
565:       for (__i = 0; __i < nnz; __i++) sum += xv[__i] * r[xi[__i]]; \
566:     }
567: #endif

569: #if defined(PETSC_USE_AVX512_KERNELS) && defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX512F__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES) && !defined(PETSC_SKIP_IMMINTRIN_H_CUDAWORKAROUND)
570:   #include <immintrin.h>
571:   #if !defined(_MM_SCALE_8)
572:     #define _MM_SCALE_8 8
573:   #endif

575: static inline void PetscSparseDensePlusDot_AVX512_Private(PetscScalar *sum, const PetscScalar *x, const MatScalar *aa, const PetscInt *aj, PetscInt n)
576: {
577:   __m512d  vec_x, vec_y, vec_vals;
578:   __m256i  vec_idx;
579:   PetscInt j;

581:   vec_y = _mm512_setzero_pd();
582:   for (j = 0; j < (n >> 3); j++) {
583:     vec_idx  = _mm256_loadu_si256((__m256i const *)aj);
584:     vec_vals = _mm512_loadu_pd(aa);
585:     vec_x    = _mm512_i32gather_pd(vec_idx, x, _MM_SCALE_8);
586:     vec_y    = _mm512_fmadd_pd(vec_x, vec_vals, vec_y);
587:     aj += 8;
588:     aa += 8;
589:   }
590:   #if defined(__AVX512VL__)
591:   /* masked load requires avx512vl, which is not supported by KNL */
592:   if (n & 0x07) {
593:     __mmask8 mask;
594:     mask     = (__mmask8)(0xff >> (8 - (n & 0x07)));
595:     vec_idx  = _mm256_mask_loadu_epi32(vec_idx, mask, aj);
596:     vec_vals = _mm512_mask_loadu_pd(vec_vals, mask, aa);
597:     vec_x    = _mm512_mask_i32gather_pd(vec_x, mask, vec_idx, x, _MM_SCALE_8);
598:     vec_y    = _mm512_mask3_fmadd_pd(vec_x, vec_vals, vec_y, mask);
599:   }
600:   *sum += _mm512_reduce_add_pd(vec_y);
601:   #else
602:   *sum += _mm512_reduce_add_pd(vec_y);
603:   for (j = 0; j < (n & 0x07); j++) *sum += aa[j] * x[aj[j]];
604:   #endif
605: }
606: #endif

608: /*
609:     PetscSparseDenseMaxDot - The inner kernel of a modified matrix-vector product \max_i xv[i] * r[xi[i]] for CSR storage

611:   Input Parameters:
612: +  nnz - the number of entries
613: .  r - the array of vector values
614: .  xv - the matrix values for the row
615: -  xi - the column indices of the nonzeros in the row

617:   Output Parameter:
618: .  max - the max of results

620: .seealso: `PetscSparseDensePlusDot()`, `PetscSparseDenseMinusDot()`
621: */
622: #define PetscSparseDenseMaxDot(max, r, xv, xi, nnz) \
623:   do { \
624:     for (PetscInt __i = 0; __i < (nnz); __i++) { max = PetscMax(PetscRealPart(max), PetscRealPart((xv)[__i] * (r)[(xi)[__i]])); } \
625:   } while (0)

627: /*
628:  Add column indices into table for counting the max nonzeros of merged rows
629:  */
630: #define MatRowMergeMax_SeqAIJ(mat, nrows, ta) \
631:   do { \
632:     if ((mat)) { \
633:       for (PetscInt _row = 0; _row < (nrows); _row++) { \
634:         const PetscInt _nz = (mat)->i[_row + 1] - (mat)->i[_row]; \
635:         for (PetscInt _j = 0; _j < _nz; _j++) { \
636:           PetscInt *_col = _j + (mat)->j + (mat)->i[_row]; \
637:           PetscCall(PetscHMapISet((ta), *_col + 1, 1)); \
638:         } \
639:       } \
640:     } \
641:   } while (0)

643: /*
644:  Add column indices into table for counting the nonzeros of merged rows
645:  */
646: #define MatMergeRows_SeqAIJ(mat, nrows, rows, ta) \
647:   do { \
648:     for (PetscInt _i = 0; _i < (nrows); _i++) { \
649:       const PetscInt _row = (rows)[_i]; \
650:       const PetscInt _nz  = (mat)->i[_row + 1] - (mat)->i[_row]; \
651:       for (PetscInt _j = 0; _j < _nz; _j++) { \
652:         PetscInt *_col = _j + (mat)->j + (mat)->i[_row]; \
653:         PetscCall(PetscHMapISetWithMode((ta), *_col + 1, 1, INSERT_VALUES)); \
654:       } \
655:     } \
656:   } while (0)

658: #endif