Actual source code: aij.h

  1: #pragma once

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

  7: /*
  8:  Used by MatCreateSubMatrices_MPIXAIJ_Local()
  9: */
 10: typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */
 11:   PetscInt   id; /* index of submats, only submats[0] is responsible for deleting some arrays below */
 12:   PetscInt   nrqs, nrqr;
 13:   PetscInt **rbuf1, **rbuf2, **rbuf3, **sbuf1, **sbuf2;
 14:   PetscInt **ptr;
 15:   PetscInt  *tmp;
 16:   PetscInt  *ctr;
 17:   PetscInt  *pa; /* proc array */
 18:   PetscInt  *req_size, *req_source1, *req_source2;
 19:   PetscBool  allcolumns, allrows;
 20:   PetscBool  singleis;
 21:   PetscInt  *row2proc; /* row to proc map */
 22:   PetscInt   nstages;
 23: #if defined(PETSC_USE_CTABLE)
 24:   PetscHMapI cmap, rmap;
 25:   PetscInt  *cmap_loc, *rmap_loc;
 26: #else
 27:   PetscInt *cmap, *rmap;
 28: #endif
 29:   PetscErrorCode (*destroy)(Mat);
 30: } Mat_SubSppt;

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

 43: /*
 44:     Struct header shared by SeqAIJ, SeqBAIJ and SeqSBAIJ matrix formats
 45: */
 46: #define SEQAIJHEADER(datatype) \
 47:   PetscBool         roworiented;  /* if true, row-oriented input, default */ \
 48:   PetscInt          nonew;        /* 1 don't add new nonzeros, -1 generate error on new */ \
 49:   PetscInt          nounused;     /* -1 generate error on unused space */ \
 50:   PetscBool         singlemalloc; /* if true a, i, and j have been obtained with one big malloc */ \
 51:   PetscInt          maxnz;        /* allocated nonzeros */ \
 52:   PetscInt         *imax;         /* maximum space allocated for each row */ \
 53:   PetscInt         *ilen;         /* actual length of each row */ \
 54:   PetscInt         *ipre;         /* space preallocated for each row by user */ \
 55:   PetscBool         free_imax_ilen; \
 56:   PetscInt          reallocs;           /* number of mallocs done during MatSetValues() \
 57:                                         as more values are set than were prealloced */ \
 58:   PetscInt          rmax;               /* max nonzeros in any row */ \
 59:   PetscBool         keepnonzeropattern; /* keeps matrix structure same in calls to MatZeroRows()*/ \
 60:   PetscBool         ignorezeroentries; \
 61:   PetscBool         free_ij;       /* free the column indices j and row offsets i when the matrix is destroyed */ \
 62:   PetscBool         free_a;        /* free the numerical values when matrix is destroy */ \
 63:   Mat_CompressedRow compressedrow; /* use compressed row format */ \
 64:   PetscInt          nz;            /* nonzeros */ \
 65:   PetscInt         *i;             /* pointer to beginning of each row */ \
 66:   PetscInt         *j;             /* column values: j + i[k] - 1 is start of row k */ \
 67:   PetscInt         *diag;          /* pointers to diagonal elements */ \
 68:   PetscInt          nonzerorowcnt; /* how many rows have nonzero entries */ \
 69:   PetscBool         free_diag; \
 70:   datatype         *a;              /* nonzero elements */ \
 71:   PetscScalar      *solve_work;     /* work space used in MatSolve */ \
 72:   IS                row, col, icol; /* index sets, used for reorderings */ \
 73:   PetscBool         pivotinblocks;  /* pivot inside factorization of each diagonal block */ \
 74:   Mat               parent;         /* set if this matrix was formed with MatDuplicate(...,MAT_SHARE_NONZERO_PATTERN,....); \
 75:                                          means that this shares some data structures with the parent including diag, ilen, imax, i, j */ \
 76:   Mat_SubSppt      *submatis1;      /* used by MatCreateSubMatrices_MPIXAIJ_Local */ \
 77:   Mat_SeqAIJOps     ops[1]          /* operations for SeqAIJ and its subclasses */

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

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

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

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

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

115: /*
116:   MATSEQAIJ format - Compressed row storage (also called Yale sparse matrix
117:   format) or compressed sparse row (CSR).  The i[] and j[] arrays start at 0. For example,
118:   j[i[k]+p] is the pth column in row k.  Note that the diagonal
119:   matrix elements are stored with the rest of the nonzeros (not separately).
120: */

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

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

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

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

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

160:   /* MatSetValues() via hash related fields */
161:   PetscHMapIJV   ht;
162:   PetscInt      *dnz;
163:   struct _MatOps cops;
164: } Mat_SeqAIJ;

166: typedef struct {
167:   PetscInt    nz;   /* nz of the matrix after assembly */
168:   PetscCount  n;    /* Number of entries in MatSetPreallocationCOO() */
169:   PetscCount  Atot; /* Total number of valid (i.e., w/ non-negative indices) entries in the COO array */
170:   PetscCount *jmap; /* perm[jmap[i]..jmap[i+1]) give indices of entries in v[] associated with i-th nonzero of the matrix */
171:   PetscCount *perm; /* The permutation array in sorting (i,j) by row and then by col */
172: } MatCOOStruct_SeqAIJ;

174: #define MatSeqXAIJGetOptions_Private(A) \
175:   { \
176:     const PetscBool oldvalues = (PetscBool)(A != PETSC_NULLPTR); \
177:     PetscInt        nonew = 0, nounused = 0; \
178:     PetscBool       roworiented = PETSC_FALSE; \
179:     if (oldvalues) { \
180:       nonew       = ((Mat_SeqAIJ *)A->data)->nonew; \
181:       nounused    = ((Mat_SeqAIJ *)A->data)->nounused; \
182:       roworiented = ((Mat_SeqAIJ *)A->data)->roworiented; \
183:     } \
184:     (void)0

186: #define MatSeqXAIJRestoreOptions_Private(A) \
187:   if (oldvalues) { \
188:     ((Mat_SeqAIJ *)A->data)->nonew       = nonew; \
189:     ((Mat_SeqAIJ *)A->data)->nounused    = nounused; \
190:     ((Mat_SeqAIJ *)A->data)->roworiented = roworiented; \
191:   } \
192:   } \
193:   (void)0

195: /*
196:   Frees the a, i, and j arrays from the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
197: */
198: static inline PetscErrorCode MatSeqXAIJFreeAIJ(Mat AA, MatScalar **a, PetscInt **j, PetscInt **i)
199: {
200:   Mat_SeqAIJ *A = (Mat_SeqAIJ *)AA->data;

202:   PetscFunctionBegin;
203:   if (A->singlemalloc) {
204:     PetscCall(PetscFree3(*a, *j, *i));
205:   } else {
206:     if (A->free_a) PetscCall(PetscFree(*a));
207:     if (A->free_ij) PetscCall(PetscFree(*j));
208:     if (A->free_ij) PetscCall(PetscFree(*i));
209:   }
210:   PetscFunctionReturn(PETSC_SUCCESS);
211: }
212: /*
213:     Allocates larger a, i, and j arrays for the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
214:     This is a macro because it takes the datatype as an argument which can be either a Mat or a MatScalar
215: */
216: #define MatSeqXAIJReallocateAIJ(Amat, AM, BS2, NROW, ROW, COL, RMAX, AA, AI, AJ, RP, AP, AIMAX, NONEW, datatype) \
217:   do { \
218:     if (NROW >= RMAX) { \
219:       Mat_SeqAIJ *Ain = (Mat_SeqAIJ *)Amat->data; \
220:       /* there is no extra room in row, therefore enlarge */ \
221:       PetscInt  CHUNKSIZE = 15, new_nz = AI[AM] + CHUNKSIZE, len, *new_i = NULL, *new_j = NULL; \
222:       datatype *new_a; \
223: \
224:       PetscCheck(NONEW != -2, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "New nonzero at (%" PetscInt_FMT ",%" PetscInt_FMT ") caused a malloc. Use MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check", ROW, COL); \
225:       /* malloc new storage space */ \
226:       PetscCall(PetscMalloc3(BS2 *new_nz, &new_a, new_nz, &new_j, AM + 1, &new_i)); \
227: \
228:       /* copy over old data into new slots */ \
229:       for (ii = 0; ii < ROW + 1; ii++) new_i[ii] = AI[ii]; \
230:       for (ii = ROW + 1; ii < AM + 1; ii++) new_i[ii] = AI[ii] + CHUNKSIZE; \
231:       PetscCall(PetscArraycpy(new_j, AJ, AI[ROW] + NROW)); \
232:       len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
233:       PetscCall(PetscArraycpy(new_j + AI[ROW] + NROW + CHUNKSIZE, PetscSafePointerPlusOffset(AJ, AI[ROW] + NROW), len)); \
234:       PetscCall(PetscArraycpy(new_a, AA, BS2 *(AI[ROW] + NROW))); \
235:       PetscCall(PetscArrayzero(new_a + BS2 * (AI[ROW] + NROW), BS2 * CHUNKSIZE)); \
236:       PetscCall(PetscArraycpy(new_a + BS2 * (AI[ROW] + NROW + CHUNKSIZE), PetscSafePointerPlusOffset(AA, BS2 * (AI[ROW] + NROW)), BS2 * len)); \
237:       /* free up old matrix storage */ \
238:       PetscCall(MatSeqXAIJFreeAIJ(A, &Ain->a, &Ain->j, &Ain->i)); \
239:       AA     = new_a; \
240:       Ain->a = (MatScalar *)new_a; \
241:       AI = Ain->i = new_i; \
242:       AJ = Ain->j       = new_j; \
243:       Ain->singlemalloc = PETSC_TRUE; \
244: \
245:       RP   = AJ + AI[ROW]; \
246:       AP   = AA + BS2 * AI[ROW]; \
247:       RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
248:       Ain->maxnz += BS2 * CHUNKSIZE; \
249:       Ain->reallocs++; \
250:       Amat->nonzerostate++; \
251:     } \
252:   } while (0)

254: #define MatSeqXAIJReallocateAIJ_structure_only(Amat, AM, BS2, NROW, ROW, COL, RMAX, AI, AJ, RP, AIMAX, NONEW, datatype) \
255:   do { \
256:     if (NROW >= RMAX) { \
257:       Mat_SeqAIJ *Ain = (Mat_SeqAIJ *)Amat->data; \
258:       /* there is no extra room in row, therefore enlarge */ \
259:       PetscInt CHUNKSIZE = 15, new_nz = AI[AM] + CHUNKSIZE, len, *new_i = NULL, *new_j = NULL; \
260: \
261:       PetscCheck(NONEW != -2, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "New nonzero at (%" PetscInt_FMT ",%" PetscInt_FMT ") caused a malloc. Use MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check", ROW, COL); \
262:       /* malloc new storage space */ \
263:       PetscCall(PetscMalloc1(new_nz, &new_j)); \
264:       PetscCall(PetscMalloc1(AM + 1, &new_i)); \
265: \
266:       /* copy over old data into new slots */ \
267:       for (ii = 0; ii < ROW + 1; ii++) new_i[ii] = AI[ii]; \
268:       for (ii = ROW + 1; ii < AM + 1; ii++) new_i[ii] = AI[ii] + CHUNKSIZE; \
269:       PetscCall(PetscArraycpy(new_j, AJ, AI[ROW] + NROW)); \
270:       len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
271:       PetscCall(PetscArraycpy(new_j + AI[ROW] + NROW + CHUNKSIZE, AJ + AI[ROW] + NROW, len)); \
272: \
273:       /* free up old matrix storage */ \
274:       PetscCall(MatSeqXAIJFreeAIJ(A, &Ain->a, &Ain->j, &Ain->i)); \
275:       Ain->a = NULL; \
276:       AI = Ain->i = new_i; \
277:       AJ = Ain->j       = new_j; \
278:       Ain->singlemalloc = PETSC_FALSE; \
279:       Ain->free_a       = PETSC_FALSE; \
280: \
281:       RP   = AJ + AI[ROW]; \
282:       RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
283:       Ain->maxnz += BS2 * CHUNKSIZE; \
284:       Ain->reallocs++; \
285:       Amat->nonzerostate++; \
286:     } \
287:   } while (0)

289: PETSC_INTERN PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat, PetscInt, const PetscInt *);
290: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_SeqAIJ(Mat, PetscCount, PetscInt[], PetscInt[]);

292: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ(Mat, Mat, IS, IS, const MatFactorInfo *);
293: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_ilu0(Mat, Mat, IS, IS, const MatFactorInfo *);

295: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ(Mat, Mat, IS, const MatFactorInfo *);
296: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ(Mat, Mat, IS, const MatFactorInfo *);
297: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_inplace(Mat, Mat, const MatFactorInfo *);
298: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ(Mat, Mat, const MatFactorInfo *);
299: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ(Mat, MatDuplicateOption, Mat *);
300: PETSC_INTERN PetscErrorCode MatCopy_SeqAIJ(Mat, Mat, MatStructure);
301: PETSC_INTERN PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat, PetscBool *, PetscInt *);
302: PETSC_INTERN PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat);
303: PETSC_INTERN PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat, PetscInt *, PetscInt **);

305: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ(Mat, Vec, Vec);
306: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ_Inode(Mat, Vec, Vec);
307: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ(Mat, Vec, Vec, Vec);
308: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ_Inode(Mat, Vec, Vec, Vec);
309: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqAIJ(Mat, Vec, Vec);
310: PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat, Vec, Vec, Vec);
311: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec);
312: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ_Inode(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec);

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

316: PETSC_INTERN PetscErrorCode MatGetSymbolicTranspose_SeqAIJ(Mat, PetscInt *[], PetscInt *[]);
317: PETSC_INTERN PetscErrorCode MatRestoreSymbolicTranspose_SeqAIJ(Mat, PetscInt *[], PetscInt *[]);
318: PETSC_INTERN PetscErrorCode MatGetSymbolicTransposeReduced_SeqAIJ(Mat, PetscInt, PetscInt, PetscInt *[], PetscInt *[]);
319: PETSC_INTERN PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat, Mat *);
320: PETSC_INTERN PetscErrorCode MatTranspose_SeqAIJ(Mat, MatReuse, Mat *);

322: PETSC_INTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt, PetscInt *, PetscInt *, PetscBool, PetscInt, PetscInt, PetscInt **, PetscInt **);
323: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ(Mat, Mat, IS, IS, const MatFactorInfo *);
324: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_inplace(Mat, Mat, const MatFactorInfo *);
325: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ(Mat, Mat, const MatFactorInfo *);
326: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(Mat, Mat, const MatFactorInfo *);
327: PETSC_INTERN PetscErrorCode MatLUFactor_SeqAIJ(Mat, IS, IS, const MatFactorInfo *);
328: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_inplace(Mat, Vec, Vec);
329: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ(Mat, Vec, Vec);
330: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode(Mat, Vec, Vec);
331: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering(Mat, Vec, Vec);
332: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ(Mat, Vec, Vec, Vec);
333: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ_inplace(Mat, Vec, Vec);
334: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ(Mat, Vec, Vec);
335: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ_inplace(Mat, Vec, Vec, Vec);
336: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ(Mat, Vec, Vec, Vec);
337: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ(Mat, Mat, Mat);
338: PETSC_INTERN PetscErrorCode MatMatSolveTranspose_SeqAIJ(Mat, Mat, Mat);
339: PETSC_INTERN PetscErrorCode MatEqual_SeqAIJ(Mat, Mat, PetscBool *);
340: PETSC_INTERN PetscErrorCode MatFDColoringCreate_SeqXAIJ(Mat, ISColoring, MatFDColoring);
341: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_SeqXAIJ(Mat, ISColoring, MatFDColoring);
342: PETSC_INTERN PetscErrorCode MatFDColoringSetUpBlocked_AIJ_Private(Mat, MatFDColoring, PetscInt);
343: PETSC_INTERN PetscErrorCode MatLoad_AIJ_HDF5(Mat, PetscViewer);
344: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ_Binary(Mat, PetscViewer);
345: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ(Mat, PetscViewer);
346: PETSC_INTERN PetscErrorCode RegisterApplyPtAPRoutines_Private(Mat);

348: #if defined(PETSC_HAVE_HYPRE)
349: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_Transpose_AIJ_AIJ(Mat);
350: #endif
351: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_SeqAIJ(Mat);

353: PETSC_INTERN PetscErrorCode MatProductSymbolic_SeqAIJ_SeqAIJ(Mat);
354: PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat);
355: PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_SeqAIJ_SeqAIJ(Mat);

357: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
358: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Sorted(Mat, Mat, PetscReal, Mat);
359: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat, Mat, PetscReal, Mat);
360: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable(Mat, Mat, PetscReal, Mat);
361: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable_fast(Mat, Mat, PetscReal, Mat);
362: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Heap(Mat, Mat, PetscReal, Mat);
363: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_BTHeap(Mat, Mat, PetscReal, Mat);
364: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_RowMerge(Mat, Mat, PetscReal, Mat);
365: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_LLCondensed(Mat, Mat, PetscReal, Mat);
366: #if defined(PETSC_HAVE_HYPRE)
367: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_AIJ_AIJ_wHYPRE(Mat, Mat, PetscReal, Mat);
368: #endif

370: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
371: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Sorted(Mat, Mat, Mat);

373: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat, Mat, Mat);
374: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Scalable(Mat, Mat, Mat);

376: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat, Mat, PetscReal, Mat);
377: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
378: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat, Mat, Mat);

380: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
381: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_matmattransposemult(Mat, Mat, PetscReal, Mat);
382: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_colorrart(Mat, Mat, PetscReal, Mat);
383: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
384: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_matmattransposemult(Mat, Mat, Mat);
385: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_colorrart(Mat, Mat, Mat);

387: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
388: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
389: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_MatTransMatMult(void *);

391: PETSC_INTERN PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat);
392: PETSC_INTERN PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat);
393: PETSC_INTERN PetscErrorCode MatTransposeColoringCreate_SeqAIJ(Mat, ISColoring, MatTransposeColoring);
394: PETSC_INTERN PetscErrorCode MatTransColoringApplySpToDen_SeqAIJ(MatTransposeColoring, Mat, Mat);
395: PETSC_INTERN PetscErrorCode MatTransColoringApplyDenToSp_SeqAIJ(MatTransposeColoring, Mat, Mat);

397: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Mat, Mat, Mat, PetscReal, Mat);
398: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ(Mat, Mat, Mat, Mat);

400: PETSC_INTERN PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat, PetscInt, PetscInt, PetscRandom);
401: PETSC_INTERN PetscErrorCode MatSetValues_SeqAIJ(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode);
402: PETSC_INTERN PetscErrorCode MatGetRow_SeqAIJ(Mat, PetscInt, PetscInt *, PetscInt **, PetscScalar **);
403: PETSC_INTERN PetscErrorCode MatRestoreRow_SeqAIJ(Mat, PetscInt, PetscInt *, PetscInt **, PetscScalar **);
404: PETSC_INTERN PetscErrorCode MatScale_SeqAIJ(Mat, PetscScalar);
405: PETSC_INTERN PetscErrorCode MatDiagonalScale_SeqAIJ(Mat, Vec, Vec);
406: PETSC_INTERN PetscErrorCode MatDiagonalSet_SeqAIJ(Mat, Vec, InsertMode);
407: PETSC_INTERN PetscErrorCode MatAXPY_SeqAIJ(Mat, PetscScalar, Mat, MatStructure);
408: PETSC_INTERN PetscErrorCode MatGetRowIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
409: PETSC_INTERN PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
410: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
411: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *);
412: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscInt *[], PetscBool *);
413: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscInt *[], PetscBool *);
414: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ(Mat);
415: PETSC_INTERN PetscErrorCode MatView_SeqAIJ(Mat, PetscViewer);

417: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat);
418: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal_Inode(Mat);
419: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode(Mat);
420: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode_FactorLU(Mat);

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

424: #if defined(PETSC_HAVE_MATLAB)
425: PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject, void *);
426: PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject, void *);
427: #endif
428: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqSBAIJ(Mat, MatType, MatReuse, Mat *);
429: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *);
430: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat, MatType, MatReuse, Mat *);
431: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat, MatType, MatReuse, Mat *);
432: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat, MatType, MatReuse, Mat *);
433: #if defined(PETSC_HAVE_SCALAPACK)
434: PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *);
435: #endif
436: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat, MatType, MatReuse, Mat *);
437: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat, MatType, MatReuse, Mat *);
438: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJSELL(Mat, MatType, MatReuse, Mat *);
439: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat, MatType, MatReuse, Mat *);
440: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat, MatType, MatReuse, Mat *);
441: PETSC_INTERN PetscErrorCode MatReorderForNonzeroDiagonal_SeqAIJ(Mat, PetscReal, IS, IS);
442: PETSC_INTERN PetscErrorCode MatRARt_SeqAIJ_SeqAIJ(Mat, Mat, MatReuse, PetscReal, Mat *);
443: PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat);
444: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat, MatAssemblyType);
445: PETSC_EXTERN PetscErrorCode MatZeroEntries_SeqAIJ(Mat);

447: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt, const PetscInt *, const PetscInt *, const PetscInt *, const PetscInt *, PetscInt *);
448: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);
449: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm, Mat, PetscInt, MatReuse, Mat *);

451: PETSC_INTERN PetscErrorCode MatSetSeqMat_SeqAIJ(Mat, IS, IS, MatStructure, Mat);
452: PETSC_INTERN PetscErrorCode MatEliminateZeros_SeqAIJ(Mat, PetscBool);
453: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *);
454: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat);
455: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Dummy(Mat);
456: PETSC_INTERN PetscErrorCode MatDestroySubMatrices_Dummy(PetscInt, Mat *[]);
457: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat, IS, IS, PetscInt, MatReuse, Mat *);

459: PETSC_INTERN PetscErrorCode MatSetSeqAIJWithArrays_private(MPI_Comm, PetscInt, PetscInt, PetscInt[], PetscInt[], PetscScalar[], MatType, Mat);

461: PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat, ISLocalToGlobalMapping *);

463: /*
464:     PetscSparseDenseMinusDot - The inner kernel of triangular solves and Gauss-Siedel smoothing. \sum_i xv[i] * r[xi[i]] for CSR storage

466:   Input Parameters:
467: +  nnz - the number of entries
468: .  r - the array of vector values
469: .  xv - the matrix values for the row
470: -  xi - the column indices of the nonzeros in the row

472:   Output Parameter:
473: .  sum - negative the sum of results

475:   PETSc compile flags:
476: +   PETSC_KERNEL_USE_UNROLL_4
477: -   PETSC_KERNEL_USE_UNROLL_2

479:   Developer Note:
480:     The macro changes sum but not other parameters

482: .seealso: `PetscSparseDensePlusDot()`
483: */
484: #if defined(PETSC_KERNEL_USE_UNROLL_4)
485:   #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \
486:     do { \
487:       if (nnz > 0) { \
488:         PetscInt nnz2 = nnz, rem = nnz & 0x3; \
489:         switch (rem) { \
490:         case 3: \
491:           sum -= *xv++ * r[*xi++]; \
492:         case 2: \
493:           sum -= *xv++ * r[*xi++]; \
494:         case 1: \
495:           sum -= *xv++ * r[*xi++]; \
496:           nnz2 -= rem; \
497:         } \
498:         while (nnz2 > 0) { \
499:           sum -= xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
500:           xv += 4; \
501:           xi += 4; \
502:           nnz2 -= 4; \
503:         } \
504:         xv -= nnz; \
505:         xi -= nnz; \
506:       } \
507:     } while (0)

509: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
510:   #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \
511:     do { \
512:       PetscInt __i, __i1, __i2; \
513:       for (__i = 0; __i < nnz - 1; __i += 2) { \
514:         __i1 = xi[__i]; \
515:         __i2 = xi[__i + 1]; \
516:         sum -= (xv[__i] * r[__i1] + xv[__i + 1] * r[__i2]); \
517:       } \
518:       if (nnz & 0x1) sum -= xv[__i] * r[xi[__i]]; \
519:     } while (0)

521: #else
522:   #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \
523:     do { \
524:       PetscInt __i; \
525:       for (__i = 0; __i < nnz; __i++) sum -= xv[__i] * r[xi[__i]]; \
526:     } while (0)
527: #endif

529: /*
530:     PetscSparseDensePlusDot - The inner kernel of matrix-vector product \sum_i xv[i] * r[xi[i]] for CSR storage

532:   Input Parameters:
533: +  nnz - the number of entries
534: .  r - the array of vector values
535: .  xv - the matrix values for the row
536: -  xi - the column indices of the nonzeros in the row

538:   Output Parameter:
539: .  sum - the sum of results

541:   PETSc compile flags:
542: +   PETSC_KERNEL_USE_UNROLL_4
543: -   PETSC_KERNEL_USE_UNROLL_2

545:   Developer Note:
546:     The macro changes sum but not other parameters

548: .seealso: `PetscSparseDenseMinusDot()`
549: */
550: #if defined(PETSC_KERNEL_USE_UNROLL_4)
551:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \
552:     do { \
553:       if (nnz > 0) { \
554:         PetscInt nnz2 = nnz, rem = nnz & 0x3; \
555:         switch (rem) { \
556:         case 3: \
557:           sum += *xv++ * r[*xi++]; \
558:         case 2: \
559:           sum += *xv++ * r[*xi++]; \
560:         case 1: \
561:           sum += *xv++ * r[*xi++]; \
562:           nnz2 -= rem; \
563:         } \
564:         while (nnz2 > 0) { \
565:           sum += xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
566:           xv += 4; \
567:           xi += 4; \
568:           nnz2 -= 4; \
569:         } \
570:         xv -= nnz; \
571:         xi -= nnz; \
572:       } \
573:     } while (0)

575: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
576:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \
577:     do { \
578:       PetscInt __i, __i1, __i2; \
579:       for (__i = 0; __i < nnz - 1; __i += 2) { \
580:         __i1 = xi[__i]; \
581:         __i2 = xi[__i + 1]; \
582:         sum += (xv[__i] * r[__i1] + xv[__i + 1] * r[__i2]); \
583:       } \
584:       if (nnz & 0x1) sum += xv[__i] * r[xi[__i]]; \
585:     } while (0)

587: #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)
588:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) PetscSparseDensePlusDot_AVX512_Private(&(sum), (r), (xv), (xi), (nnz))

590: #else
591:   #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \
592:     do { \
593:       PetscInt __i; \
594:       for (__i = 0; __i < nnz; __i++) sum += xv[__i] * r[xi[__i]]; \
595:     } while (0)
596: #endif

598: #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)
599:   #include <immintrin.h>
600:   #if !defined(_MM_SCALE_8)
601:     #define _MM_SCALE_8 8
602:   #endif

604: static inline void PetscSparseDensePlusDot_AVX512_Private(PetscScalar *sum, const PetscScalar *x, const MatScalar *aa, const PetscInt *aj, PetscInt n)
605: {
606:   __m512d  vec_x, vec_y, vec_vals;
607:   __m256i  vec_idx;
608:   PetscInt j;

610:   vec_y = _mm512_setzero_pd();
611:   for (j = 0; j < (n >> 3); j++) {
612:     vec_idx  = _mm256_loadu_si256((__m256i const *)aj);
613:     vec_vals = _mm512_loadu_pd(aa);
614:     vec_x    = _mm512_i32gather_pd(vec_idx, x, _MM_SCALE_8);
615:     vec_y    = _mm512_fmadd_pd(vec_x, vec_vals, vec_y);
616:     aj += 8;
617:     aa += 8;
618:   }
619:   #if defined(__AVX512VL__)
620:   /* masked load requires avx512vl, which is not supported by KNL */
621:   if (n & 0x07) {
622:     __mmask8 mask;
623:     mask     = (__mmask8)(0xff >> (8 - (n & 0x07)));
624:     vec_idx  = _mm256_mask_loadu_epi32(vec_idx, mask, aj);
625:     vec_vals = _mm512_mask_loadu_pd(vec_vals, mask, aa);
626:     vec_x    = _mm512_mask_i32gather_pd(vec_x, mask, vec_idx, x, _MM_SCALE_8);
627:     vec_y    = _mm512_mask3_fmadd_pd(vec_x, vec_vals, vec_y, mask);
628:   }
629:   *sum += _mm512_reduce_add_pd(vec_y);
630:   #else
631:   *sum += _mm512_reduce_add_pd(vec_y);
632:   for (j = 0; j < (n & 0x07); j++) *sum += aa[j] * x[aj[j]];
633:   #endif
634: }
635: #endif

637: /*
638:     PetscSparseDenseMaxDot - The inner kernel of a modified matrix-vector product \max_i xv[i] * r[xi[i]] for CSR storage

640:   Input Parameters:
641: +  nnz - the number of entries
642: .  r - the array of vector values
643: .  xv - the matrix values for the row
644: -  xi - the column indices of the nonzeros in the row

646:   Output Parameter:
647: .  max - the max of results

649: .seealso: `PetscSparseDensePlusDot()`, `PetscSparseDenseMinusDot()`
650: */
651: #define PetscSparseDenseMaxDot(max, r, xv, xi, nnz) \
652:   do { \
653:     for (PetscInt __i = 0; __i < (nnz); __i++) { max = PetscMax(PetscRealPart(max), PetscRealPart((xv)[__i] * (r)[(xi)[__i]])); } \
654:   } while (0)

656: /*
657:  Add column indices into table for counting the max nonzeros of merged rows
658:  */
659: #define MatRowMergeMax_SeqAIJ(mat, nrows, ta) \
660:   do { \
661:     if (mat) { \
662:       for (PetscInt _row = 0; _row < (nrows); _row++) { \
663:         const PetscInt _nz = (mat)->i[_row + 1] - (mat)->i[_row]; \
664:         for (PetscInt _j = 0; _j < _nz; _j++) { \
665:           PetscInt *_col = _j + (mat)->j + (mat)->i[_row]; \
666:           PetscCall(PetscHMapISet((ta), *_col + 1, 1)); \
667:         } \
668:       } \
669:     } \
670:   } while (0)

672: /*
673:  Add column indices into table for counting the nonzeros of merged rows
674:  */
675: #define MatMergeRows_SeqAIJ(mat, nrows, rows, ta) \
676:   do { \
677:     for (PetscInt _i = 0; _i < (nrows); _i++) { \
678:       const PetscInt _row = (rows)[_i]; \
679:       const PetscInt _nz  = (mat)->i[_row + 1] - (mat)->i[_row]; \
680:       for (PetscInt _j = 0; _j < _nz; _j++) { \
681:         PetscInt *_col = _j + (mat)->j + (mat)->i[_row]; \
682:         PetscCall(PetscHMapISetWithMode((ta), *_col + 1, 1, INSERT_VALUES)); \
683:       } \
684:     } \
685:   } while (0)