Actual source code: aij.h
petsc-3.8.4 2018-03-24
5: #include <petsc/private/matimpl.h>
6: #include <petscctable.h>
8: /*
9: Struct header shared by SeqAIJ, SeqBAIJ and SeqSBAIJ matrix formats
10: */
11: #define SEQAIJHEADER(datatype) \
12: PetscBool roworiented; /* if true, row-oriented input, default */ \
13: PetscInt nonew; /* 1 don't add new nonzeros, -1 generate error on new */ \
14: PetscInt nounused; /* -1 generate error on unused space */ \
15: PetscBool singlemalloc; /* if true a, i, and j have been obtained with one big malloc */ \
16: PetscInt maxnz; /* allocated nonzeros */ \
17: PetscInt *imax; /* maximum space allocated for each row */ \
18: PetscInt *ilen; /* actual length of each row */ \
19: PetscBool free_imax_ilen; \
20: PetscInt reallocs; /* number of mallocs done during MatSetValues() \
21: as more values are set than were prealloced */\
22: PetscInt rmax; /* max nonzeros in any row */ \
23: PetscBool keepnonzeropattern; /* keeps matrix structure same in calls to MatZeroRows()*/ \
24: PetscBool ignorezeroentries; \
25: PetscBool free_ij; /* free the column indices j and row offsets i when the matrix is destroyed */ \
26: PetscBool free_a; /* free the numerical values when matrix is destroy */ \
27: Mat_CompressedRow compressedrow; /* use compressed row format */ \
28: PetscInt nz; /* nonzeros */ \
29: PetscInt *i; /* pointer to beginning of each row */ \
30: PetscInt *j; /* column values: j + i[k] - 1 is start of row k */ \
31: PetscInt *diag; /* pointers to diagonal elements */ \
32: PetscInt nonzerorowcnt; /* how many rows have nonzero entries */ \
33: PetscBool free_diag; \
34: datatype *a; /* nonzero elements */ \
35: PetscScalar *solve_work; /* work space used in MatSolve */ \
36: IS row, col, icol; /* index sets, used for reorderings */ \
37: PetscBool pivotinblocks; /* pivot inside factorization of each diagonal block */ \
38: Mat parent; /* set if this matrix was formed with MatDuplicate(...,MAT_SHARE_NONZERO_PATTERN,....); \
39: means that this shares some data structures with the parent including diag, ilen, imax, i, j */\
40: Mat_SubSppt *submatis1 /* used by MatCreateSubMatrices_MPIXAIJ_Local */
42: typedef struct {
43: MatTransposeColoring matcoloring;
44: Mat Bt_den; /* dense matrix of B^T */
45: Mat ABt_den; /* dense matrix of A*B^T */
46: PetscBool usecoloring;
47: PetscErrorCode (*destroy)(Mat);
48: } Mat_MatMatTransMult;
50: typedef struct { /* for MatTransposeMatMult_SeqAIJ_SeqDense() */
51: Mat mA; /* maij matrix of A */
52: Vec bt,ct; /* vectors to hold locally transposed arrays of B and C */
53: PetscErrorCode (*destroy)(Mat);
54: } Mat_MatTransMatMult;
56: typedef struct {
57: PetscInt *api,*apj; /* symbolic structure of A*P */
58: PetscScalar *apa; /* temporary array for storing one row of A*P */
59: PetscErrorCode (*destroy)(Mat);
60: } Mat_PtAP;
62: typedef struct {
63: MatTransposeColoring matcoloring;
64: Mat Rt; /* sparse or dense matrix of R^T */
65: Mat RARt; /* dense matrix of R*A*R^T */
66: Mat ARt; /* A*R^T used for the case -matrart_color_art */
67: MatScalar *work; /* work array to store columns of A*R^T used in MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqDense() */
68: PetscErrorCode (*destroy)(Mat);
69: } Mat_RARt;
71: typedef struct {
72: Mat BC; /* temp matrix for storing B*C */
73: PetscErrorCode (*destroy)(Mat);
74: } Mat_MatMatMatMult;
76: /*
77: MATSEQAIJ format - Compressed row storage (also called Yale sparse matrix
78: format) or compressed sparse row (CSR). The i[] and j[] arrays start at 0. For example,
79: j[i[k]+p] is the pth column in row k. Note that the diagonal
80: matrix elements are stored with the rest of the nonzeros (not separately).
81: */
83: /* Info about i-nodes (identical nodes) helper class for SeqAIJ */
84: typedef struct {
85: MatScalar *bdiag,*ibdiag,*ssor_work; /* diagonal blocks of matrix used for MatSOR_SeqAIJ_Inode() */
86: PetscInt bdiagsize; /* length of bdiag and ibdiag */
87: PetscBool ibdiagvalid; /* do ibdiag[] and bdiag[] contain the most recent values */
89: PetscBool use;
90: PetscInt node_count; /* number of inodes */
91: PetscInt *size; /* size of each inode */
92: PetscInt limit; /* inode limit */
93: PetscInt max_limit; /* maximum supported inode limit */
94: PetscBool checked; /* if inodes have been checked for */
95: PetscObjectState mat_nonzerostate; /* non-zero state when inodes were checked for */
96: } Mat_SeqAIJ_Inode;
98: PETSC_INTERN PetscErrorCode MatView_SeqAIJ_Inode(Mat,PetscViewer);
99: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ_Inode(Mat,MatAssemblyType);
100: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_Inode(Mat);
101: PETSC_INTERN PetscErrorCode MatCreate_SeqAIJ_Inode(Mat);
102: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ_Inode(Mat,MatOption,PetscBool);
103: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ_Inode(Mat,MatDuplicateOption,Mat*);
104: PETSC_INTERN PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat,Mat,MatDuplicateOption,PetscBool);
105: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode_inplace(Mat,Mat,const MatFactorInfo*);
106: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode(Mat,Mat,const MatFactorInfo*);
108: typedef struct {
109: SEQAIJHEADER(MatScalar);
110: Mat_SeqAIJ_Inode inode;
111: MatScalar *saved_values; /* location for stashing nonzero values of matrix */
113: PetscScalar *idiag,*mdiag,*ssor_work; /* inverse of diagonal entries, diagonal values and workspace for Eisenstat trick */
114: PetscBool idiagvalid; /* current idiag[] and mdiag[] are valid */
115: PetscScalar *ibdiag; /* inverses of block diagonals */
116: PetscBool ibdiagvalid; /* inverses of block diagonals are valid. */
117: PetscScalar fshift,omega; /* last used omega and fshift */
119: ISColoring coloring; /* set with MatADSetColoring() used by MatADSetValues() */
121: PetscScalar *matmult_abdense; /* used by MatMatMult() */
122: Mat_PtAP *ptap; /* used by MatPtAP() */
123: Mat_MatMatMatMult *matmatmatmult; /* used by MatMatMatMult() */
124: Mat_RARt *rart; /* used by MatRARt() */
125: Mat_MatMatTransMult *abt; /* used by MatMatTransposeMult() */
126: } Mat_SeqAIJ;
128: /*
129: Frees the a, i, and j arrays from the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
130: */
131: PETSC_STATIC_INLINE PetscErrorCode MatSeqXAIJFreeAIJ(Mat AA,MatScalar **a,PetscInt **j,PetscInt **i)
132: {
134: Mat_SeqAIJ *A = (Mat_SeqAIJ*) AA->data;
135: if (A->singlemalloc) {
136: PetscFree3(*a,*j,*i);
137: } else {
138: if (A->free_a) {PetscFree(*a);}
139: if (A->free_ij) {PetscFree(*j);}
140: if (A->free_ij) {PetscFree(*i);}
141: }
142: return 0;
143: }
144: /*
145: Allocates larger a, i, and j arrays for the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
146: This is a macro because it takes the datatype as an argument which can be either a Mat or a MatScalar
147: */
148: #define MatSeqXAIJReallocateAIJ(Amat,AM,BS2,NROW,ROW,COL,RMAX,AA,AI,AJ,RP,AP,AIMAX,NONEW,datatype) \
149: if (NROW >= RMAX) { \
150: Mat_SeqAIJ *Ain = (Mat_SeqAIJ*)Amat->data; \
151: /* there is no extra room in row, therefore enlarge */ \
152: PetscInt CHUNKSIZE = 15,new_nz = AI[AM] + CHUNKSIZE,len,*new_i=0,*new_j=0; \
153: datatype *new_a; \
154: \
155: if (NONEW == -2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"New nonzero at (%D,%D) caused a malloc\nUse MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check",ROW,COL); \
156: /* malloc new storage space */ \
157: PetscMalloc3(BS2*new_nz,&new_a,new_nz,&new_j,AM+1,&new_i); \
158: \
159: /* copy over old data into new slots */ \
160: for (ii=0; ii<ROW+1; ii++) {new_i[ii] = AI[ii];} \
161: for (ii=ROW+1; ii<AM+1; ii++) {new_i[ii] = AI[ii]+CHUNKSIZE;} \
162: PetscMemcpy(new_j,AJ,(AI[ROW]+NROW)*sizeof(PetscInt)); \
163: len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
164: PetscMemcpy(new_j+AI[ROW]+NROW+CHUNKSIZE,AJ+AI[ROW]+NROW,len*sizeof(PetscInt)); \
165: PetscMemcpy(new_a,AA,BS2*(AI[ROW]+NROW)*sizeof(datatype)); \
166: PetscMemzero(new_a+BS2*(AI[ROW]+NROW),BS2*CHUNKSIZE*sizeof(datatype)); \
167: PetscMemcpy(new_a+BS2*(AI[ROW]+NROW+CHUNKSIZE),AA+BS2*(AI[ROW]+NROW),BS2*len*sizeof(datatype)); \
168: /* free up old matrix storage */ \
169: MatSeqXAIJFreeAIJ(A,&Ain->a,&Ain->j,&Ain->i); \
170: AA = new_a; \
171: Ain->a = (MatScalar*) new_a; \
172: AI = Ain->i = new_i; AJ = Ain->j = new_j; \
173: Ain->singlemalloc = PETSC_TRUE; \
174: \
175: RP = AJ + AI[ROW]; AP = AA + BS2*AI[ROW]; \
176: RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
177: Ain->maxnz += BS2*CHUNKSIZE; \
178: Ain->reallocs++; \
179: } \
181: #define MatSeqXAIJReallocateAIJ_structure_only(Amat,AM,BS2,NROW,ROW,COL,RMAX,AI,AJ,RP,AIMAX,NONEW,datatype) \
182: if (NROW >= RMAX) { \
183: Mat_SeqAIJ *Ain = (Mat_SeqAIJ*)Amat->data; \
184: /* there is no extra room in row, therefore enlarge */ \
185: PetscInt CHUNKSIZE = 15,new_nz = AI[AM] + CHUNKSIZE,len,*new_i=0,*new_j=0; \
186: \
187: if (NONEW == -2) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"New nonzero at (%D,%D) caused a malloc\nUse MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check",ROW,COL); \
188: /* malloc new storage space */ \
189: PetscMalloc1(new_nz,&new_j); \
190: PetscMalloc1(AM+1,&new_i);\
191: \
192: /* copy over old data into new slots */ \
193: for (ii=0; ii<ROW+1; ii++) {new_i[ii] = AI[ii];} \
194: for (ii=ROW+1; ii<AM+1; ii++) {new_i[ii] = AI[ii]+CHUNKSIZE;} \
195: PetscMemcpy(new_j,AJ,(AI[ROW]+NROW)*sizeof(PetscInt)); \
196: len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
197: PetscMemcpy(new_j+AI[ROW]+NROW+CHUNKSIZE,AJ+AI[ROW]+NROW,len*sizeof(PetscInt)); \
198: \
199: /* free up old matrix storage */ \
200: MatSeqXAIJFreeAIJ(A,&Ain->a,&Ain->j,&Ain->i); \
201: Ain->a = NULL; \
202: AI = Ain->i = new_i; AJ = Ain->j = new_j; \
203: Ain->singlemalloc = PETSC_FALSE; \
204: Ain->free_a = PETSC_FALSE; \
205: \
206: RP = AJ + AI[ROW]; \
207: RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
208: Ain->maxnz += BS2*CHUNKSIZE; \
209: Ain->reallocs++; \
210: } \
212: PETSC_INTERN PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat,PetscInt,const PetscInt*);
213: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,IS,const MatFactorInfo*);
214: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ(Mat,Mat,IS,IS,const MatFactorInfo*);
215: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_ilu0(Mat,Mat,IS,IS,const MatFactorInfo*);
217: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,const MatFactorInfo*);
218: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ(Mat,Mat,IS,const MatFactorInfo*);
219: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,const MatFactorInfo*);
220: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ(Mat,Mat,IS,const MatFactorInfo*);
221: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_inplace(Mat,Mat,const MatFactorInfo*);
222: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ(Mat,Mat,const MatFactorInfo*);
223: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ(Mat,MatDuplicateOption,Mat*);
224: PETSC_INTERN PetscErrorCode MatCopy_SeqAIJ(Mat,Mat,MatStructure);
225: PETSC_INTERN PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat,PetscBool*,PetscInt*);
226: PETSC_INTERN PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat);
227: PETSC_INTERN PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat,PetscInt*,PetscInt**);
229: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ(Mat A,Vec,Vec);
230: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ(Mat A,Vec,Vec,Vec);
231: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqAIJ(Mat A,Vec,Vec);
232: PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat A,Vec,Vec,Vec);
233: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
235: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ(Mat,MatOption,PetscBool);
237: PETSC_INTERN PetscErrorCode MatGetSymbolicTranspose_SeqAIJ(Mat,PetscInt *[],PetscInt *[]);
238: PETSC_INTERN PetscErrorCode MatGetSymbolicTransposeReduced_SeqAIJ(Mat,PetscInt,PetscInt,PetscInt *[],PetscInt *[]);
239: PETSC_INTERN PetscErrorCode MatRestoreSymbolicTranspose_SeqAIJ(Mat,PetscInt *[],PetscInt *[]);
240: PETSC_INTERN PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat,Mat*);
241: PETSC_INTERN PetscErrorCode MatTranspose_SeqAIJ(Mat,MatReuse,Mat*);
242: PETSC_INTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt,PetscInt*,PetscInt*,PetscBool,PetscInt,PetscInt,PetscInt**,PetscInt**);
243: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,IS,const MatFactorInfo*);
244: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ(Mat,Mat,IS,IS,const MatFactorInfo*);
245: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_inplace(Mat,Mat,const MatFactorInfo*);
246: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ(Mat,Mat,const MatFactorInfo*);
247: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(Mat,Mat,const MatFactorInfo*);
248: PETSC_INTERN PetscErrorCode MatLUFactor_SeqAIJ(Mat,IS,IS,const MatFactorInfo*);
249: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_inplace(Mat,Vec,Vec);
250: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ(Mat,Vec,Vec);
251: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode_inplace(Mat,Vec,Vec);
252: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode(Mat,Vec,Vec);
253: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering_inplace(Mat,Vec,Vec);
254: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering(Mat,Vec,Vec);
255: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_InplaceWithPerm(Mat,Vec,Vec);
256: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ_inplace(Mat,Vec,Vec,Vec);
257: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ(Mat,Vec,Vec,Vec);
258: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ_inplace(Mat,Vec,Vec);
259: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ(Mat,Vec,Vec);
260: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ_inplace(Mat,Vec,Vec,Vec);
261: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ(Mat,Vec,Vec,Vec);
262: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ_inplace(Mat,Mat,Mat);
263: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ(Mat,Mat,Mat);
264: PETSC_INTERN PetscErrorCode MatEqual_SeqAIJ(Mat,Mat,PetscBool*);
265: PETSC_INTERN PetscErrorCode MatFDColoringCreate_SeqXAIJ(Mat,ISColoring,MatFDColoring);
266: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_SeqXAIJ(Mat,ISColoring,MatFDColoring);
267: PETSC_INTERN PetscErrorCode MatFDColoringSetUpBlocked_AIJ_Private(Mat,MatFDColoring,PetscInt);
268: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ(Mat,PetscViewer);
269: PETSC_INTERN PetscErrorCode RegisterApplyPtAPRoutines_Private(Mat);
271: PETSC_INTERN PetscErrorCode MatMatMult_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
272: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat*);
273: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat,Mat,PetscReal,Mat*);
274: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable(Mat,Mat,PetscReal,Mat*);
275: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable_fast(Mat,Mat,PetscReal,Mat*);
276: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Heap(Mat,Mat,PetscReal,Mat*);
277: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_BTHeap(Mat,Mat,PetscReal,Mat*);
278: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
279: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat,Mat,Mat);
280: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Scalable(Mat,Mat,Mat);
282: PETSC_INTERN PetscErrorCode MatPtAP_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
283: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_DenseAxpy(Mat,Mat,PetscReal,Mat*);
284: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat,Mat,PetscReal,Mat*);
285: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
286: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat,Mat,Mat);
288: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat*);
289: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_matmattransposemult(Mat,Mat,PetscReal,Mat*);
290: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_colorrart(Mat,Mat,PetscReal,Mat*);
291: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
292: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_matmattransposemult(Mat,Mat,Mat);
293: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_colorrart(Mat,Mat,Mat);
295: PETSC_INTERN PetscErrorCode MatTransposeMatMult_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
296: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat*);
297: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
299: PETSC_INTERN PetscErrorCode MatTransposeMatMult_SeqAIJ_SeqDense(Mat,Mat,MatReuse,PetscReal,Mat*);
300: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqDense(Mat,Mat,PetscReal,Mat*);
301: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqDense(Mat,Mat,Mat);
303: PETSC_INTERN PetscErrorCode MatMatTransposeMult_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
304: PETSC_INTERN PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat*);
305: PETSC_INTERN PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
306: PETSC_INTERN PetscErrorCode MatTransposeColoringCreate_SeqAIJ(Mat,ISColoring,MatTransposeColoring);
307: PETSC_INTERN PetscErrorCode MatTransColoringApplySpToDen_SeqAIJ(MatTransposeColoring,Mat,Mat);
308: PETSC_INTERN PetscErrorCode MatTransColoringApplyDenToSp_SeqAIJ(MatTransposeColoring,Mat,Mat);
310: PETSC_INTERN PetscErrorCode MatMatMatMult_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
311: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,PetscReal,Mat*);
312: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,Mat);
314: PETSC_INTERN PetscErrorCode MatSetValues_SeqAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
315: PETSC_INTERN PetscErrorCode MatGetRow_SeqAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
316: PETSC_INTERN PetscErrorCode MatRestoreRow_SeqAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
317: PETSC_INTERN PetscErrorCode MatScale_SeqAIJ(Mat,PetscScalar);
318: PETSC_INTERN PetscErrorCode MatDiagonalScale_SeqAIJ(Mat,Vec,Vec);
319: PETSC_INTERN PetscErrorCode MatDiagonalSet_SeqAIJ(Mat,Vec,InsertMode);
320: PETSC_INTERN PetscErrorCode MatAXPY_SeqAIJ(Mat,PetscScalar,Mat,MatStructure);
321: PETSC_INTERN PetscErrorCode MatGetRowIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
322: PETSC_INTERN PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
323: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
324: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
325: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscInt *[],PetscBool*);
326: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscInt *[],PetscBool*);
327: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ(Mat);
328: PETSC_INTERN PetscErrorCode MatSetUp_SeqAIJ(Mat);
329: PETSC_INTERN PetscErrorCode MatView_SeqAIJ(Mat,PetscViewer);
331: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat);
332: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal_Inode(Mat);
333: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode(Mat);
334: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode_FactorLU(Mat);
336: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat,Mat,PetscInt*);
338: PETSC_INTERN PetscErrorCode MatMatMatMult_Transpose_AIJ_AIJ(Mat,Mat,Mat,MatReuse,PetscReal,Mat*);
339: PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*);
340: PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*);
341: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqSBAIJ(Mat,MatType,MatReuse,Mat*);
342: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqBAIJ(Mat,MatType,MatReuse,Mat*);
343: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*);
344: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*);
345: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
346: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
347: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,MatType,MatReuse,Mat*);
348: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat,MatType,MatReuse,Mat*);
349: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat,MatType,MatReuse,Mat*);
350: PETSC_INTERN PetscErrorCode MatReorderForNonzeroDiagonal_SeqAIJ(Mat,PetscReal,IS,IS);
351: PETSC_INTERN PetscErrorCode MatMatMult_SeqDense_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
352: PETSC_INTERN PetscErrorCode MatRARt_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
353: PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat);
354: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat,MatAssemblyType);
356: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt,const PetscInt*,const PetscInt*,const PetscInt*,const PetscInt*,PetscInt*);
357: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
358: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
360: PETSC_INTERN PetscErrorCode MatSetSeqMat_SeqAIJ(Mat,IS,IS,MatStructure,Mat);
361: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt*);
362: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat);
363: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Dummy(Mat);
364: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat,IS,IS,PetscInt,MatReuse,Mat*);
366: /*
367: PetscSparseDenseMinusDot - The inner kernel of triangular solves and Gauss-Siedel smoothing. \sum_i xv[i] * r[xi[i]] for CSR storage
369: Input Parameters:
370: + nnz - the number of entries
371: . r - the array of vector values
372: . xv - the matrix values for the row
373: - xi - the column indices of the nonzeros in the row
375: Output Parameter:
376: . sum - negative the sum of results
378: PETSc compile flags:
379: + PETSC_KERNEL_USE_UNROLL_4 - don't use this; it changes nnz and hence is WRONG
380: - PETSC_KERNEL_USE_UNROLL_2 -
382: .seealso: PetscSparseDensePlusDot()
384: */
385: #if defined(PETSC_KERNEL_USE_UNROLL_4)
386: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
387: if (nnz > 0) { \
388: switch (nnz & 0x3) { \
389: case 3: sum -= *xv++ *r[*xi++]; \
390: case 2: sum -= *xv++ *r[*xi++]; \
391: case 1: sum -= *xv++ *r[*xi++]; \
392: nnz -= 4;} \
393: while (nnz > 0) { \
394: sum -= xv[0] * r[xi[0]] - xv[1] * r[xi[1]] - \
395: xv[2] * r[xi[2]] - xv[3] * r[xi[3]]; \
396: xv += 4; xi += 4; nnz -= 4; }}}
398: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
399: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
400: PetscInt __i,__i1,__i2; \
401: for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
402: sum -= (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
403: if (nnz & 0x1) sum -= xv[__i] * r[xi[__i]];}
405: #else
406: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
407: PetscInt __i; \
408: for (__i=0; __i<nnz; __i++) sum -= xv[__i] * r[xi[__i]];}
409: #endif
413: /*
414: PetscSparseDensePlusDot - The inner kernel of matrix-vector product \sum_i xv[i] * r[xi[i]] for CSR storage
416: Input Parameters:
417: + nnz - the number of entries
418: . r - the array of vector values
419: . xv - the matrix values for the row
420: - xi - the column indices of the nonzeros in the row
422: Output Parameter:
423: . sum - the sum of results
425: PETSc compile flags:
426: + PETSC_KERNEL_USE_UNROLL_4 - don't use this; it changes nnz and hence is WRONG
427: - PETSC_KERNEL_USE_UNROLL_2 -
429: .seealso: PetscSparseDenseMinusDot()
431: */
432: #if defined(PETSC_KERNEL_USE_UNROLL_4)
433: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
434: if (nnz > 0) { \
435: switch (nnz & 0x3) { \
436: case 3: sum += *xv++ *r[*xi++]; \
437: case 2: sum += *xv++ *r[*xi++]; \
438: case 1: sum += *xv++ *r[*xi++]; \
439: nnz -= 4;} \
440: while (nnz > 0) { \
441: sum += xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + \
442: xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
443: xv += 4; xi += 4; nnz -= 4; }}}
445: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
446: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
447: PetscInt __i,__i1,__i2; \
448: for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
449: sum += (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
450: if (nnz & 0x1) sum += xv[__i] * r[xi[__i]];}
452: #else
453: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
454: PetscInt __i; \
455: for (__i=0; __i<nnz; __i++) sum += xv[__i] * r[xi[__i]];}
456: #endif
459: /*
460: PetscSparseDenseMaxDot - The inner kernel of a modified matrix-vector product \max_i xv[i] * r[xi[i]] for CSR storage
462: Input Parameters:
463: + nnz - the number of entries
464: . r - the array of vector values
465: . xv - the matrix values for the row
466: - xi - the column indices of the nonzeros in the row
468: Output Parameter:
469: . max - the max of results
471: .seealso: PetscSparseDensePlusDot(), PetscSparseDenseMinusDot()
473: */
474: #define PetscSparseDenseMaxDot(max,r,xv,xi,nnz) { \
475: PetscInt __i; \
476: for (__i=0; __i<nnz; __i++) max = PetscMax(PetscRealPart(max), PetscRealPart(xv[__i] * r[xi[__i]]));}
478: /*
479: Add column indices into table for counting the max nonzeros of merged rows
480: */
481: #define MatRowMergeMax_SeqAIJ(mat,nrows,ta) { \
482: PetscInt _j,_row,_nz,*_col; \
483: if (mat) { \
484: for (_row=0; _row<nrows; _row++) { \
485: _nz = mat->i[_row+1] - mat->i[_row]; \
486: for (_j=0; _j<_nz; _j++) { \
487: _col = _j + mat->j + mat->i[_row]; \
488: PetscTableAdd(ta,*_col+1,1,INSERT_VALUES); \
489: } \
490: } \
491: } \
492: }
494: /*
495: Add column indices into table for counting the nonzeros of merged rows
496: */
497: #define MatMergeRows_SeqAIJ(mat,nrows,rows,ta) { \
498: PetscInt _j,_row,_nz,*_col,_i; \
499: for (_i=0; _i<nrows; _i++) {\
500: _row = rows[_i]; \
501: _nz = mat->i[_row+1] - mat->i[_row]; \
502: for (_j=0; _j<_nz; _j++) { \
503: _col = _j + mat->j + mat->i[_row]; \
504: PetscTableAdd(ta,*_col+1,1,INSERT_VALUES); \
505: } \
506: } \
507: }
509: #endif