Actual source code: aij.h
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: PetscInt *ipre; /* space preallocated for each row by user */ \
20: PetscBool free_imax_ilen; \
21: PetscInt reallocs; /* number of mallocs done during MatSetValues() \
22: as more values are set than were prealloced */\
23: PetscInt rmax; /* max nonzeros in any row */ \
24: PetscBool keepnonzeropattern; /* keeps matrix structure same in calls to MatZeroRows()*/ \
25: PetscBool ignorezeroentries; \
26: PetscBool free_ij; /* free the column indices j and row offsets i when the matrix is destroyed */ \
27: PetscBool free_a; /* free the numerical values when matrix is destroy */ \
28: Mat_CompressedRow compressedrow; /* use compressed row format */ \
29: PetscInt nz; /* nonzeros */ \
30: PetscInt *i; /* pointer to beginning of each row */ \
31: PetscInt *j; /* column values: j + i[k] - 1 is start of row k */ \
32: PetscInt *diag; /* pointers to diagonal elements */ \
33: PetscInt nonzerorowcnt; /* how many rows have nonzero entries */ \
34: PetscBool free_diag; \
35: datatype *a; /* nonzero elements */ \
36: PetscScalar *solve_work; /* work space used in MatSolve */ \
37: IS row, col, icol; /* index sets, used for reorderings */ \
38: PetscBool pivotinblocks; /* pivot inside factorization of each diagonal block */ \
39: Mat parent; /* set if this matrix was formed with MatDuplicate(...,MAT_SHARE_NONZERO_PATTERN,....); \
40: means that this shares some data structures with the parent including diag, ilen, imax, i, j */\
41: Mat_SubSppt *submatis1 /* used by MatCreateSubMatrices_MPIXAIJ_Local */
43: typedef struct {
44: MatTransposeColoring matcoloring;
45: Mat Bt_den; /* dense matrix of B^T */
46: Mat ABt_den; /* dense matrix of A*B^T */
47: PetscBool usecoloring;
48: } Mat_MatMatTransMult;
50: typedef struct { /* used by MatTransposeMatMult() */
51: Mat At; /* transpose of the first matrix */
52: Mat mA; /* maij matrix of A */
53: Vec bt,ct; /* vectors to hold locally transposed arrays of B and C */
54: PetscBool updateAt; /* flg to avoid recomputing At in MatProductNumeric_AtB_SeqAIJ_SeqAIJ() */
55: /* used by PtAP */
56: void *data;
57: PetscErrorCode (*destroy)(void*);
58: } Mat_MatTransMatMult;
60: typedef struct {
61: PetscInt *api,*apj; /* symbolic structure of A*P */
62: PetscScalar *apa; /* temporary array for storing one row of A*P */
63: } Mat_AP;
65: typedef struct {
66: MatTransposeColoring matcoloring;
67: Mat Rt; /* sparse or dense matrix of R^T */
68: Mat RARt; /* dense matrix of R*A*R^T */
69: Mat ARt; /* A*R^T used for the case -matrart_color_art */
70: MatScalar *work; /* work array to store columns of A*R^T used in MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqDense() */
71: /* free intermediate products needed for PtAP */
72: void *data;
73: PetscErrorCode (*destroy)(void*);
74: } Mat_RARt;
76: typedef struct {
77: Mat BC; /* temp matrix for storing B*C */
78: } Mat_MatMatMatMult;
80: /*
81: MATSEQAIJ format - Compressed row storage (also called Yale sparse matrix
82: format) or compressed sparse row (CSR). The i[] and j[] arrays start at 0. For example,
83: j[i[k]+p] is the pth column in row k. Note that the diagonal
84: matrix elements are stored with the rest of the nonzeros (not separately).
85: */
87: /* Info about i-nodes (identical nodes) helper class for SeqAIJ */
88: typedef struct {
89: MatScalar *bdiag,*ibdiag,*ssor_work; /* diagonal blocks of matrix used for MatSOR_SeqAIJ_Inode() */
90: PetscInt bdiagsize; /* length of bdiag and ibdiag */
91: PetscBool ibdiagvalid; /* do ibdiag[] and bdiag[] contain the most recent values */
93: PetscBool use;
94: PetscInt node_count; /* number of inodes */
95: PetscInt *size; /* size of each inode */
96: PetscInt limit; /* inode limit */
97: PetscInt max_limit; /* maximum supported inode limit */
98: PetscBool checked; /* if inodes have been checked for */
99: PetscObjectState mat_nonzerostate; /* non-zero state when inodes were checked for */
100: } Mat_SeqAIJ_Inode;
102: PETSC_INTERN PetscErrorCode MatView_SeqAIJ_Inode(Mat,PetscViewer);
103: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ_Inode(Mat,MatAssemblyType);
104: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_Inode(Mat);
105: PETSC_INTERN PetscErrorCode MatCreate_SeqAIJ_Inode(Mat);
106: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ_Inode(Mat,MatOption,PetscBool);
107: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ_Inode(Mat,MatDuplicateOption,Mat*);
108: PETSC_INTERN PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat,Mat,MatDuplicateOption,PetscBool);
109: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode_inplace(Mat,Mat,const MatFactorInfo*);
110: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode(Mat,Mat,const MatFactorInfo*);
111: PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat,PetscScalar**);
112: PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat,PetscScalar**);
114: typedef struct {
115: SEQAIJHEADER(MatScalar);
116: Mat_SeqAIJ_Inode inode;
117: MatScalar *saved_values; /* location for stashing nonzero values of matrix */
119: PetscScalar *idiag,*mdiag,*ssor_work; /* inverse of diagonal entries, diagonal values and workspace for Eisenstat trick */
120: PetscBool idiagvalid; /* current idiag[] and mdiag[] are valid */
121: PetscScalar *ibdiag; /* inverses of block diagonals */
122: PetscBool ibdiagvalid; /* inverses of block diagonals are valid. */
123: PetscBool diagonaldense; /* all entries along the diagonal have been set; i.e. no missing diagonal terms */
124: PetscScalar fshift,omega; /* last used omega and fshift */
125: } Mat_SeqAIJ;
127: /*
128: Frees the a, i, and j arrays from the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
129: */
130: PETSC_STATIC_INLINE PetscErrorCode MatSeqXAIJFreeAIJ(Mat AA,MatScalar **a,PetscInt **j,PetscInt **i)
131: {
133: Mat_SeqAIJ *A = (Mat_SeqAIJ*) AA->data;
134: if (A->singlemalloc) {
135: PetscFree3(*a,*j,*i);
136: } else {
137: if (A->free_a) {PetscFree(*a);}
138: if (A->free_ij) {PetscFree(*j);}
139: if (A->free_ij) {PetscFree(*i);}
140: }
141: return 0;
142: }
143: /*
144: Allocates larger a, i, and j arrays for the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
145: This is a macro because it takes the datatype as an argument which can be either a Mat or a MatScalar
146: */
147: #define MatSeqXAIJReallocateAIJ(Amat,AM,BS2,NROW,ROW,COL,RMAX,AA,AI,AJ,RP,AP,AIMAX,NONEW,datatype) \
148: if (NROW >= RMAX) { \
149: Mat_SeqAIJ *Ain = (Mat_SeqAIJ*)Amat->data; \
150: /* there is no extra room in row, therefore enlarge */ \
151: PetscInt CHUNKSIZE = 15,new_nz = AI[AM] + CHUNKSIZE,len,*new_i=NULL,*new_j=NULL; \
152: datatype *new_a; \
153: \
154: 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); \
155: /* malloc new storage space */ \
156: PetscMalloc3(BS2*new_nz,&new_a,new_nz,&new_j,AM+1,&new_i); \
157: \
158: /* copy over old data into new slots */ \
159: for (ii=0; ii<ROW+1; ii++) {new_i[ii] = AI[ii];} \
160: for (ii=ROW+1; ii<AM+1; ii++) {new_i[ii] = AI[ii]+CHUNKSIZE;} \
161: PetscArraycpy(new_j,AJ,AI[ROW]+NROW); \
162: len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
163: PetscArraycpy(new_j+AI[ROW]+NROW+CHUNKSIZE,AJ+AI[ROW]+NROW,len); \
164: PetscArraycpy(new_a,AA,BS2*(AI[ROW]+NROW)); \
165: PetscArrayzero(new_a+BS2*(AI[ROW]+NROW),BS2*CHUNKSIZE); \
166: PetscArraycpy(new_a+BS2*(AI[ROW]+NROW+CHUNKSIZE),AA+BS2*(AI[ROW]+NROW),BS2*len); \
167: /* free up old matrix storage */ \
168: MatSeqXAIJFreeAIJ(A,&Ain->a,&Ain->j,&Ain->i); \
169: AA = new_a; \
170: Ain->a = (MatScalar*) new_a; \
171: AI = Ain->i = new_i; AJ = Ain->j = new_j; \
172: Ain->singlemalloc = PETSC_TRUE; \
173: \
174: RP = AJ + AI[ROW]; AP = AA + BS2*AI[ROW]; \
175: RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
176: Ain->maxnz += BS2*CHUNKSIZE; \
177: Ain->reallocs++; \
178: } \
180: #define MatSeqXAIJReallocateAIJ_structure_only(Amat,AM,BS2,NROW,ROW,COL,RMAX,AI,AJ,RP,AIMAX,NONEW,datatype) \
181: if (NROW >= RMAX) { \
182: Mat_SeqAIJ *Ain = (Mat_SeqAIJ*)Amat->data; \
183: /* there is no extra room in row, therefore enlarge */ \
184: PetscInt CHUNKSIZE = 15,new_nz = AI[AM] + CHUNKSIZE,len,*new_i=NULL,*new_j=NULL; \
185: \
186: 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); \
187: /* malloc new storage space */ \
188: PetscMalloc1(new_nz,&new_j); \
189: PetscMalloc1(AM+1,&new_i);\
190: \
191: /* copy over old data into new slots */ \
192: for (ii=0; ii<ROW+1; ii++) {new_i[ii] = AI[ii];} \
193: for (ii=ROW+1; ii<AM+1; ii++) {new_i[ii] = AI[ii]+CHUNKSIZE;} \
194: PetscArraycpy(new_j,AJ,AI[ROW]+NROW); \
195: len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
196: PetscArraycpy(new_j+AI[ROW]+NROW+CHUNKSIZE,AJ+AI[ROW]+NROW,len); \
197: \
198: /* free up old matrix storage */ \
199: MatSeqXAIJFreeAIJ(A,&Ain->a,&Ain->j,&Ain->i); \
200: Ain->a = NULL; \
201: AI = Ain->i = new_i; AJ = Ain->j = new_j; \
202: Ain->singlemalloc = PETSC_FALSE; \
203: Ain->free_a = PETSC_FALSE; \
204: \
205: RP = AJ + AI[ROW]; \
206: RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
207: Ain->maxnz += BS2*CHUNKSIZE; \
208: Ain->reallocs++; \
209: } \
211: PETSC_INTERN PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat,PetscInt,const PetscInt*);
212: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,IS,const MatFactorInfo*);
213: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ(Mat,Mat,IS,IS,const MatFactorInfo*);
214: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_ilu0(Mat,Mat,IS,IS,const MatFactorInfo*);
216: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,const MatFactorInfo*);
217: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ(Mat,Mat,IS,const MatFactorInfo*);
218: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,const MatFactorInfo*);
219: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ(Mat,Mat,IS,const MatFactorInfo*);
220: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_inplace(Mat,Mat,const MatFactorInfo*);
221: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ(Mat,Mat,const MatFactorInfo*);
222: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ(Mat,MatDuplicateOption,Mat*);
223: PETSC_INTERN PetscErrorCode MatCopy_SeqAIJ(Mat,Mat,MatStructure);
224: PETSC_INTERN PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat,PetscBool*,PetscInt*);
225: PETSC_INTERN PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat);
226: PETSC_INTERN PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat,PetscInt*,PetscInt**);
228: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ(Mat,Vec,Vec);
229: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ_Inode(Mat,Vec,Vec);
230: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ(Mat,Vec,Vec,Vec);
231: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ_Inode(Mat,Vec,Vec,Vec);
232: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqAIJ(Mat,Vec,Vec);
233: PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat,Vec,Vec,Vec);
234: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
235: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ_Inode(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
237: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ(Mat,MatOption,PetscBool);
239: PETSC_INTERN PetscErrorCode MatGetSymbolicTranspose_SeqAIJ(Mat,PetscInt *[],PetscInt *[]);
240: PETSC_INTERN PetscErrorCode MatGetSymbolicTransposeReduced_SeqAIJ(Mat,PetscInt,PetscInt,PetscInt *[],PetscInt *[]);
241: PETSC_INTERN PetscErrorCode MatRestoreSymbolicTranspose_SeqAIJ(Mat,PetscInt *[],PetscInt *[]);
242: PETSC_INTERN PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat,Mat*);
243: PETSC_INTERN PetscErrorCode MatTranspose_SeqAIJ(Mat,MatReuse,Mat*);
244: PETSC_INTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt,PetscInt*,PetscInt*,PetscBool,PetscInt,PetscInt,PetscInt**,PetscInt**);
245: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,IS,const MatFactorInfo*);
246: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ(Mat,Mat,IS,IS,const MatFactorInfo*);
247: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_inplace(Mat,Mat,const MatFactorInfo*);
248: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ(Mat,Mat,const MatFactorInfo*);
249: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(Mat,Mat,const MatFactorInfo*);
250: PETSC_INTERN PetscErrorCode MatLUFactor_SeqAIJ(Mat,IS,IS,const MatFactorInfo*);
251: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_inplace(Mat,Vec,Vec);
252: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ(Mat,Vec,Vec);
253: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode_inplace(Mat,Vec,Vec);
254: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode(Mat,Vec,Vec);
255: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering_inplace(Mat,Vec,Vec);
256: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering(Mat,Vec,Vec);
257: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_InplaceWithPerm(Mat,Vec,Vec);
258: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ_inplace(Mat,Vec,Vec,Vec);
259: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ(Mat,Vec,Vec,Vec);
260: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ_inplace(Mat,Vec,Vec);
261: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ(Mat,Vec,Vec);
262: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ_inplace(Mat,Vec,Vec,Vec);
263: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ(Mat,Vec,Vec,Vec);
264: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ_inplace(Mat,Mat,Mat);
265: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ(Mat,Mat,Mat);
266: PETSC_INTERN PetscErrorCode MatEqual_SeqAIJ(Mat,Mat,PetscBool*);
267: PETSC_INTERN PetscErrorCode MatFDColoringCreate_SeqXAIJ(Mat,ISColoring,MatFDColoring);
268: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_SeqXAIJ(Mat,ISColoring,MatFDColoring);
269: PETSC_INTERN PetscErrorCode MatFDColoringSetUpBlocked_AIJ_Private(Mat,MatFDColoring,PetscInt);
270: PETSC_INTERN PetscErrorCode MatLoad_AIJ_HDF5(Mat,PetscViewer);
271: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ_Binary(Mat,PetscViewer);
272: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ(Mat,PetscViewer);
273: PETSC_INTERN PetscErrorCode RegisterApplyPtAPRoutines_Private(Mat);
275: #if defined(PETSC_HAVE_HYPRE)
276: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_Transpose_AIJ_AIJ(Mat);
277: #endif
278: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_SeqAIJ(Mat);
280: PETSC_INTERN PetscErrorCode MatProductSymbolic_SeqAIJ_SeqAIJ(Mat);
281: PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat);
282: PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_SeqAIJ_SeqAIJ(Mat);
284: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
285: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Sorted(Mat,Mat,PetscReal,Mat);
286: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat,Mat,PetscReal,Mat);
287: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable(Mat,Mat,PetscReal,Mat);
288: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable_fast(Mat,Mat,PetscReal,Mat);
289: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Heap(Mat,Mat,PetscReal,Mat);
290: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_BTHeap(Mat,Mat,PetscReal,Mat);
291: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_RowMerge(Mat,Mat,PetscReal,Mat);
292: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_LLCondensed(Mat,Mat,PetscReal,Mat);
293: #if defined(PETSC_HAVE_HYPRE)
294: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat);
295: #endif
297: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
298: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Sorted(Mat,Mat,Mat);
300: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat,Mat,Mat);
301: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Scalable(Mat,Mat,Mat);
303: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat,Mat,PetscReal,Mat);
304: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
305: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat,Mat,Mat);
307: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
308: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_matmattransposemult(Mat,Mat,PetscReal,Mat);
309: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_colorrart(Mat,Mat,PetscReal,Mat);
310: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
311: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_matmattransposemult(Mat,Mat,Mat);
312: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_colorrart(Mat,Mat,Mat);
314: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
315: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
316: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_MatTransMatMult(void*);
318: PETSC_INTERN PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
319: PETSC_INTERN PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
320: PETSC_INTERN PetscErrorCode MatTransposeColoringCreate_SeqAIJ(Mat,ISColoring,MatTransposeColoring);
321: PETSC_INTERN PetscErrorCode MatTransColoringApplySpToDen_SeqAIJ(MatTransposeColoring,Mat,Mat);
322: PETSC_INTERN PetscErrorCode MatTransColoringApplyDenToSp_SeqAIJ(MatTransposeColoring,Mat,Mat);
324: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,PetscReal,Mat);
325: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,Mat);
327: PETSC_INTERN PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat,PetscInt,PetscInt,PetscRandom);
328: PETSC_INTERN PetscErrorCode MatSetValues_SeqAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
329: PETSC_INTERN PetscErrorCode MatGetRow_SeqAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
330: PETSC_INTERN PetscErrorCode MatRestoreRow_SeqAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
331: PETSC_INTERN PetscErrorCode MatScale_SeqAIJ(Mat,PetscScalar);
332: PETSC_INTERN PetscErrorCode MatDiagonalScale_SeqAIJ(Mat,Vec,Vec);
333: PETSC_INTERN PetscErrorCode MatDiagonalSet_SeqAIJ(Mat,Vec,InsertMode);
334: PETSC_INTERN PetscErrorCode MatAXPY_SeqAIJ(Mat,PetscScalar,Mat,MatStructure);
335: PETSC_INTERN PetscErrorCode MatGetRowIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
336: PETSC_INTERN PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
337: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
338: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
339: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscInt *[],PetscBool*);
340: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscInt *[],PetscBool*);
341: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ(Mat);
342: PETSC_INTERN PetscErrorCode MatSetUp_SeqAIJ(Mat);
343: PETSC_INTERN PetscErrorCode MatView_SeqAIJ(Mat,PetscViewer);
345: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat);
346: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal_Inode(Mat);
347: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode(Mat);
348: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode_FactorLU(Mat);
350: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat,Mat,PetscInt*);
352: #if defined(PETSC_HAVE_MATLAB_ENGINE)
353: PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*);
354: PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*);
355: #endif
356: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqSBAIJ(Mat,MatType,MatReuse,Mat*);
357: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqBAIJ(Mat,MatType,MatReuse,Mat*);
358: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*);
359: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*);
360: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
361: #if defined(PETSC_HAVE_SCALAPACK)
362: PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
363: #endif
364: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
365: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,MatType,MatReuse,Mat*);
366: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJSELL(Mat,MatType,MatReuse,Mat*);
367: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat,MatType,MatReuse,Mat*);
368: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat,MatType,MatReuse,Mat*);
369: PETSC_INTERN PetscErrorCode MatReorderForNonzeroDiagonal_SeqAIJ(Mat,PetscReal,IS,IS);
370: PETSC_INTERN PetscErrorCode MatRARt_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
371: PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat);
372: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat,MatAssemblyType);
373: PETSC_EXTERN PetscErrorCode MatZeroEntries_SeqAIJ(Mat);
375: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt,const PetscInt*,const PetscInt*,const PetscInt*,const PetscInt*,PetscInt*);
376: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
377: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
379: PETSC_INTERN PetscErrorCode MatSetSeqMat_SeqAIJ(Mat,IS,IS,MatStructure,Mat);
380: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt*);
381: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat);
382: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Dummy(Mat);
383: PETSC_INTERN PetscErrorCode MatDestroySubMatrices_Dummy(PetscInt, Mat*[]);
384: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat,IS,IS,PetscInt,MatReuse,Mat*);
386: PETSC_INTERN PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat,ISLocalToGlobalMapping*);
387: PETSC_INTERN PetscErrorCode MatSetSeqAIJWithArrays_private(MPI_Comm,PetscInt,PetscInt,PetscInt[],PetscInt[],PetscScalar[],MatType,Mat);
389: /*
390: PetscSparseDenseMinusDot - The inner kernel of triangular solves and Gauss-Siedel smoothing. \sum_i xv[i] * r[xi[i]] for CSR storage
392: Input Parameters:
393: + nnz - the number of entries
394: . r - the array of vector values
395: . xv - the matrix values for the row
396: - xi - the column indices of the nonzeros in the row
398: Output Parameter:
399: . sum - negative the sum of results
401: PETSc compile flags:
402: + PETSC_KERNEL_USE_UNROLL_4
403: - PETSC_KERNEL_USE_UNROLL_2
405: Developer Notes:
406: The macro changes sum but not other parameters
408: .seealso: PetscSparseDensePlusDot()
410: */
411: #if defined(PETSC_KERNEL_USE_UNROLL_4)
412: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
413: if (nnz > 0) { \
414: PetscInt nnz2=nnz,rem=nnz&0x3; \
415: switch (rem) { \
416: case 3: sum -= *xv++ *r[*xi++]; \
417: case 2: sum -= *xv++ *r[*xi++]; \
418: case 1: sum -= *xv++ *r[*xi++]; \
419: nnz2 -= rem;} \
420: while (nnz2 > 0) { \
421: sum -= xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + \
422: xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
423: xv += 4; xi += 4; nnz2 -= 4; \
424: } \
425: xv -= nnz; xi -= nnz; \
426: } \
427: }
429: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
430: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
431: PetscInt __i,__i1,__i2; \
432: for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
433: sum -= (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
434: if (nnz & 0x1) sum -= xv[__i] * r[xi[__i]];}
436: #else
437: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
438: PetscInt __i; \
439: for (__i=0; __i<nnz; __i++) sum -= xv[__i] * r[xi[__i]];}
440: #endif
444: /*
445: PetscSparseDensePlusDot - The inner kernel of matrix-vector product \sum_i xv[i] * r[xi[i]] for CSR storage
447: Input Parameters:
448: + nnz - the number of entries
449: . r - the array of vector values
450: . xv - the matrix values for the row
451: - xi - the column indices of the nonzeros in the row
453: Output Parameter:
454: . sum - the sum of results
456: PETSc compile flags:
457: + PETSC_KERNEL_USE_UNROLL_4
458: - PETSC_KERNEL_USE_UNROLL_2
460: Developer Notes:
461: The macro changes sum but not other parameters
463: .seealso: PetscSparseDenseMinusDot()
465: */
466: #if defined(PETSC_KERNEL_USE_UNROLL_4)
467: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
468: if (nnz > 0) { \
469: PetscInt nnz2=nnz,rem=nnz&0x3; \
470: switch (rem) { \
471: case 3: sum += *xv++ *r[*xi++]; \
472: case 2: sum += *xv++ *r[*xi++]; \
473: case 1: sum += *xv++ *r[*xi++]; \
474: nnz2 -= rem;} \
475: while (nnz2 > 0) { \
476: sum += xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + \
477: xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \
478: xv += 4; xi += 4; nnz2 -= 4; \
479: } \
480: xv -= nnz; xi -= nnz; \
481: } \
482: }
484: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
485: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
486: PetscInt __i,__i1,__i2; \
487: for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
488: sum += (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
489: if (nnz & 0x1) sum += xv[__i] * r[xi[__i]];}
491: #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)
492: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) PetscSparseDensePlusDot_AVX512_Private(&(sum),(r),(xv),(xi),(nnz))
494: #else
495: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
496: PetscInt __i; \
497: for (__i=0; __i<nnz; __i++) sum += xv[__i] * r[xi[__i]];}
498: #endif
500: #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)
501: #include <immintrin.h>
502: #if !defined(_MM_SCALE_8)
503: #define _MM_SCALE_8 8
504: #endif
506: PETSC_STATIC_INLINE void PetscSparseDensePlusDot_AVX512_Private(PetscScalar *sum,const PetscScalar *x,const MatScalar *aa,const PetscInt *aj,PetscInt n)
507: {
508: __m512d vec_x,vec_y,vec_vals;
509: __m256i vec_idx;
510: __mmask8 mask;
511: PetscInt j;
513: vec_y = _mm512_setzero_pd();
514: for (j=0; j<(n>>3); j++) {
515: vec_idx = _mm256_loadu_si256((__m256i const*)aj);
516: vec_vals = _mm512_loadu_pd(aa);
517: vec_x = _mm512_i32gather_pd(vec_idx,x,_MM_SCALE_8);
518: vec_y = _mm512_fmadd_pd(vec_x,vec_vals,vec_y);
519: aj += 8; aa += 8;
520: }
521: /* masked load does not work on KNL, it requires avx512vl */
522: if ((n&0x07)>2) {
523: mask = (__mmask8)(0xff >> (8-(n&0x07)));
524: vec_idx = _mm256_loadu_si256((__m256i const*)aj);
525: vec_vals = _mm512_loadu_pd(aa);
526: vec_x = _mm512_mask_i32gather_pd(vec_x,mask,vec_idx,x,_MM_SCALE_8);
527: vec_y = _mm512_mask3_fmadd_pd(vec_x,vec_vals,vec_y,mask);
528: } else if ((n&0x07)==2) {
529: *sum += aa[0]*x[aj[0]];
530: *sum += aa[1]*x[aj[1]];
531: } else if ((n&0x07)==1) {
532: *sum += aa[0]*x[aj[0]];
533: }
534: if (n>2) *sum += _mm512_reduce_add_pd(vec_y);
535: /*
536: for (j=0;j<(n&0x07);j++) *sum += aa[j]*x[aj[j]];
537: */
538: }
539: #endif
541: /*
542: PetscSparseDenseMaxDot - The inner kernel of a modified matrix-vector product \max_i xv[i] * r[xi[i]] for CSR storage
544: Input Parameters:
545: + nnz - the number of entries
546: . r - the array of vector values
547: . xv - the matrix values for the row
548: - xi - the column indices of the nonzeros in the row
550: Output Parameter:
551: . max - the max of results
553: .seealso: PetscSparseDensePlusDot(), PetscSparseDenseMinusDot()
555: */
556: #define PetscSparseDenseMaxDot(max,r,xv,xi,nnz) { \
557: PetscInt __i; \
558: for (__i=0; __i<nnz; __i++) max = PetscMax(PetscRealPart(max), PetscRealPart(xv[__i] * r[xi[__i]]));}
560: /*
561: Add column indices into table for counting the max nonzeros of merged rows
562: */
563: #define MatRowMergeMax_SeqAIJ(mat,nrows,ta) { \
564: PetscInt _j,_row,_nz,*_col; \
565: if (mat) { \
566: for (_row=0; _row<nrows; _row++) { \
567: _nz = mat->i[_row+1] - mat->i[_row]; \
568: for (_j=0; _j<_nz; _j++) { \
569: _col = _j + mat->j + mat->i[_row]; \
570: PetscTableAdd(ta,*_col+1,1,INSERT_VALUES); \
571: } \
572: } \
573: } \
574: }
576: /*
577: Add column indices into table for counting the nonzeros of merged rows
578: */
579: #define MatMergeRows_SeqAIJ(mat,nrows,rows,ta) { \
580: PetscInt _j,_row,_nz,*_col,_i; \
581: for (_i=0; _i<nrows; _i++) {\
582: _row = rows[_i]; \
583: _nz = mat->i[_row+1] - mat->i[_row]; \
584: for (_j=0; _j<_nz; _j++) { \
585: _col = _j + mat->j + mat->i[_row]; \
586: PetscTableAdd(ta,*_col+1,1,INSERT_VALUES); \
587: } \
588: } \
589: }
591: #endif