Date: 2022-03-31T04:46:45+00:00

Actual source code: aij.h

      5: #include <petsc/private/matimpl.h>
      6: #include <petscctable.h>

      8: /* Operations provided by MATSEQAIJ and its subclasses */
      9: typedef struct {
     10:   PetscErrorCode (*getarray)(Mat,PetscScalar **);
     11:   PetscErrorCode (*restorearray)(Mat,PetscScalar **);
     12:   PetscErrorCode (*getarrayread)(Mat,const PetscScalar **);
     13:   PetscErrorCode (*restorearrayread)(Mat,const PetscScalar **);
     14:   PetscErrorCode (*getarraywrite)(Mat,PetscScalar **);
     15:   PetscErrorCode (*restorearraywrite)(Mat,PetscScalar **);
     16:   PetscErrorCode (*getcsrandmemtype)(Mat,const PetscInt**,const PetscInt**,PetscScalar**,PetscMemType*);
     17: } Mat_SeqAIJOps;

     19: /*
     20:     Struct header shared by SeqAIJ, SeqBAIJ and SeqSBAIJ matrix formats
     21: */
     22: #define SEQAIJHEADER(datatype)        \
     23:   PetscBool roworiented;              /* if true, row-oriented input, default */ \
     24:   PetscInt  nonew;                    /* 1 don't add new nonzeros, -1 generate error on new */ \
     25:   PetscInt  nounused;                 /* -1 generate error on unused space */ \
     26:   PetscBool singlemalloc;             /* if true a, i, and j have been obtained with one big malloc */ \
     27:   PetscInt  maxnz;                    /* allocated nonzeros */ \
     28:   PetscInt  *imax;                    /* maximum space allocated for each row */ \
     29:   PetscInt  *ilen;                    /* actual length of each row */ \
     30:   PetscInt  *ipre;                    /* space preallocated for each row by user */ \
     31:   PetscBool free_imax_ilen;  \
     32:   PetscInt  reallocs;                 /* number of mallocs done during MatSetValues() \
     33:                                         as more values are set than were prealloced */\
     34:   PetscInt          rmax;             /* max nonzeros in any row */ \
     35:   PetscBool         keepnonzeropattern;   /* keeps matrix structure same in calls to MatZeroRows()*/ \
     36:   PetscBool         ignorezeroentries; \
     37:   PetscBool         free_ij;          /* free the column indices j and row offsets i when the matrix is destroyed */ \
     38:   PetscBool         free_a;           /* free the numerical values when matrix is destroy */ \
     39:   Mat_CompressedRow compressedrow;    /* use compressed row format */                      \
     40:   PetscInt          nz;               /* nonzeros */                                       \
     41:   PetscInt          *i;               /* pointer to beginning of each row */               \
     42:   PetscInt          *j;               /* column values: j + i[k] - 1 is start of row k */  \
     43:   PetscInt          *diag;            /* pointers to diagonal elements */                  \
     44:   PetscInt          nonzerorowcnt;    /* how many rows have nonzero entries */             \
     45:   PetscBool         free_diag;         \
     46:   datatype          *a;               /* nonzero elements */                               \
     47:   PetscScalar       *solve_work;      /* work space used in MatSolve */                    \
     48:   IS                row, col, icol;   /* index sets, used for reorderings */ \
     49:   PetscBool         pivotinblocks;    /* pivot inside factorization of each diagonal block */ \
     50:   Mat               parent;           /* set if this matrix was formed with MatDuplicate(...,MAT_SHARE_NONZERO_PATTERN,....); \
     51:                                          means that this shares some data structures with the parent including diag, ilen, imax, i, j */\
     52:   Mat_SubSppt       *submatis1;       /* used by MatCreateSubMatrices_MPIXAIJ_Local */    \
     53:   Mat_SeqAIJOps     ops[1]            /* operations for SeqAIJ and its subclasses */

     55: typedef struct {
     56:   MatTransposeColoring matcoloring;
     57:   Mat                  Bt_den;       /* dense matrix of B^T */
     58:   Mat                  ABt_den;      /* dense matrix of A*B^T */
     59:   PetscBool            usecoloring;
     60: } Mat_MatMatTransMult;

     62: typedef struct { /* used by MatTransposeMatMult() */
     63:   Mat          At;           /* transpose of the first matrix */
     64:   Mat          mA;           /* maij matrix of A */
     65:   Vec          bt,ct;        /* vectors to hold locally transposed arrays of B and C */
     66:   PetscBool    updateAt;     /* flg to avoid recomputing At in MatProductNumeric_AtB_SeqAIJ_SeqAIJ() */
     67:   /* used by PtAP */
     68:   void           *data;
     69:   PetscErrorCode (*destroy)(void*);
     70: } Mat_MatTransMatMult;

     72: typedef struct {
     73:   PetscInt    *api,*apj;       /* symbolic structure of A*P */
     74:   PetscScalar *apa;            /* temporary array for storing one row of A*P */
     75: } Mat_AP;

     77: typedef struct {
     78:   MatTransposeColoring matcoloring;
     79:   Mat                  Rt;    /* sparse or dense matrix of R^T */
     80:   Mat                  RARt;  /* dense matrix of R*A*R^T */
     81:   Mat                  ARt;   /* A*R^T used for the case -matrart_color_art */
     82:   MatScalar            *work; /* work array to store columns of A*R^T used in MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqDense() */
     83:   /* free intermediate products needed for PtAP */
     84:   void                 *data;
     85:   PetscErrorCode       (*destroy)(void*);
     86: } Mat_RARt;

     88: typedef struct {
     89:   Mat BC;               /* temp matrix for storing B*C */
     90: } Mat_MatMatMatMult;

     92: /*
     93:   MATSEQAIJ format - Compressed row storage (also called Yale sparse matrix
     94:   format) or compressed sparse row (CSR).  The i[] and j[] arrays start at 0. For example,
     95:   j[i[k]+p] is the pth column in row k.  Note that the diagonal
     96:   matrix elements are stored with the rest of the nonzeros (not separately).
     97: */

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

    105:   PetscBool        use;
    106:   PetscInt         node_count;                     /* number of inodes */
    107:   PetscInt         *size;                          /* size of each inode */
    108:   PetscInt         limit;                          /* inode limit */
    109:   PetscInt         max_limit;                      /* maximum supported inode limit */
    110:   PetscBool        checked;                        /* if inodes have been checked for */
    111:   PetscObjectState mat_nonzerostate;               /* non-zero state when inodes were checked for */
    112: } Mat_SeqAIJ_Inode;

    114: PETSC_INTERN PetscErrorCode MatView_SeqAIJ_Inode(Mat,PetscViewer);
    115: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ_Inode(Mat,MatAssemblyType);
    116: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_Inode(Mat);
    117: PETSC_INTERN PetscErrorCode MatCreate_SeqAIJ_Inode(Mat);
    118: PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ_Inode(Mat,MatOption,PetscBool);
    119: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ_Inode(Mat,MatDuplicateOption,Mat*);
    120: PETSC_INTERN PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat,Mat,MatDuplicateOption,PetscBool);
    121: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode_inplace(Mat,Mat,const MatFactorInfo*);
    122: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode(Mat,Mat,const MatFactorInfo*);
    123: PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat,PetscScalar**);
    124: PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat,PetscScalar**);

    126: typedef struct {
    127:   SEQAIJHEADER(MatScalar);
    128:   Mat_SeqAIJ_Inode inode;
    129:   MatScalar        *saved_values;             /* location for stashing nonzero values of matrix */

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

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

    145: /*
    146:   Frees the a, i, and j arrays from the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
    147: */
    148: static inline PetscErrorCode MatSeqXAIJFreeAIJ(Mat AA,MatScalar **a,PetscInt **j,PetscInt **i)
    149: {
    150:   Mat_SeqAIJ     *A = (Mat_SeqAIJ*) AA->data;
    151:   if (A->singlemalloc) {
    152:     PetscFree3(*a,*j,*i);
    153:   } else {
    154:     if (A->free_a)  PetscFree(*a);
    155:     if (A->free_ij) PetscFree(*j);
    156:     if (A->free_ij) PetscFree(*i);
    157:   }
    158:   return 0;
    159: }
    160: /*
    161:     Allocates larger a, i, and j arrays for the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types
    162:     This is a macro because it takes the datatype as an argument which can be either a Mat or a MatScalar
    163: */
    164: #define MatSeqXAIJReallocateAIJ(Amat,AM,BS2,NROW,ROW,COL,RMAX,AA,AI,AJ,RP,AP,AIMAX,NONEW,datatype) \
    165:   if (NROW >= RMAX) { \
    166:     Mat_SeqAIJ *Ain = (Mat_SeqAIJ*)Amat->data; \
    167:     /* there is no extra room in row, therefore enlarge */ \
    168:     PetscInt CHUNKSIZE = 15,new_nz = AI[AM] + CHUNKSIZE,len,*new_i=NULL,*new_j=NULL; \
    169:     datatype *new_a; \
    170:  \
    172:     /* malloc new storage space */ \
    173:     PetscMalloc3(BS2*new_nz,&new_a,new_nz,&new_j,AM+1,&new_i); \
    174:  \
    175:     /* copy over old data into new slots */ \
    176:     for (ii=0; ii<ROW+1; ii++) {new_i[ii] = AI[ii];} \
    177:     for (ii=ROW+1; ii<AM+1; ii++) {new_i[ii] = AI[ii]+CHUNKSIZE;} \
    178:     PetscArraycpy(new_j,AJ,AI[ROW]+NROW); \
    179:     len  = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
    180:     PetscArraycpy(new_j+AI[ROW]+NROW+CHUNKSIZE,AJ+AI[ROW]+NROW,len); \
    181:     PetscArraycpy(new_a,AA,BS2*(AI[ROW]+NROW));    \
    182:     PetscArrayzero(new_a+BS2*(AI[ROW]+NROW),BS2*CHUNKSIZE); \
    183:     PetscArraycpy(new_a+BS2*(AI[ROW]+NROW+CHUNKSIZE),AA+BS2*(AI[ROW]+NROW),BS2*len);  \
    184:     /* free up old matrix storage */ \
    185:     MatSeqXAIJFreeAIJ(A,&Ain->a,&Ain->j,&Ain->i); \
    186:     AA                = new_a; \
    187:     Ain->a            = (MatScalar*) new_a;                   \
    188:     AI                = Ain->i = new_i; AJ = Ain->j = new_j;  \
    189:     Ain->singlemalloc = PETSC_TRUE; \
    190:  \
    191:     RP          = AJ + AI[ROW]; AP = AA + BS2*AI[ROW]; \
    192:     RMAX        = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
    193:     Ain->maxnz += BS2*CHUNKSIZE; \
    194:     Ain->reallocs++; \
    195:   } \

    197: #define MatSeqXAIJReallocateAIJ_structure_only(Amat,AM,BS2,NROW,ROW,COL,RMAX,AI,AJ,RP,AIMAX,NONEW,datatype) \
    198:   if (NROW >= RMAX) { \
    199:     Mat_SeqAIJ *Ain = (Mat_SeqAIJ*)Amat->data; \
    200:     /* there is no extra room in row, therefore enlarge */ \
    201:     PetscInt CHUNKSIZE = 15,new_nz = AI[AM] + CHUNKSIZE,len,*new_i=NULL,*new_j=NULL; \
    202:  \
    204:     /* malloc new storage space */ \
    205:     PetscMalloc1(new_nz,&new_j); \
    206:     PetscMalloc1(AM+1,&new_i);\
    207:  \
    208:     /* copy over old data into new slots */ \
    209:     for (ii=0; ii<ROW+1; ii++) {new_i[ii] = AI[ii];} \
    210:     for (ii=ROW+1; ii<AM+1; ii++) {new_i[ii] = AI[ii]+CHUNKSIZE;} \
    211:     PetscArraycpy(new_j,AJ,AI[ROW]+NROW); \
    212:     len  = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \
    213:     PetscArraycpy(new_j+AI[ROW]+NROW+CHUNKSIZE,AJ+AI[ROW]+NROW,len); \
    214:  \
    215:     /* free up old matrix storage */ \
    216:     MatSeqXAIJFreeAIJ(A,&Ain->a,&Ain->j,&Ain->i); \
    217:     Ain->a            = NULL;                   \
    218:     AI                = Ain->i = new_i; AJ = Ain->j = new_j;  \
    219:     Ain->singlemalloc = PETSC_FALSE; \
    220:     Ain->free_a       = PETSC_FALSE;             \
    221:  \
    222:     RP          = AJ + AI[ROW];    \
    223:     RMAX        = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \
    224:     Ain->maxnz += BS2*CHUNKSIZE; \
    225:     Ain->reallocs++; \
    226:   } \

    228: PETSC_INTERN PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat,PetscInt,const PetscInt*);
    229: PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_SeqAIJ(Mat,PetscCount,const PetscInt[],const PetscInt[]);
    230: PETSC_INTERN PetscErrorCode MatResetPreallocationCOO_SeqAIJ(Mat);

    232: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,IS,const MatFactorInfo*);
    233: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ(Mat,Mat,IS,IS,const MatFactorInfo*);
    234: PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_ilu0(Mat,Mat,IS,IS,const MatFactorInfo*);

    236: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,const MatFactorInfo*);
    237: PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ(Mat,Mat,IS,const MatFactorInfo*);
    238: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,const MatFactorInfo*);
    239: PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ(Mat,Mat,IS,const MatFactorInfo*);
    240: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_inplace(Mat,Mat,const MatFactorInfo*);
    241: PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ(Mat,Mat,const MatFactorInfo*);
    242: PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ(Mat,MatDuplicateOption,Mat*);
    243: PETSC_INTERN PetscErrorCode MatCopy_SeqAIJ(Mat,Mat,MatStructure);
    244: PETSC_INTERN PetscErrorCode MatMissingDiagonal_SeqAIJ(Mat,PetscBool*,PetscInt*);
    245: PETSC_INTERN PetscErrorCode MatMarkDiagonal_SeqAIJ(Mat);
    246: PETSC_INTERN PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat,PetscInt*,PetscInt**);

    248: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ(Mat,Vec,Vec);
    249: PETSC_INTERN PetscErrorCode MatMult_SeqAIJ_Inode(Mat,Vec,Vec);
    250: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ(Mat,Vec,Vec,Vec);
    251: PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ_Inode(Mat,Vec,Vec,Vec);
    252: PETSC_INTERN PetscErrorCode MatMultTranspose_SeqAIJ(Mat,Vec,Vec);
    253: PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat,Vec,Vec,Vec);
    254: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
    255: PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ_Inode(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);

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

    259: PETSC_INTERN PetscErrorCode MatGetSymbolicTranspose_SeqAIJ(Mat,PetscInt *[],PetscInt *[]);
    260: PETSC_INTERN PetscErrorCode MatGetSymbolicTransposeReduced_SeqAIJ(Mat,PetscInt,PetscInt,PetscInt *[],PetscInt *[]);
    261: PETSC_INTERN PetscErrorCode MatRestoreSymbolicTranspose_SeqAIJ(Mat,PetscInt *[],PetscInt *[]);
    262: PETSC_INTERN PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat,Mat*);
    263: PETSC_INTERN PetscErrorCode MatTranspose_SeqAIJ(Mat,MatReuse,Mat*);
    264: PETSC_INTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt,PetscInt*,PetscInt*,PetscBool,PetscInt,PetscInt,PetscInt**,PetscInt**);
    265: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ_inplace(Mat,Mat,IS,IS,const MatFactorInfo*);
    266: PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ(Mat,Mat,IS,IS,const MatFactorInfo*);
    267: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_inplace(Mat,Mat,const MatFactorInfo*);
    268: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ(Mat,Mat,const MatFactorInfo*);
    269: PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(Mat,Mat,const MatFactorInfo*);
    270: PETSC_INTERN PetscErrorCode MatLUFactor_SeqAIJ(Mat,IS,IS,const MatFactorInfo*);
    271: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_inplace(Mat,Vec,Vec);
    272: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ(Mat,Vec,Vec);
    273: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode_inplace(Mat,Vec,Vec);
    274: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode(Mat,Vec,Vec);
    275: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering_inplace(Mat,Vec,Vec);
    276: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering(Mat,Vec,Vec);
    277: PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_InplaceWithPerm(Mat,Vec,Vec);
    278: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ_inplace(Mat,Vec,Vec,Vec);
    279: PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ(Mat,Vec,Vec,Vec);
    280: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ_inplace(Mat,Vec,Vec);
    281: PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ(Mat,Vec,Vec);
    282: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ_inplace(Mat,Vec,Vec,Vec);
    283: PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ(Mat,Vec,Vec,Vec);
    284: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ_inplace(Mat,Mat,Mat);
    285: PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ(Mat,Mat,Mat);
    286: PETSC_INTERN PetscErrorCode MatEqual_SeqAIJ(Mat,Mat,PetscBool*);
    287: PETSC_INTERN PetscErrorCode MatFDColoringCreate_SeqXAIJ(Mat,ISColoring,MatFDColoring);
    288: PETSC_INTERN PetscErrorCode MatFDColoringSetUp_SeqXAIJ(Mat,ISColoring,MatFDColoring);
    289: PETSC_INTERN PetscErrorCode MatFDColoringSetUpBlocked_AIJ_Private(Mat,MatFDColoring,PetscInt);
    290: PETSC_INTERN PetscErrorCode MatLoad_AIJ_HDF5(Mat,PetscViewer);
    291: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ_Binary(Mat,PetscViewer);
    292: PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ(Mat,PetscViewer);
    293: PETSC_INTERN PetscErrorCode RegisterApplyPtAPRoutines_Private(Mat);

    295: #if defined(PETSC_HAVE_HYPRE)
    296: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_Transpose_AIJ_AIJ(Mat);
    297: #endif
    298: PETSC_INTERN PetscErrorCode MatProductSetFromOptions_SeqAIJ(Mat);

    300: PETSC_INTERN PetscErrorCode MatProductSymbolic_SeqAIJ_SeqAIJ(Mat);
    301: PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat);
    302: PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_SeqAIJ_SeqAIJ(Mat);

    304: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
    305: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Sorted(Mat,Mat,PetscReal,Mat);
    306: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat,Mat,PetscReal,Mat);
    307: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable(Mat,Mat,PetscReal,Mat);
    308: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable_fast(Mat,Mat,PetscReal,Mat);
    309: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Heap(Mat,Mat,PetscReal,Mat);
    310: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_BTHeap(Mat,Mat,PetscReal,Mat);
    311: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_RowMerge(Mat,Mat,PetscReal,Mat);
    312: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_LLCondensed(Mat,Mat,PetscReal,Mat);
    313: #if defined(PETSC_HAVE_HYPRE)
    314: PETSC_INTERN PetscErrorCode MatMatMultSymbolic_AIJ_AIJ_wHYPRE(Mat,Mat,PetscReal,Mat);
    315: #endif

    317: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
    318: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Sorted(Mat,Mat,Mat);

    320: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat,Mat,Mat);
    321: PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Scalable(Mat,Mat,Mat);

    323: PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat,Mat,PetscReal,Mat);
    324: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
    325: PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat,Mat,Mat);

    327: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
    328: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_matmattransposemult(Mat,Mat,PetscReal,Mat);
    329: PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_colorrart(Mat,Mat,PetscReal,Mat);
    330: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
    331: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_matmattransposemult(Mat,Mat,Mat);
    332: PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_colorrart(Mat,Mat,Mat);

    334: PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
    335: PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
    336: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_MatTransMatMult(void*);

    338: PETSC_INTERN PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat,Mat,PetscReal,Mat);
    339: PETSC_INTERN PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat,Mat,Mat);
    340: PETSC_INTERN PetscErrorCode MatTransposeColoringCreate_SeqAIJ(Mat,ISColoring,MatTransposeColoring);
    341: PETSC_INTERN PetscErrorCode MatTransColoringApplySpToDen_SeqAIJ(MatTransposeColoring,Mat,Mat);
    342: PETSC_INTERN PetscErrorCode MatTransColoringApplyDenToSp_SeqAIJ(MatTransposeColoring,Mat,Mat);

    344: PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,PetscReal,Mat);
    345: PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ(Mat,Mat,Mat,Mat);

    347: PETSC_INTERN PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat,PetscInt,PetscInt,PetscRandom);
    348: PETSC_INTERN PetscErrorCode MatSetValues_SeqAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
    349: PETSC_INTERN PetscErrorCode MatGetRow_SeqAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
    350: PETSC_INTERN PetscErrorCode MatRestoreRow_SeqAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
    351: PETSC_INTERN PetscErrorCode MatScale_SeqAIJ(Mat,PetscScalar);
    352: PETSC_INTERN PetscErrorCode MatDiagonalScale_SeqAIJ(Mat,Vec,Vec);
    353: PETSC_INTERN PetscErrorCode MatDiagonalSet_SeqAIJ(Mat,Vec,InsertMode);
    354: PETSC_INTERN PetscErrorCode MatAXPY_SeqAIJ(Mat,PetscScalar,Mat,MatStructure);
    355: PETSC_INTERN PetscErrorCode MatGetRowIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
    356: PETSC_INTERN PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
    357: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
    358: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscBool*);
    359: PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscInt *[],PetscBool*);
    360: PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat,PetscInt,PetscBool,PetscBool,PetscInt*,const PetscInt *[],const PetscInt *[],PetscInt *[],PetscBool*);
    361: PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ(Mat);
    362: PETSC_INTERN PetscErrorCode MatSetUp_SeqAIJ(Mat);
    363: PETSC_INTERN PetscErrorCode MatView_SeqAIJ(Mat,PetscViewer);

    365: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal(Mat);
    366: PETSC_INTERN PetscErrorCode MatSeqAIJInvalidateDiagonal_Inode(Mat);
    367: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode(Mat);
    368: PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode_FactorLU(Mat);

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

    372: #if defined(PETSC_HAVE_MATLAB_ENGINE)
    373: PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject,void*);
    374: PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject,void*);
    375: #endif
    376: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqSBAIJ(Mat,MatType,MatReuse,Mat*);
    377: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqBAIJ(Mat,MatType,MatReuse,Mat*);
    378: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat,MatType,MatReuse,Mat*);
    379: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat,MatType,MatReuse,Mat*);
    380: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat,MatType,MatReuse,Mat*);
    381: #if defined(PETSC_HAVE_SCALAPACK)
    382: PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat,MatType,MatReuse,Mat*);
    383: #endif
    384: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
    385: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat,MatType,MatReuse,Mat*);
    386: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJSELL(Mat,MatType,MatReuse,Mat*);
    387: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat,MatType,MatReuse,Mat*);
    388: PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat,MatType,MatReuse,Mat*);
    389: PETSC_INTERN PetscErrorCode MatReorderForNonzeroDiagonal_SeqAIJ(Mat,PetscReal,IS,IS);
    390: PETSC_INTERN PetscErrorCode MatRARt_SeqAIJ_SeqAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);
    391: PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat);
    392: PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat,MatAssemblyType);
    393: PETSC_EXTERN PetscErrorCode MatZeroEntries_SeqAIJ(Mat);

    395: PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt,const PetscInt*,const PetscInt*,const PetscInt*,const PetscInt*,PetscInt*);
    396: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);
    397: PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm,Mat,PetscInt,MatReuse,Mat*);

    399: PETSC_INTERN PetscErrorCode MatSetSeqMat_SeqAIJ(Mat,IS,IS,MatStructure,Mat);
    400: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt*);
    401: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat);
    402: PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Dummy(Mat);
    403: PETSC_INTERN PetscErrorCode MatDestroySubMatrices_Dummy(PetscInt, Mat*[]);
    404: PETSC_INTERN PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat,IS,IS,PetscInt,MatReuse,Mat*);

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

    409: /*
    410:     PetscSparseDenseMinusDot - The inner kernel of triangular solves and Gauss-Siedel smoothing. \sum_i xv[i] * r[xi[i]] for CSR storage

    412:   Input Parameters:
    413: +  nnz - the number of entries
    414: .  r - the array of vector values
    415: .  xv - the matrix values for the row
    416: -  xi - the column indices of the nonzeros in the row

    418:   Output Parameter:
    419: .  sum - negative the sum of results

    421:   PETSc compile flags:
    422: +   PETSC_KERNEL_USE_UNROLL_4
    423: -   PETSC_KERNEL_USE_UNROLL_2

    425:   Developer Notes:
    426:     The macro changes sum but not other parameters

    428: .seealso: PetscSparseDensePlusDot()

    430: */
    431: #if defined(PETSC_KERNEL_USE_UNROLL_4)
    432: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
    433:     if (nnz > 0) { \
    434:       PetscInt nnz2=nnz,rem=nnz&0x3; \
    435:       switch (rem) { \
    436:       case 3: sum -= *xv++ *r[*xi++]; \
    437:       case 2: sum -= *xv++ *r[*xi++]; \
    438:       case 1: sum -= *xv++ *r[*xi++]; \
    439:         nnz2      -= rem;} \
    440:       while (nnz2 > 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; nnz2 -= 4; \
    444:       } \
    445:       xv -= nnz; xi -= nnz; \
    446:     } \
    447:   }

    449: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
    450: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
    451:     PetscInt __i,__i1,__i2; \
    452:     for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
    453:                                     sum -= (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
    454:     if (nnz & 0x1) sum -= xv[__i] * r[xi[__i]];}

    456: #else
    457: #define PetscSparseDenseMinusDot(sum,r,xv,xi,nnz) { \
    458:     PetscInt __i; \
    459:     for (__i=0; __i<nnz; __i++) sum -= xv[__i] * r[xi[__i]];}
    460: #endif

    462: /*
    463:     PetscSparseDensePlusDot - The inner kernel of matrix-vector product \sum_i xv[i] * r[xi[i]] for CSR storage

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

    471:   Output Parameter:
    472: .  sum - the sum of results

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

    478:   Developer Notes:
    479:     The macro changes sum but not other parameters

    481: .seealso: PetscSparseDenseMinusDot()

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

    502: #elif defined(PETSC_KERNEL_USE_UNROLL_2)
    503: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
    504:     PetscInt __i,__i1,__i2; \
    505:     for (__i=0; __i<nnz-1; __i+=2) {__i1 = xi[__i]; __i2=xi[__i+1]; \
    506:                                     sum += (xv[__i]*r[__i1] + xv[__i+1]*r[__i2]);} \
    507:     if (nnz & 0x1) sum += xv[__i] * r[xi[__i]];}

    509: #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)
    510: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) PetscSparseDensePlusDot_AVX512_Private(&(sum),(r),(xv),(xi),(nnz))

    512: #else
    513: #define PetscSparseDensePlusDot(sum,r,xv,xi,nnz) { \
    514:     PetscInt __i; \
    515:     for (__i=0; __i<nnz; __i++) sum += xv[__i] * r[xi[__i]];}
    516: #endif

    518: #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)
    519:   #include <immintrin.h>
    520:   #if !defined(_MM_SCALE_8)
    521:   #define _MM_SCALE_8    8
    522:   #endif

    524: static inline void PetscSparseDensePlusDot_AVX512_Private(PetscScalar *sum,const PetscScalar *x,const MatScalar *aa,const PetscInt *aj,PetscInt n)
    525: {
    526:   __m512d  vec_x,vec_y,vec_vals;
    527:   __m256i  vec_idx;
    528:   __mmask8 mask;
    529:   PetscInt j;

    531:   vec_y = _mm512_setzero_pd();
    532:   for (j=0; j<(n>>3); j++) {
    533:     vec_idx  = _mm256_loadu_si256((__m256i const*)aj);
    534:     vec_vals = _mm512_loadu_pd(aa);
    535:     vec_x    = _mm512_i32gather_pd(vec_idx,x,_MM_SCALE_8);
    536:     vec_y    = _mm512_fmadd_pd(vec_x,vec_vals,vec_y);
    537:     aj += 8; aa += 8;
    538:   }
    539:   /* masked load does not work on KNL, it requires avx512vl */
    540:   if ((n&0x07)>2) {
    541:     mask     = (__mmask8)(0xff >> (8-(n&0x07)));
    542:     vec_idx  = _mm256_loadu_si256((__m256i const*)aj);
    543:     vec_vals = _mm512_loadu_pd(aa);
    544:     vec_x    = _mm512_mask_i32gather_pd(vec_x,mask,vec_idx,x,_MM_SCALE_8);
    545:     vec_y    = _mm512_mask3_fmadd_pd(vec_x,vec_vals,vec_y,mask);
    546:   } else if ((n&0x07)==2) {
    547:     *sum += aa[0]*x[aj[0]];
    548:     *sum += aa[1]*x[aj[1]];
    549:   } else if ((n&0x07)==1) {
    550:     *sum += aa[0]*x[aj[0]];
    551:   }
    552:   if (n>2) *sum += _mm512_reduce_add_pd(vec_y);
    553: /*
    554:   for (j=0;j<(n&0x07);j++) *sum += aa[j]*x[aj[j]];
    555: */
    556: }
    557: #endif

    559: /*
    560:     PetscSparseDenseMaxDot - The inner kernel of a modified matrix-vector product \max_i xv[i] * r[xi[i]] for CSR storage

    562:   Input Parameters:
    563: +  nnz - the number of entries
    564: .  r - the array of vector values
    565: .  xv - the matrix values for the row
    566: -  xi - the column indices of the nonzeros in the row

    568:   Output Parameter:
    569: .  max - the max of results

    571: .seealso: PetscSparseDensePlusDot(), PetscSparseDenseMinusDot()

    573: */
    574: #define PetscSparseDenseMaxDot(max,r,xv,xi,nnz) { \
    575:     PetscInt __i; \
    576:     for (__i=0; __i<nnz; __i++) max = PetscMax(PetscRealPart(max), PetscRealPart(xv[__i] * r[xi[__i]]));}

    578: /*
    579:  Add column indices into table for counting the max nonzeros of merged rows
    580:  */
    581: #define MatRowMergeMax_SeqAIJ(mat,nrows,ta) {       \
    582:     PetscInt _j,_row,_nz,*_col;                     \
    583:     if (mat) { \
    584:       for (_row=0; _row<nrows; _row++) {   \
    585:         _nz = mat->i[_row+1] - mat->i[_row];    \
    586:         for (_j=0; _j<_nz; _j++) {               \
    587:           _col = _j + mat->j + mat->i[_row];       \
    588:           PetscTableAdd(ta,*_col+1,1,INSERT_VALUES);                    \
    589:         }                                                               \
    590:       }                                                                 \
    591:     }    \
    592: }

    594: /*
    595:  Add column indices into table for counting the nonzeros of merged rows
    596:  */
    597: #define MatMergeRows_SeqAIJ(mat,nrows,rows,ta) {    \
    598:   PetscInt _j,_row,_nz,*_col,_i;                      \
    599:     for (_i=0; _i<nrows; _i++) {\
    600:       _row = rows[_i]; \
    601:       _nz = mat->i[_row+1] - mat->i[_row]; \
    602:       for (_j=0; _j<_nz; _j++) {                \
    603:         _col = _j + mat->j + mat->i[_row];       \
    604:         PetscTableAdd(ta,*_col+1,1,INSERT_VALUES); \
    605:       }                                                                 \
    606:     }                                                                   \
    607: }

    609: #endif