#pragma once #include #include #include /* Used by MatCreateSubMatrices_MPIXAIJ_Local() */ typedef struct { /* used by MatCreateSubMatrices_MPIAIJ_SingleIS_Local() and MatCreateSubMatrices_MPIAIJ_Local */ PetscInt id; /* index of submats, only submats[0] is responsible for deleting some arrays below */ PetscMPIInt nrqs, nrqr; PetscInt **rbuf1, **rbuf2, **rbuf3, **sbuf1, **sbuf2; PetscInt **ptr; PetscInt *tmp; PetscInt *ctr; PetscMPIInt *pa; /* process array */ PetscInt *req_size; PetscMPIInt *req_source1, *req_source2; PetscBool allcolumns, allrows; PetscBool singleis; PetscMPIInt *row2proc; /* row to process (MPI rank) map */ PetscInt nstages; #if defined(PETSC_USE_CTABLE) PetscHMapI cmap, rmap; PetscInt *cmap_loc, *rmap_loc; #else PetscInt *cmap, *rmap; #endif PetscErrorCode (*destroy)(Mat); } Mat_SubSppt; /* Operations provided by MATSEQAIJ and its subclasses */ typedef struct { PetscErrorCode (*getarray)(Mat, PetscScalar **); PetscErrorCode (*restorearray)(Mat, PetscScalar **); PetscErrorCode (*getarrayread)(Mat, const PetscScalar **); PetscErrorCode (*restorearrayread)(Mat, const PetscScalar **); PetscErrorCode (*getarraywrite)(Mat, PetscScalar **); PetscErrorCode (*restorearraywrite)(Mat, PetscScalar **); PetscErrorCode (*getcsrandmemtype)(Mat, const PetscInt **, const PetscInt **, PetscScalar **, PetscMemType *); } Mat_SeqAIJOps; /* Struct header shared by SeqAIJ, SeqBAIJ and SeqSBAIJ matrix formats */ #define SEQAIJHEADER(datatype) \ PetscBool roworiented; /* if true, row-oriented input, default */ \ PetscInt nonew; /* 1 don't add new nonzeros, -1 generate error on new */ \ PetscInt nounused; /* -1 generate error on unused space */ \ PetscInt maxnz; /* allocated nonzeros */ \ PetscInt *imax; /* maximum space allocated for each row */ \ PetscInt *ilen; /* actual length of each row */ \ PetscInt *ipre; /* space preallocated for each row by user */ \ PetscBool free_imax_ilen; \ PetscInt reallocs; /* number of mallocs done during MatSetValues() \ as more values are set than were prealloced */ \ PetscInt rmax; /* max nonzeros in any row */ \ PetscBool keepnonzeropattern; /* keeps matrix nonzero structure same in calls to MatZeroRows()*/ \ PetscBool ignorezeroentries; \ PetscBool free_ij; /* free the column indices j and row offsets i when the matrix is destroyed */ \ PetscBool free_a; /* free the numerical values when matrix is destroy */ \ Mat_CompressedRow compressedrow; /* use compressed row format */ \ PetscInt nz; /* nonzeros */ \ PetscInt *i; /* pointer to beginning of each row */ \ PetscInt *j; /* column values: j + i[k] - 1 is start of row k */ \ PetscInt *diag; /* pointers to diagonal elements */ \ PetscObjectState diagNonzeroState; /* nonzero state of the matrix when diag was obtained */ \ PetscBool diagDense; /* all entries along the diagonal have been set; i.e. no missing diagonal terms */ \ PetscInt nonzerorowcnt; /* how many rows have nonzero entries */ \ datatype *a; /* nonzero elements */ \ PetscScalar *solve_work; /* work space used in MatSolve */ \ IS row, col, icol; /* index sets, used for reorderings */ \ PetscBool pivotinblocks; /* pivot inside factorization of each diagonal block */ \ Mat parent; /* set if this matrix was formed with MatDuplicate(...,MAT_SHARE_NONZERO_PATTERN,....); \ means that this shares some data structures with the parent including diag, ilen, imax, i, j */ \ Mat_SubSppt *submatis1; /* used by MatCreateSubMatrices_MPIXAIJ_Local */ \ Mat_SeqAIJOps ops[1] /* operations for SeqAIJ and its subclasses */ typedef struct { MatTransposeColoring matcoloring; Mat Bt_den; /* dense matrix of B^T */ Mat ABt_den; /* dense matrix of A*B^T */ PetscBool usecoloring; } MatProductCtx_MatMatTransMult; typedef struct { /* used by MatTransposeMatMult() */ Mat At; /* transpose of the first matrix */ Mat mA; /* maij matrix of A */ Vec bt, ct; /* vectors to hold locally transposed arrays of B and C */ /* used by PtAP */ void *data; PetscCtxDestroyFn *destroy; } MatProductCtx_MatTransMatMult; typedef struct { PetscInt *api, *apj; /* symbolic structure of A*P */ PetscScalar *apa; /* temporary array for storing one row of A*P */ } MatProductCtx_AP; typedef struct { MatTransposeColoring matcoloring; Mat Rt; /* sparse or dense matrix of R^T */ Mat RARt; /* dense matrix of R*A*R^T */ Mat ARt; /* A*R^T used for the case -matrart_color_art */ MatScalar *work; /* work array to store columns of A*R^T used in MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqDense() */ /* free intermediate products needed for PtAP */ void *data; PetscCtxDestroyFn *destroy; } MatProductCtx_RARt; typedef struct { Mat BC; /* temp matrix for storing B*C */ } MatProductCtx_MatMatMatMult; /* MATSEQAIJ format - Compressed row storage (also called Yale sparse matrix format) or compressed sparse row (CSR). The i[] and j[] arrays start at 0. For example, j[i[k]+p] is the pth column in row k. Note that the diagonal matrix elements are stored with the rest of the nonzeros (not separately). */ /* Info about i-nodes (identical nodes) helper class for SeqAIJ */ typedef struct { /* data for MatSOR_SeqAIJ_Inode() */ MatScalar *bdiag, *ibdiag, *ssor_work; /* diagonal blocks of matrices */ PetscInt bdiagsize; /* length of bdiag and ibdiag */ PetscObjectState ibdiagState; /* state of the matrix when ibdiag[] and bdiag[] were constructed */ PetscBool use; PetscInt node_count; /* number of inodes */ PetscInt *size_csr; /* inode sizes in csr with size_csr[0] = 0 and i-th node size = size_csr[i+1] - size_csr[i], to facilitate parallel computation */ PetscInt limit; /* inode limit */ PetscInt max_limit; /* maximum supported inode limit */ PetscBool checked; /* if inodes have been checked for */ PetscObjectState mat_nonzerostate; /* non-zero state when inodes were checked for */ } Mat_SeqAIJ_Inode; PETSC_INTERN PetscErrorCode MatView_SeqAIJ_Inode(Mat, PetscViewer); PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ_Inode(Mat, MatAssemblyType); PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ_Inode(Mat); PETSC_INTERN PetscErrorCode MatCreate_SeqAIJ_Inode(Mat); PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ_Inode(Mat, MatOption, PetscBool); PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ_Inode(Mat, MatDuplicateOption, Mat *); PETSC_INTERN PetscErrorCode MatDuplicateNoCreate_SeqAIJ(Mat, Mat, MatDuplicateOption, PetscBool); PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_Inode(Mat, Mat, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatSeqAIJGetArray_SeqAIJ(Mat, PetscScalar **); PETSC_INTERN PetscErrorCode MatSeqAIJRestoreArray_SeqAIJ(Mat, PetscScalar **); typedef struct { SEQAIJHEADER(MatScalar); Mat_SeqAIJ_Inode inode; MatScalar *saved_values; /* location for stashing nonzero values of matrix */ /* data needed for MatSOR_SeqAIJ() */ PetscScalar *mdiag, *idiag; /* diagonal values, inverse of diagonal entries */ PetscScalar *ssor_work; /* workspace for Eisenstat trick */ PetscObjectState idiagState; /* state of the matrix when mdiag and idiag was obtained */ PetscScalar fshift, omega; /* last used omega and fshift */ PetscScalar *ibdiag; /* inverses of block diagonals */ PetscBool ibdiagvalid; /* inverses of block diagonals are valid. */ /* MatSetValues() via hash related fields */ PetscHMapIJV ht; PetscInt *dnz; struct _MatOps cops; } Mat_SeqAIJ; typedef struct { PetscInt nz; /* nz of the matrix after assembly */ PetscCount n; /* Number of entries in MatSetPreallocationCOO() */ PetscCount Atot; /* Total number of valid (i.e., w/ non-negative indices) entries in the COO array */ PetscCount *jmap; /* perm[jmap[i]..jmap[i+1]) give indices of entries in v[] associated with i-th nonzero of the matrix */ PetscCount *perm; /* The permutation array in sorting (i,j) by row and then by col */ } MatCOOStruct_SeqAIJ; #define MatSeqXAIJGetOptions_Private(A) \ { \ const PetscBool oldvalues = (PetscBool)(A != PETSC_NULLPTR); \ PetscInt nonew = 0, nounused = 0; \ PetscBool roworiented = PETSC_FALSE; \ if (oldvalues) { \ nonew = ((Mat_SeqAIJ *)A->data)->nonew; \ nounused = ((Mat_SeqAIJ *)A->data)->nounused; \ roworiented = ((Mat_SeqAIJ *)A->data)->roworiented; \ } \ (void)0 #define MatSeqXAIJRestoreOptions_Private(A) \ if (oldvalues) { \ ((Mat_SeqAIJ *)A->data)->nonew = nonew; \ ((Mat_SeqAIJ *)A->data)->nounused = nounused; \ ((Mat_SeqAIJ *)A->data)->roworiented = roworiented; \ } \ } \ (void)0 static inline PetscErrorCode MatXAIJAllocatea(Mat A, PetscInt nz, PetscScalar **array) { Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data; PetscFunctionBegin; PetscCall(PetscShmgetAllocateArray(nz, sizeof(PetscScalar), (void **)array)); a->free_a = PETSC_TRUE; PetscFunctionReturn(PETSC_SUCCESS); } static inline PetscErrorCode MatXAIJDeallocatea(Mat A, PetscScalar **array) { Mat_SeqAIJ *a = (Mat_SeqAIJ *)A->data; PetscFunctionBegin; if (a->free_a) PetscCall(PetscShmgetDeallocateArray((void **)array)); a->free_a = PETSC_FALSE; PetscFunctionReturn(PETSC_SUCCESS); } /* Frees the a, i, and j arrays from the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types */ static inline PetscErrorCode MatSeqXAIJFreeAIJ(Mat AA, MatScalar **a, PetscInt **j, PetscInt **i) { Mat_SeqAIJ *A = (Mat_SeqAIJ *)AA->data; PetscFunctionBegin; if (A->free_a) PetscCall(PetscShmgetDeallocateArray((void **)a)); if (A->free_ij) PetscCall(PetscShmgetDeallocateArray((void **)j)); if (A->free_ij) PetscCall(PetscShmgetDeallocateArray((void **)i)); PetscFunctionReturn(PETSC_SUCCESS); } /* Allocates larger a, i, and j arrays for the XAIJ (AIJ, BAIJ, and SBAIJ) matrix types This is a macro because it takes the datatype as an argument which can be either a Mat or a MatScalar */ #define MatSeqXAIJReallocateAIJ(Amat, AM, BS2, NROW, ROW, COL, RMAX, AA, AI, AJ, RP, AP, AIMAX, NONEW, datatype) \ do { \ if (NROW >= RMAX) { \ Mat_SeqAIJ *Ain = (Mat_SeqAIJ *)Amat->data; \ PetscInt CHUNKSIZE = 15, new_nz = AI[AM] + CHUNKSIZE, len, *new_i = NULL, *new_j = NULL; \ datatype *new_a; \ \ PetscCheck(NONEW != -2, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "New nonzero at (%" PetscInt_FMT ",%" PetscInt_FMT ") caused a malloc. Use MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check", ROW, COL); \ /* malloc new storage space */ \ PetscCall(PetscShmgetAllocateArray(BS2 * new_nz, sizeof(PetscScalar), (void **)&new_a)); \ PetscCall(PetscShmgetAllocateArray(new_nz, sizeof(PetscInt), (void **)&new_j)); \ PetscCall(PetscShmgetAllocateArray(AM + 1, sizeof(PetscInt), (void **)&new_i)); \ Ain->free_a = PETSC_TRUE; \ Ain->free_ij = PETSC_TRUE; \ /* copy over old data into new slots */ \ for (ii = 0; ii < ROW + 1; ii++) new_i[ii] = AI[ii]; \ for (ii = ROW + 1; ii < AM + 1; ii++) new_i[ii] = AI[ii] + CHUNKSIZE; \ PetscCall(PetscArraycpy(new_j, AJ, AI[ROW] + NROW)); \ len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \ PetscCall(PetscArraycpy(new_j + AI[ROW] + NROW + CHUNKSIZE, PetscSafePointerPlusOffset(AJ, AI[ROW] + NROW), len)); \ PetscCall(PetscArraycpy(new_a, AA, BS2 * (AI[ROW] + NROW))); \ PetscCall(PetscArrayzero(new_a + BS2 * (AI[ROW] + NROW), BS2 * CHUNKSIZE)); \ PetscCall(PetscArraycpy(new_a + BS2 * (AI[ROW] + NROW + CHUNKSIZE), PetscSafePointerPlusOffset(AA, BS2 * (AI[ROW] + NROW)), BS2 * len)); \ /* free up old matrix storage */ \ PetscCall(MatSeqXAIJFreeAIJ(A, &Ain->a, &Ain->j, &Ain->i)); \ AA = new_a; \ Ain->a = new_a; \ AI = Ain->i = new_i; \ AJ = Ain->j = new_j; \ \ RP = AJ + AI[ROW]; \ AP = AA + BS2 * AI[ROW]; \ RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \ Ain->maxnz += BS2 * CHUNKSIZE; \ Ain->reallocs++; \ Amat->nonzerostate++; \ } \ } while (0) #define MatSeqXAIJReallocateAIJ_structure_only(Amat, AM, BS2, NROW, ROW, COL, RMAX, AI, AJ, RP, AIMAX, NONEW, datatype) \ do { \ if (NROW >= RMAX) { \ Mat_SeqAIJ *Ain = (Mat_SeqAIJ *)Amat->data; \ /* there is no extra room in row, therefore enlarge */ \ PetscInt CHUNKSIZE = 15, new_nz = AI[AM] + CHUNKSIZE, len, *new_i = NULL, *new_j = NULL; \ \ PetscCheck(NONEW != -2, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "New nonzero at (%" PetscInt_FMT ",%" PetscInt_FMT ") caused a malloc. Use MatSetOption(A, MAT_NEW_NONZERO_ALLOCATION_ERR, PETSC_FALSE) to turn off this check", ROW, COL); \ /* malloc new storage space */ \ PetscCall(PetscShmgetAllocateArray(new_nz, sizeof(PetscInt), (void **)&new_j)); \ PetscCall(PetscShmgetAllocateArray(AM + 1, sizeof(PetscInt), (void **)&new_i)); \ Ain->free_a = PETSC_FALSE; \ Ain->free_ij = PETSC_TRUE; \ \ /* copy over old data into new slots */ \ for (ii = 0; ii < ROW + 1; ii++) new_i[ii] = AI[ii]; \ for (ii = ROW + 1; ii < AM + 1; ii++) new_i[ii] = AI[ii] + CHUNKSIZE; \ PetscCall(PetscArraycpy(new_j, AJ, AI[ROW] + NROW)); \ len = (new_nz - CHUNKSIZE - AI[ROW] - NROW); \ PetscCall(PetscArraycpy(new_j + AI[ROW] + NROW + CHUNKSIZE, AJ + AI[ROW] + NROW, len)); \ \ /* free up old matrix storage */ \ PetscCall(MatSeqXAIJFreeAIJ(A, &Ain->a, &Ain->j, &Ain->i)); \ Ain->a = NULL; \ AI = Ain->i = new_i; \ AJ = Ain->j = new_j; \ \ RP = AJ + AI[ROW]; \ RMAX = AIMAX[ROW] = AIMAX[ROW] + CHUNKSIZE; \ Ain->maxnz += BS2 * CHUNKSIZE; \ Ain->reallocs++; \ Amat->nonzerostate++; \ } \ } while (0) PETSC_INTERN PetscErrorCode MatSeqAIJSetPreallocation_SeqAIJ(Mat, PetscInt, const PetscInt *); PETSC_INTERN PetscErrorCode MatSetPreallocationCOO_SeqAIJ(Mat, PetscCount, PetscInt[], PetscInt[]); PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ(Mat, Mat, IS, IS, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatILUFactorSymbolic_SeqAIJ_ilu0(Mat, Mat, IS, IS, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatICCFactorSymbolic_SeqAIJ(Mat, Mat, IS, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatCholeskyFactorSymbolic_SeqAIJ(Mat, Mat, IS, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ_inplace(Mat, Mat, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatCholeskyFactorNumeric_SeqAIJ(Mat, Mat, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatDuplicate_SeqAIJ(Mat, MatDuplicateOption, Mat *); PETSC_INTERN PetscErrorCode MatCopy_SeqAIJ(Mat, Mat, MatStructure); PETSC_EXTERN PetscErrorCode MatGetDiagonalMarkers_SeqAIJ(Mat, const PetscInt **, PetscBool *); PETSC_INTERN PetscErrorCode MatFindZeroDiagonals_SeqAIJ_Private(Mat, PetscInt *, PetscInt **); PETSC_INTERN PetscErrorCode MatMult_SeqAIJ(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatMult_SeqAIJ_Inode(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ(Mat, Vec, Vec, Vec); PETSC_INTERN PetscErrorCode MatMultAdd_SeqAIJ_Inode(Mat, Vec, Vec, Vec); PETSC_INTERN PetscErrorCode MatMultTranspose_SeqAIJ(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatMultTransposeAdd_SeqAIJ(Mat, Vec, Vec, Vec); PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec); PETSC_INTERN PetscErrorCode MatSOR_SeqAIJ_Inode(Mat, Vec, PetscReal, MatSORType, PetscReal, PetscInt, PetscInt, Vec); PETSC_INTERN PetscErrorCode MatSetOption_SeqAIJ(Mat, MatOption, PetscBool); PETSC_INTERN PetscErrorCode MatGetSymbolicTranspose_SeqAIJ(Mat, PetscInt *[], PetscInt *[]); PETSC_INTERN PetscErrorCode MatRestoreSymbolicTranspose_SeqAIJ(Mat, PetscInt *[], PetscInt *[]); PETSC_INTERN PetscErrorCode MatGetSymbolicTransposeReduced_SeqAIJ(Mat, PetscInt, PetscInt, PetscInt *[], PetscInt *[]); PETSC_INTERN PetscErrorCode MatTransposeSymbolic_SeqAIJ(Mat, Mat *); PETSC_INTERN PetscErrorCode MatTranspose_SeqAIJ(Mat, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatToSymmetricIJ_SeqAIJ(PetscInt, PetscInt *, PetscInt *, PetscBool, PetscInt, PetscInt, PetscInt **, PetscInt **); PETSC_INTERN PetscErrorCode MatLUFactorSymbolic_SeqAIJ(Mat, Mat, IS, IS, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_inplace(Mat, Mat, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ(Mat, Mat, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatLUFactorNumeric_SeqAIJ_InplaceWithPerm(Mat, Mat, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatLUFactor_SeqAIJ(Mat, IS, IS, const MatFactorInfo *); PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_inplace(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_Inode(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolve_SeqAIJ_NaturalOrdering(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolveAdd_SeqAIJ(Mat, Vec, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ_inplace(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolveTranspose_SeqAIJ(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ_inplace(Mat, Vec, Vec, Vec); PETSC_INTERN PetscErrorCode MatSolveTransposeAdd_SeqAIJ(Mat, Vec, Vec, Vec); PETSC_INTERN PetscErrorCode MatMatSolve_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatMatSolveTranspose_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatEqual_SeqAIJ(Mat, Mat, PetscBool *); PETSC_INTERN PetscErrorCode MatFDColoringCreate_SeqXAIJ(Mat, ISColoring, MatFDColoring); PETSC_INTERN PetscErrorCode MatFDColoringSetUp_SeqXAIJ(Mat, ISColoring, MatFDColoring); PETSC_INTERN PetscErrorCode MatFDColoringSetUpBlocked_AIJ_Private(Mat, MatFDColoring, PetscInt); PETSC_INTERN PetscErrorCode MatLoad_AIJ_HDF5(Mat, PetscViewer); PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ_Binary(Mat, PetscViewer); PETSC_INTERN PetscErrorCode MatLoad_SeqAIJ(Mat, PetscViewer); PETSC_INTERN PetscErrorCode RegisterApplyPtAPRoutines_Private(Mat); #if defined(PETSC_HAVE_HYPRE) PETSC_INTERN PetscErrorCode MatProductSetFromOptions_Transpose_AIJ_AIJ(Mat); #endif PETSC_INTERN PetscErrorCode MatProductSetFromOptions_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatProductSymbolic_SeqAIJ_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatProductSymbolic_PtAP_SeqAIJ_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatProductSymbolic_RARt_SeqAIJ_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Sorted(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqDense_SeqAIJ(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Scalable_fast(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_Heap(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_BTHeap(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_RowMerge(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMultSymbolic_SeqAIJ_SeqAIJ_LLCondensed(Mat, Mat, PetscReal, Mat); #if defined(PETSC_HAVE_HYPRE) PETSC_INTERN PetscErrorCode MatMatMultSymbolic_AIJ_AIJ_wHYPRE(Mat, Mat, PetscReal, Mat); #endif PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Sorted(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqDense_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatMatMultNumeric_SeqAIJ_SeqAIJ_Scalable(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatPtAPSymbolic_SeqAIJ_SeqAIJ_SparseAxpy(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatPtAPNumeric_SeqAIJ_SeqAIJ_SparseAxpy(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_matmattransposemult(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatRARtSymbolic_SeqAIJ_SeqAIJ_colorrart(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_matmattransposemult(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatRARtNumeric_SeqAIJ_SeqAIJ_colorrart(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatTransposeMatMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatTransposeMatMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatProductCtxDestroy_SeqAIJ_MatTransMatMult(PetscCtxRt); PETSC_INTERN PetscErrorCode MatMatTransposeMultSymbolic_SeqAIJ_SeqAIJ(Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatTransposeMultNumeric_SeqAIJ_SeqAIJ(Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatTransposeColoringCreate_SeqAIJ(Mat, ISColoring, MatTransposeColoring); PETSC_INTERN PetscErrorCode MatTransColoringApplySpToDen_SeqAIJ(MatTransposeColoring, Mat, Mat); PETSC_INTERN PetscErrorCode MatTransColoringApplyDenToSp_SeqAIJ(MatTransposeColoring, Mat, Mat); PETSC_INTERN PetscErrorCode MatMatMatMultSymbolic_SeqAIJ_SeqAIJ_SeqAIJ(Mat, Mat, Mat, PetscReal, Mat); PETSC_INTERN PetscErrorCode MatMatMatMultNumeric_SeqAIJ_SeqAIJ_SeqAIJ(Mat, Mat, Mat, Mat); PETSC_INTERN PetscErrorCode MatSetRandomSkipColumnRange_SeqAIJ_Private(Mat, PetscInt, PetscInt, PetscRandom); PETSC_INTERN PetscErrorCode MatSetValues_SeqAIJ(Mat, PetscInt, const PetscInt[], PetscInt, const PetscInt[], const PetscScalar[], InsertMode); PETSC_INTERN PetscErrorCode MatGetRow_SeqAIJ(Mat, PetscInt, PetscInt *, PetscInt **, PetscScalar **); PETSC_INTERN PetscErrorCode MatRestoreRow_SeqAIJ(Mat, PetscInt, PetscInt *, PetscInt **, PetscScalar **); PETSC_INTERN PetscErrorCode MatScale_SeqAIJ(Mat, PetscScalar); PETSC_INTERN PetscErrorCode MatDiagonalScale_SeqAIJ(Mat, Vec, Vec); PETSC_INTERN PetscErrorCode MatDiagonalSet_SeqAIJ(Mat, Vec, InsertMode); PETSC_INTERN PetscErrorCode MatAXPY_SeqAIJ(Mat, PetscScalar, Mat, MatStructure); PETSC_INTERN PetscErrorCode MatGetRowIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *); PETSC_INTERN PetscErrorCode MatRestoreRowIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *); PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *); PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscBool *); PETSC_INTERN PetscErrorCode MatGetColumnIJ_SeqAIJ_Color(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscInt *[], PetscBool *); PETSC_INTERN PetscErrorCode MatRestoreColumnIJ_SeqAIJ_Color(Mat, PetscInt, PetscBool, PetscBool, PetscInt *, const PetscInt *[], const PetscInt *[], PetscInt *[], PetscBool *); PETSC_INTERN PetscErrorCode MatDestroy_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatView_SeqAIJ(Mat, PetscViewer); PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode(Mat); PETSC_INTERN PetscErrorCode MatSeqAIJCheckInode_FactorLU(Mat); PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqAIJ(Mat, Mat, PetscInt *); #if defined(PETSC_HAVE_MATLAB) PETSC_EXTERN PetscErrorCode MatlabEnginePut_SeqAIJ(PetscObject, void *); PETSC_EXTERN PetscErrorCode MatlabEngineGet_SeqAIJ(PetscObject, void *); #endif PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqSBAIJ(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqBAIJ(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqDense(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJCRL(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_Elemental(Mat, MatType, MatReuse, Mat *); #if defined(PETSC_HAVE_SCALAPACK) PETSC_INTERN PetscErrorCode MatConvert_AIJ_ScaLAPACK(Mat, MatType, MatReuse, Mat *); #endif PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJPERM(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJSELL(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJViennaCL(Mat, MatType, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatReorderForNonzeroDiagonal_SeqAIJ(Mat, PetscReal, IS, IS); PETSC_INTERN PetscErrorCode MatRARt_SeqAIJ_SeqAIJ(Mat, Mat, MatReuse, PetscReal, Mat *); PETSC_EXTERN PetscErrorCode MatCreate_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatAssemblyEnd_SeqAIJ(Mat, MatAssemblyType); PETSC_INTERN PetscErrorCode MatZeroEntries_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatAXPYGetPreallocation_SeqX_private(PetscInt, const PetscInt *, const PetscInt *, const PetscInt *, const PetscInt *, PetscInt *); PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqAIJ(MPI_Comm, Mat, PetscInt, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIAIJ(MPI_Comm, Mat, PetscInt, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatSetSeqMat_SeqAIJ(Mat, IS, IS, MatStructure, Mat); PETSC_INTERN PetscErrorCode MatEliminateZeros_SeqAIJ(Mat, PetscBool); PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Private(Mat_SubSppt *); PETSC_INTERN PetscErrorCode MatDestroySubMatrix_SeqAIJ(Mat); PETSC_INTERN PetscErrorCode MatDestroySubMatrix_Dummy(Mat); PETSC_INTERN PetscErrorCode MatDestroySubMatrices_Dummy(PetscInt, Mat *[]); PETSC_INTERN PetscErrorCode MatCreateSubMatrix_SeqAIJ(Mat, IS, IS, PetscInt, MatReuse, Mat *); PETSC_INTERN PetscErrorCode MatSetSeqAIJWithArrays_private(MPI_Comm, PetscInt, PetscInt, PetscInt[], PetscInt[], PetscScalar[], MatType, Mat); PETSC_INTERN PetscErrorCode MatResetPreallocation_SeqAIJ_Private(Mat A, PetscBool *memoryreset); PETSC_SINGLE_LIBRARY_INTERN PetscErrorCode MatSeqAIJCompactOutExtraColumns_SeqAIJ(Mat, ISLocalToGlobalMapping *); /* PetscSparseDenseMinusDot - The inner kernel of triangular solves and Gauss-Siedel smoothing. \sum_i xv[i] * r[xi[i]] for CSR storage Input Parameters: + nnz - the number of entries . r - the array of vector values . xv - the matrix values for the row - xi - the column indices of the nonzeros in the row Output Parameter: . sum - negative the sum of results PETSc compile flags: + PETSC_KERNEL_USE_UNROLL_4 - PETSC_KERNEL_USE_UNROLL_2 Developer Note: The macro changes sum but not other parameters .seealso: `PetscSparseDensePlusDot()` */ #if defined(PETSC_KERNEL_USE_UNROLL_4) #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \ do { \ if (nnz > 0) { \ PetscInt nnz2 = nnz, rem = nnz & 0x3; \ switch (rem) { \ case 3: \ sum -= *xv++ * r[*xi++]; \ case 2: \ sum -= *xv++ * r[*xi++]; \ case 1: \ sum -= *xv++ * r[*xi++]; \ nnz2 -= rem; \ } \ while (nnz2 > 0) { \ sum -= xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \ xv += 4; \ xi += 4; \ nnz2 -= 4; \ } \ xv -= nnz; \ xi -= nnz; \ } \ } while (0) #elif defined(PETSC_KERNEL_USE_UNROLL_2) #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \ do { \ PetscInt __i, __i1, __i2; \ for (__i = 0; __i < nnz - 1; __i += 2) { \ __i1 = xi[__i]; \ __i2 = xi[__i + 1]; \ sum -= (xv[__i] * r[__i1] + xv[__i + 1] * r[__i2]); \ } \ if (nnz & 0x1) sum -= xv[__i] * r[xi[__i]]; \ } while (0) #else #define PetscSparseDenseMinusDot(sum, r, xv, xi, nnz) \ do { \ PetscInt __i; \ for (__i = 0; __i < nnz; __i++) sum -= xv[__i] * r[xi[__i]]; \ } while (0) #endif /* PetscSparseDensePlusDot - The inner kernel of matrix-vector product \sum_i xv[i] * r[xi[i]] for CSR storage Input Parameters: + nnz - the number of entries . r - the array of vector values . xv - the matrix values for the row - xi - the column indices of the nonzeros in the row Output Parameter: . sum - the sum of results PETSc compile flags: + PETSC_KERNEL_USE_UNROLL_4 - PETSC_KERNEL_USE_UNROLL_2 Developer Note: The macro changes sum but not other parameters .seealso: `PetscSparseDenseMinusDot()` */ #if defined(PETSC_KERNEL_USE_UNROLL_4) #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \ do { \ if (nnz > 0) { \ PetscInt nnz2 = nnz, rem = nnz & 0x3; \ switch (rem) { \ case 3: \ sum += *xv++ * r[*xi++]; \ case 2: \ sum += *xv++ * r[*xi++]; \ case 1: \ sum += *xv++ * r[*xi++]; \ nnz2 -= rem; \ } \ while (nnz2 > 0) { \ sum += xv[0] * r[xi[0]] + xv[1] * r[xi[1]] + xv[2] * r[xi[2]] + xv[3] * r[xi[3]]; \ xv += 4; \ xi += 4; \ nnz2 -= 4; \ } \ xv -= nnz; \ xi -= nnz; \ } \ } while (0) #elif defined(PETSC_KERNEL_USE_UNROLL_2) #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \ do { \ PetscInt __i, __i1, __i2; \ for (__i = 0; __i < nnz - 1; __i += 2) { \ __i1 = xi[__i]; \ __i2 = xi[__i + 1]; \ sum += (xv[__i] * r[__i1] + xv[__i + 1] * r[__i2]); \ } \ if (nnz & 0x1) sum += xv[__i] * r[xi[__i]]; \ } while (0) #elif !(defined(__GNUC__) && defined(_OPENMP)) && 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) #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) PetscSparseDensePlusDot_AVX512_Private(&(sum), (r), (xv), (xi), (nnz)) #else #define PetscSparseDensePlusDot(sum, r, xv, xi, nnz) \ do { \ PetscInt __i; \ for (__i = 0; __i < nnz; __i++) sum += xv[__i] * r[xi[__i]]; \ } while (0) #endif #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) #include #if !defined(_MM_SCALE_8) #define _MM_SCALE_8 8 #endif static inline void PetscSparseDensePlusDot_AVX512_Private(PetscScalar *sum, const PetscScalar *x, const MatScalar *aa, const PetscInt *aj, PetscInt n) { __m512d vec_x, vec_y, vec_vals; __m256i vec_idx; PetscInt j; vec_y = _mm512_setzero_pd(); for (j = 0; j < (n >> 3); j++) { vec_idx = _mm256_loadu_si256((__m256i const *)aj); vec_vals = _mm512_loadu_pd(aa); vec_x = _mm512_i32gather_pd(vec_idx, x, _MM_SCALE_8); vec_y = _mm512_fmadd_pd(vec_x, vec_vals, vec_y); aj += 8; aa += 8; } #if defined(__AVX512VL__) /* masked load requires avx512vl, which is not supported by KNL */ if (n & 0x07) { __mmask8 mask; mask = (__mmask8)(0xff >> (8 - (n & 0x07))); vec_idx = _mm256_mask_loadu_epi32(vec_idx, mask, aj); vec_vals = _mm512_mask_loadu_pd(vec_vals, mask, aa); vec_x = _mm512_mask_i32gather_pd(vec_x, mask, vec_idx, x, _MM_SCALE_8); vec_y = _mm512_mask3_fmadd_pd(vec_x, vec_vals, vec_y, mask); } *sum += _mm512_reduce_add_pd(vec_y); #else *sum += _mm512_reduce_add_pd(vec_y); for (j = 0; j < (n & 0x07); j++) *sum += aa[j] * x[aj[j]]; #endif } #endif /* PetscSparseDenseMaxDot - The inner kernel of a modified matrix-vector product \max_i xv[i] * r[xi[i]] for CSR storage Input Parameters: + nnz - the number of entries . r - the array of vector values . xv - the matrix values for the row - xi - the column indices of the nonzeros in the row Output Parameter: . max - the max of results .seealso: `PetscSparseDensePlusDot()`, `PetscSparseDenseMinusDot()` */ #define PetscSparseDenseMaxDot(max, r, xv, xi, nnz) \ do { \ for (PetscInt __i = 0; __i < (nnz); __i++) max = PetscMax(PetscRealPart(max), PetscRealPart((xv)[__i] * (r)[(xi)[__i]])); \ } while (0) /* Add column indices into table for counting the max nonzeros of merged rows */ #define MatRowMergeMax_SeqAIJ(mat, nrows, ta) \ do { \ if (mat) { \ for (PetscInt _row = 0; _row < (nrows); _row++) { \ const PetscInt _nz = (mat)->i[_row + 1] - (mat)->i[_row]; \ for (PetscInt _j = 0; _j < _nz; _j++) { \ PetscInt *_col = _j + (mat)->j + (mat)->i[_row]; \ PetscCall(PetscHMapISet((ta), *_col + 1, 1)); \ } \ } \ } \ } while (0) /* Add column indices into table for counting the nonzeros of merged rows */ #define MatMergeRows_SeqAIJ(mat, nrows, rows, ta) \ do { \ for (PetscInt _i = 0; _i < (nrows); _i++) { \ const PetscInt _row = (rows)[_i]; \ const PetscInt _nz = (mat)->i[_row + 1] - (mat)->i[_row]; \ for (PetscInt _j = 0; _j < _nz; _j++) { \ PetscInt *_col = _j + (mat)->j + (mat)->i[_row]; \ PetscCall(PetscHMapISetWithMode((ta), *_col + 1, 1, INSERT_VALUES)); \ } \ } \ } while (0)