1 2 #include <../src/mat/impls/aij/mpi/mpiaij.h> 3 /*@C 4 MatCreateMPIAIJPERM - Creates a sparse parallel matrix whose local 5 portions are stored as SEQAIJPERM matrices (a matrix class that inherits 6 from SEQAIJ but includes some optimizations to allow more effective 7 vectorization). The same guidelines that apply to MPIAIJ matrices for 8 preallocating the matrix storage apply here as well. 9 10 Collective 11 12 Input Parameters: 13 + comm - MPI communicator 14 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 15 This value should be the same as the local size used in creating the 16 y vector for the matrix-vector product y = Ax. 17 . n - This value should be the same as the local size used in creating the 18 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 19 calculated if N is given) For square matrices n is almost always m. 20 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 21 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 22 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 23 (same value is used for all local rows) 24 . d_nnz - array containing the number of nonzeros in the various rows of the 25 DIAGONAL portion of the local submatrix (possibly different for each row) 26 or NULL, if d_nz is used to specify the nonzero structure. 27 The size of this array is equal to the number of local rows, i.e 'm'. 28 For matrices you plan to factor you must leave room for the diagonal entry and 29 put in the entry even if it is zero. 30 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 31 submatrix (same value is used for all local rows). 32 - o_nnz - array containing the number of nonzeros in the various rows of the 33 OFF-DIAGONAL portion of the local submatrix (possibly different for 34 each row) or NULL, if o_nz is used to specify the nonzero 35 structure. The size of this array is equal to the number 36 of local rows, i.e 'm'. 37 38 Output Parameter: 39 . A - the matrix 40 41 Notes: 42 If the *_nnz parameter is given then the *_nz parameter is ignored 43 44 m,n,M,N parameters specify the size of the matrix, and its partitioning across 45 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 46 storage requirements for this matrix. 47 48 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 49 processor than it must be used on all processors that share the object for 50 that argument. 51 52 The user MUST specify either the local or global matrix dimensions 53 (possibly both). 54 55 The parallel matrix is partitioned such that the first m0 rows belong to 56 process 0, the next m1 rows belong to process 1, the next m2 rows belong 57 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 58 59 The DIAGONAL portion of the local submatrix of a processor can be defined 60 as the submatrix which is obtained by extraction the part corresponding 61 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 62 first row that belongs to the processor, and r2 is the last row belonging 63 to the this processor. This is a square mxm matrix. The remaining portion 64 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 65 66 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 67 68 When calling this routine with a single process communicator, a matrix of 69 type SEQAIJPERM is returned. If a matrix of type MPIAIJPERM is desired 70 for this type of communicator, use the construction mechanism: 71 MatCreate(...,&A); MatSetType(A,MPIAIJ); MatMPIAIJSetPreallocation(A,...); 72 73 By default, this format uses inodes (identical nodes) when possible. 74 We search for consecutive rows with the same nonzero structure, thereby 75 reusing matrix information to achieve increased efficiency. 76 77 Options Database Keys: 78 + -mat_no_inode - Do not use inodes 79 - -mat_inode_limit <limit> - Sets inode limit (max limit=5) 80 81 Level: intermediate 82 83 .seealso: MatCreate(), MatCreateSeqAIJPERM(), MatSetValues() 84 @*/ 85 PetscErrorCode MatCreateMPIAIJPERM(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A) 86 { 87 PetscErrorCode ierr; 88 PetscMPIInt size; 89 90 PetscFunctionBegin; 91 ierr = MatCreate(comm,A);CHKERRQ(ierr); 92 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 93 ierr = MPI_Comm_size(comm,&size);CHKERRMPI(ierr); 94 if (size > 1) { 95 ierr = MatSetType(*A,MATMPIAIJPERM);CHKERRQ(ierr); 96 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 97 } else { 98 ierr = MatSetType(*A,MATSEQAIJPERM);CHKERRQ(ierr); 99 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 100 } 101 PetscFunctionReturn(0); 102 } 103 104 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJPERM(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 105 { 106 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 107 PetscErrorCode ierr; 108 109 PetscFunctionBegin; 110 ierr = MatMPIAIJSetPreallocation_MPIAIJ(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 111 ierr = MatConvert_SeqAIJ_SeqAIJPERM(b->A, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->A);CHKERRQ(ierr); 112 ierr = MatConvert_SeqAIJ_SeqAIJPERM(b->B, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->B);CHKERRQ(ierr); 113 PetscFunctionReturn(0); 114 } 115 116 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat A,MatType type,MatReuse reuse,Mat *newmat) 117 { 118 PetscErrorCode ierr; 119 Mat B = *newmat; 120 121 PetscFunctionBegin; 122 if (reuse == MAT_INITIAL_MATRIX) { 123 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 124 } 125 126 ierr = PetscObjectChangeTypeName((PetscObject) B, MATMPIAIJPERM);CHKERRQ(ierr); 127 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJPERM);CHKERRQ(ierr); 128 *newmat = B; 129 PetscFunctionReturn(0); 130 } 131 132 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJPERM(Mat A) 133 { 134 PetscErrorCode ierr; 135 136 PetscFunctionBegin; 137 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 138 ierr = MatConvert_MPIAIJ_MPIAIJPERM(A,MATMPIAIJPERM,MAT_INPLACE_MATRIX,&A);CHKERRQ(ierr); 139 PetscFunctionReturn(0); 140 } 141 142 /*MC 143 MATAIJPERM - MATAIJPERM = "AIJPERM" - A matrix type to be used for sparse matrices. 144 145 This matrix type is identical to MATSEQAIJPERM when constructed with a single process communicator, 146 and MATMPIAIJPERM otherwise. As a result, for single process communicators, 147 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 148 for communicators controlling multiple processes. It is recommended that you call both of 149 the above preallocation routines for simplicity. 150 151 Options Database Keys: 152 . -mat_type aijperm - sets the matrix type to "AIJPERM" during a call to MatSetFromOptions() 153 154 Level: beginner 155 156 .seealso: MatCreateMPIAIJPERM(), MATSEQAIJPERM, MATMPIAIJPERM 157 M*/ 158 159