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 on MPI_Comm 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 .keywords: matrix, cray, sparse, parallel 84 85 .seealso: MatCreate(), MatCreateSeqAIJPERM(), MatSetValues() 86 @*/ 87 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) 88 { 89 PetscErrorCode ierr; 90 PetscMPIInt size; 91 92 PetscFunctionBegin; 93 ierr = MatCreate(comm,A);CHKERRQ(ierr); 94 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 95 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 96 if (size > 1) { 97 ierr = MatSetType(*A,MATMPIAIJPERM);CHKERRQ(ierr); 98 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 99 } else { 100 ierr = MatSetType(*A,MATSEQAIJPERM);CHKERRQ(ierr); 101 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 102 } 103 PetscFunctionReturn(0); 104 } 105 106 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJPERM(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[]) 107 { 108 Mat_MPIAIJ *b = (Mat_MPIAIJ*)B->data; 109 PetscErrorCode ierr; 110 111 PetscFunctionBegin; 112 ierr = MatMPIAIJSetPreallocation_MPIAIJ(B,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 113 ierr = MatConvert_SeqAIJ_SeqAIJPERM(b->A, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->A);CHKERRQ(ierr); 114 ierr = MatConvert_SeqAIJ_SeqAIJPERM(b->B, MATSEQAIJPERM, MAT_INPLACE_MATRIX, &b->B);CHKERRQ(ierr); 115 PetscFunctionReturn(0); 116 } 117 118 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJPERM(Mat A,MatType type,MatReuse reuse,Mat *newmat) 119 { 120 PetscErrorCode ierr; 121 Mat B = *newmat; 122 123 PetscFunctionBegin; 124 if (reuse == MAT_INITIAL_MATRIX) { 125 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 126 } 127 128 ierr = PetscObjectChangeTypeName((PetscObject) B, MATMPIAIJPERM);CHKERRQ(ierr); 129 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJPERM);CHKERRQ(ierr); 130 *newmat = B; 131 PetscFunctionReturn(0); 132 } 133 134 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJPERM(Mat A) 135 { 136 PetscErrorCode ierr; 137 138 PetscFunctionBegin; 139 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 140 ierr = MatConvert_MPIAIJ_MPIAIJPERM(A,MATMPIAIJPERM,MAT_INPLACE_MATRIX,&A);CHKERRQ(ierr); 141 PetscFunctionReturn(0); 142 } 143 144 /*MC 145 MATAIJPERM - MATAIJPERM = "AIJPERM" - A matrix type to be used for sparse matrices. 146 147 This matrix type is identical to MATSEQAIJPERM when constructed with a single process communicator, 148 and MATMPIAIJPERM otherwise. As a result, for single process communicators, 149 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 150 for communicators controlling multiple processes. It is recommended that you call both of 151 the above preallocation routines for simplicity. 152 153 Options Database Keys: 154 . -mat_type aijperm - sets the matrix type to "AIJPERM" during a call to MatSetFromOptions() 155 156 Level: beginner 157 158 .seealso: MatCreateMPIAIJPERM(), MATSEQAIJPERM, MATMPIAIJPERM 159 M*/ 160 161