1 #include <../src/mat/impls/aij/mpi/mpiaij.h> 2 #undef __FUNCT__ 3 #define __FUNCT__ "MatCreateMPIAIJMKL" 4 /*@C 5 MatCreateMPIAIJMKL - Creates a sparse parallel matrix whose local 6 portions are stored as SEQAIJMKL matrices (a matrix class that inherits 7 from SEQAIJ but uses some operations provided by Intel MKL). The same 8 guidelines that apply to MPIAIJ matrices for preallocating the matrix 9 storage apply here as well. 10 11 Collective on MPI_Comm 12 13 Input Parameters: 14 + comm - MPI communicator 15 . m - number of local rows (or PETSC_DECIDE to have calculated if M is given) 16 This value should be the same as the local size used in creating the 17 y vector for the matrix-vector product y = Ax. 18 . n - This value should be the same as the local size used in creating the 19 x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have 20 calculated if N is given) For square matrices n is almost always m. 21 . M - number of global rows (or PETSC_DETERMINE to have calculated if m is given) 22 . N - number of global columns (or PETSC_DETERMINE to have calculated if n is given) 23 . d_nz - number of nonzeros per row in DIAGONAL portion of local submatrix 24 (same value is used for all local rows) 25 . d_nnz - array containing the number of nonzeros in the various rows of the 26 DIAGONAL portion of the local submatrix (possibly different for each row) 27 or NULL, if d_nz is used to specify the nonzero structure. 28 The size of this array is equal to the number of local rows, i.e 'm'. 29 For matrices you plan to factor you must leave room for the diagonal entry and 30 put in the entry even if it is zero. 31 . o_nz - number of nonzeros per row in the OFF-DIAGONAL portion of local 32 submatrix (same value is used for all local rows). 33 - o_nnz - array containing the number of nonzeros in the various rows of the 34 OFF-DIAGONAL portion of the local submatrix (possibly different for 35 each row) or NULL, if o_nz is used to specify the nonzero 36 structure. The size of this array is equal to the number 37 of local rows, i.e 'm'. 38 39 Output Parameter: 40 . A - the matrix 41 42 Notes: 43 If the *_nnz parameter is given then the *_nz parameter is ignored 44 45 m,n,M,N parameters specify the size of the matrix, and its partitioning across 46 processors, while d_nz,d_nnz,o_nz,o_nnz parameters specify the approximate 47 storage requirements for this matrix. 48 49 If PETSC_DECIDE or PETSC_DETERMINE is used for a particular argument on one 50 processor than it must be used on all processors that share the object for 51 that argument. 52 53 The user MUST specify either the local or global matrix dimensions 54 (possibly both). 55 56 The parallel matrix is partitioned such that the first m0 rows belong to 57 process 0, the next m1 rows belong to process 1, the next m2 rows belong 58 to process 2 etc.. where m0,m1,m2... are the input parameter 'm'. 59 60 The DIAGONAL portion of the local submatrix of a processor can be defined 61 as the submatrix which is obtained by extraction the part corresponding 62 to the rows r1-r2 and columns r1-r2 of the global matrix, where r1 is the 63 first row that belongs to the processor, and r2 is the last row belonging 64 to the this processor. This is a square mxm matrix. The remaining portion 65 of the local submatrix (mxN) constitute the OFF-DIAGONAL portion. 66 67 If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored. 68 69 When calling this routine with a single process communicator, a matrix of 70 type SEQAIJMKL is returned. If a matrix of type MPIAIJMKL is desired 71 for this type of communicator, use the construction mechanism: 72 MatCreate(...,&A); MatSetType(A,MPIAIJMKL); MatMPIAIJSetPreallocation(A,...); 73 74 Options Database Keys: 75 . -mat_aijmkl_no_spmv2 - disables use of the SpMV2 inspector-executor routines 76 77 Level: intermediate 78 79 .keywords: matrix, MKL, sparse, parallel 80 81 .seealso: MatCreate(), MatCreateSeqAIJMKL(), MatSetValues() 82 @*/ 83 PetscErrorCode MatCreateMPIAIJMKL(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) 84 { 85 PetscErrorCode ierr; 86 PetscMPIInt size; 87 88 PetscFunctionBegin; 89 ierr = MatCreate(comm,A);CHKERRQ(ierr); 90 ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr); 91 ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr); 92 if (size > 1) { 93 ierr = MatSetType(*A,MATMPIAIJMKL);CHKERRQ(ierr); 94 ierr = MatMPIAIJSetPreallocation(*A,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr); 95 } else { 96 ierr = MatSetType(*A,MATSEQAIJMKL);CHKERRQ(ierr); 97 ierr = MatSeqAIJSetPreallocation(*A,d_nz,d_nnz);CHKERRQ(ierr); 98 } 99 PetscFunctionReturn(0); 100 } 101 102 PETSC_INTERN PetscErrorCode MatConvert_SeqAIJ_SeqAIJMKL(Mat,MatType,MatReuse,Mat*); 103 104 #undef __FUNCT__ 105 #define __FUNCT__ "MatMPIAIJSetPreallocation_MPIAIJMKL" 106 PetscErrorCode MatMPIAIJSetPreallocation_MPIAIJMKL(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_SeqAIJMKL(b->A, MATSEQAIJMKL, MAT_INPLACE_MATRIX, &b->A);CHKERRQ(ierr); 114 ierr = MatConvert_SeqAIJ_SeqAIJMKL(b->B, MATSEQAIJMKL, MAT_INPLACE_MATRIX, &b->B);CHKERRQ(ierr); 115 PetscFunctionReturn(0); 116 } 117 118 #undef __FUNCT__ 119 #define __FUNCT__ "MatConvert_MPIAIJ_MPIAIJMKL" 120 PETSC_INTERN PetscErrorCode MatConvert_MPIAIJ_MPIAIJMKL(Mat A,MatType type,MatReuse reuse,Mat *newmat) 121 { 122 PetscErrorCode ierr; 123 Mat B = *newmat; 124 125 PetscFunctionBegin; 126 if (reuse == MAT_INITIAL_MATRIX) { 127 ierr = MatDuplicate(A,MAT_COPY_VALUES,&B);CHKERRQ(ierr); 128 } 129 130 ierr = PetscObjectChangeTypeName((PetscObject) B, MATMPIAIJMKL);CHKERRQ(ierr); 131 ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIAIJSetPreallocation_C",MatMPIAIJSetPreallocation_MPIAIJMKL);CHKERRQ(ierr); 132 *newmat = B; 133 PetscFunctionReturn(0); 134 } 135 136 #undef __FUNCT__ 137 #define __FUNCT__ "MatCreate_MPIAIJMKL" 138 PETSC_EXTERN PetscErrorCode MatCreate_MPIAIJMKL(Mat A) 139 { 140 PetscErrorCode ierr; 141 142 PetscFunctionBegin; 143 ierr = MatSetType(A,MATMPIAIJ);CHKERRQ(ierr); 144 ierr = MatConvert_MPIAIJ_MPIAIJMKL(A,MATMPIAIJMKL,MAT_INPLACE_MATRIX,&A);CHKERRQ(ierr); 145 PetscFunctionReturn(0); 146 } 147 148 /*MC 149 MATAIJMKL - MATAIJMKL = "AIJMKL" - A matrix type to be used for sparse matrices. 150 151 This matrix type is identical to MATSEQAIJMKL when constructed with a single process communicator, 152 and MATMPIAIJMKL otherwise. As a result, for single process communicators, 153 MatSeqAIJSetPreallocation() is supported, and similarly MatMPIAIJSetPreallocation() is supported 154 for communicators controlling multiple processes. It is recommended that you call both of 155 the above preallocation routines for simplicity. 156 157 Options Database Keys: 158 . -mat_type aijmkl - sets the matrix type to "AIJMKL" during a call to MatSetFromOptions() 159 160 Level: beginner 161 162 .seealso: MatCreateMPIAIJMKL(), MATSEQAIJMKL, MATMPIAIJMKL 163 M*/ 164 165