Developer Reference for Intel® oneAPI Math Kernel Library for Fortran
mkl_sparse_?_convert_dense
Conversion of the source sparse matrix to dense format in adns array.
Syntax
stat = mkl_sparse_s_convert_dense ( source, descr, dense_layout, lda, adns )
stat = mkl_sparse_d_convert_dense ( source, descr, dense_layout, lda, adns )
stat = mkl_sparse_c_convert_dense ( source, descr, dense_layout, lda, adns )
stat = mkl_sparse_z_convert_dense ( source, descr, dense_layout, lda, adns )
Include Files
mkl_spblas.f90
Description
The mkl_sparse_?_convert_dense routine converts a sparse matrix handle to a dense matrix representation and stores the result in the user-provided dense array.
See also mkl_sparse_?_dense2csr , mkl_sparse_?_dense2csc , mkl_sparse_?_dense2coo , and mkl_sparse_?_dense2bsr for the reverse operations (dense to sparse).
Input Parameters
source
SPARSE_MATRIX_T .
Handle containing internal data.
descr
MATRIX_DESCR .
Descriptor specifying sparse matrix properties.
sparse_matrix_type_t type |
Specifies the type of a sparse matrix:
|
sparse_fill_mode_t mode |
Specifies the triangular matrix part for symmetric, Hermitian, triangular, and block-triangular matrices:
|
sparse_diag_type_t diag |
Specifies diagonal type for non-general matrices:
|
dense_layout
C_INT .
Describes the storage scheme for the dense matrix:
SPARSE_LAYOUT_COLUMN_MAJOR |
Storage of elements uses column major layout. |
SPARSE_LAYOUT_ROW_MAJOR |
Storage of elements uses row major layout. |
lda
C_INT .
Leading dimension of the dense matrix. For column-major layout, must be at least rows. For row-major layout, must be at least cols.
Output Parameters
adns
C_FLOAT |
for mkl_sparse_s_convert_dense |
C_DOUBLE |
for mkl_sparse_d_convert_dense |
C_FLOAT_COMPLEX |
for mkl_sparse_c_convert_dense |
C_DOUBLE_COMPLEX |
for mkl_sparse_z_convert_dense |
Array filled with elements of the dense matrix. Must be pre-allocated with size at least lda * cols for column-major layout or lda * rows for row-major layout.
stat
INTEGER
Value indicating whether the operation was successful, and if not, why:
SPARSE_STATUS_SUCCESS |
The operation was successful. |
SPARSE_STATUS_NOT_INITIALIZED |
The routine encountered an empty handle or matrix array. |
SPARSE_STATUS_ALLOC_FAILED |
Internal memory allocation failed. |
SPARSE_STATUS_INVALID_VALUE |
The input parameters contain an invalid value. |
SPARSE_STATUS_EXECUTION_FAILED |
Execution failed. |
SPARSE_STATUS_INTERNAL_ERROR |
An error in algorithm implementation occurred. |
SPARSE_STATUS_NOT_SUPPORTED |
The requested operation is not supported. |
Return Values
See Output Parameter, stat.