mkl_sparse_sypr

Computes the symmetric product of three sparse matrices and stores the result in a newly allocated sparse matrix.

Syntax

sparse_status_t mkl_sparse_sypr

(

const sparse_operation_t

operation

const

sparse_matrix_t

const

sparse_matrix_t

const struct

matrix_descr

sparse_matrix_t

const sparse_request_t

request

);

Include Files

mkl_spblas.h

Description

The

mkl_sparse_sypr

routine performs a multiplication of three sparse matrices that results in a symmetric or Hermitian matrix, C.

C:=A*B*opA(A)

C:=opA(A)*B*A

depending on the matrix modifier operation.

Here, A, B, and C are sparse matrices, where A has a general structure while B and C are symmetric or Hermitian matrices. opA is the transpose (real precision) or conjugate transpose (complex precision) operator.

This routine is not supported for sparse matrices in COO or CSC formats. This routine supports only CSR and BSR formats. In addition, it supports only the sorted CSR and sorted BSR formats for the input matrix. If the data is unsorted, call the mkl_sparse_order routine before either mkl_sparse_sypr or mkl_sparse_?_syprd.

Input Parameters

operation: Specifies operation on the input sparse matrices.

SPARSE_OPERATION_NON_TRANSPOSE
Non-transpose case.
C:=A*B*(A^T) for real precision
C:=A*B*(A^H) for complex precision.

SPARSE_OPERATION_TRANSPOSE
Transpose case. This is not supported for complex matrices.
C:=(A^T)*B*A

SPARSE_OPERATION_CONJUGATE_TRANSPOSE
Conjugate transpose case. This is not supported for real matrices.
C:=(A^H)*B*A
A: Handle which contains the sparse matrix A.
B: Handle which contains the sparse matrix B.
descrB: Structure specifying properties of the sparse matrix.
sparse_matrix_type_t type specifies the type of a sparse matrix

SPARSE_MATRIX_TYPE_SYMMETRIC
The matrix is symmetric (only the specified triangle is processed).

SPARSE_MATRIX_TYPE_HERMITIAN
The matrix is Hermitian (only the specified triangle is processed).

sparse_fill_mode_t mode specifies the triangular matrix part.

SPARSE_FILL_MODE_LOWER
The lower triangular matrix part is processed.

SPARSE_FILL_MODE_UPPER
The upper triangular matrix part is processed.

sparse_diag_type_t diag specifies the type of diagonal.

SPARSE_DIAG_NON_UNIT
Diagonal elements cannot be equal to one.

This routine also supports C=AA^T,H with these parameters:
descrB.type=SPARSE_MATRIX_TYPE_DIAGONAL
descrB.diag=SPARSE_DIAG_UNIT
In this case, you do not need to allocate structure B. Use the routine as a 2-stage version of mkl_sparse_syrk.
request: Use this routine to specify if the computations should be performed in a single step or using the two-stage algorithm. See Two-stage Algorithm for Inspector-executor Sparse BLAS Routines for more information.

SPARSE_STAGE_NNZ_COUNT
Only rowIndex (BSR/CSR format) or colIndex (CSC format) array of the matrix is computed internally. The computation can be extracted to measure the memory required for full operation.

SPARSE_STAGE_FINALIZE_MULT_NO_VAL
Finalize computations of the matrix structure (values will not be computed). Use only after the call with SPARSE_STAGE_NNZ_COUNT parameter.

SPARSE_STAGE_FINALIZE_MULT
Finalize computation. Can be used after the call with the SPARSE_STAGE_NNZ_COUNT or SPARSE_STAGE_FINALIZE_MULT_NO_VAL. Can also be used when the matrix structure remains unchanged and only values of the resulting matrix C need to be recomputed.

SPARSE_STAGE_FULL_MULT_NO_VAL
Perform computations of the matrix structure.

SPARSE_STAGE_FULL_MULT
Perform the entire computation in a single step.

Output Parameters

C: Handle which contains the resulting sparse matrix. Only the upper-triangular part of the matrix is computed.

Return Values

The function returns a value indicating whether the operation was successful, or the reason why it failed.

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.

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mkl_sparse_sypr

Syntax

Product and Performance Information

`SPARSE_OPERATION_NON_TRANSPOSE`	Non-transpose case. `C`:=`A``B`(A^T) for real precision `C`:=`A``B`(`A`^H) for complex precision.
`SPARSE_OPERATION_TRANSPOSE`	Transpose case. This is not supported for complex matrices. `C`:=(`A`^T)`B``A`
`SPARSE_OPERATION_CONJUGATE_TRANSPOSE`	Conjugate transpose case. This is not supported for real matrices. `C`:=(`A`^H)`B``A`

SPARSE_MATRIX_TYPE_SYMMETRIC	The matrix is symmetric (only the specified triangle is processed).
SPARSE_MATRIX_TYPE_HERMITIAN	The matrix is Hermitian (only the specified triangle is processed).

SPARSE_FILL_MODE_LOWER	The lower triangular matrix part is processed.
SPARSE_FILL_MODE_UPPER	The upper triangular matrix part is processed.

SPARSE_STAGE_NNZ_COUNT	Only `rowIndex` (BSR/CSR format) or `colIndex` (CSC format) array of the matrix is computed internally. The computation can be extracted to measure the memory required for full operation.
SPARSE_STAGE_FINALIZE_MULT_NO_VAL	Finalize computations of the matrix structure (values will not be computed). Use only after the call with SPARSE_STAGE_NNZ_COUNT parameter.
SPARSE_STAGE_FINALIZE_MULT	Finalize computation. Can be used after the call with the SPARSE_STAGE_NNZ_COUNT or SPARSE_STAGE_FINALIZE_MULT_NO_VAL. Can also be used when the matrix structure remains unchanged and only values of the resulting matrix `C` need to be recomputed.
SPARSE_STAGE_FULL_MULT_NO_VAL	Perform computations of the matrix structure.
SPARSE_STAGE_FULL_MULT	Perform the entire computation in a single step.

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mkl_sparse_sypr

Syntax

Product and Performance Information