aoclsparse_?syprd() - aoclsparse_?syprd() - 5.3 English - 68552

AOCL API Guide (68552)
Document_ID
68552
Release_Date
2026-05-13
Version
5.3 English
aoclsparse_status aoclsparse_ssyprd(const aoclsparse_operation op, const aoclsparse_matrix A, const float *B, const aoclsparse_order orderB, const aoclsparse_int ldb, const float alpha, const float beta, float *C, const aoclsparse_order orderC, const aoclsparse_int ldc)#
aoclsparse_status aoclsparse_dsyprd(const aoclsparse_operation op, const aoclsparse_matrix A, const double *B, const aoclsparse_order orderB, const aoclsparse_int ldb, const double alpha, const double beta, double *C, const aoclsparse_order orderC, const aoclsparse_int ldc)#
aoclsparse_status aoclsparse_csyprd(const aoclsparse_operation op, const aoclsparse_matrix A, const aoclsparse_float_complex *B, const aoclsparse_order orderB, const aoclsparse_int ldb, const aoclsparse_float_complex alpha, const aoclsparse_float_complex beta, aoclsparse_float_complex *C, const aoclsparse_order orderC, const aoclsparse_int ldc)#
aoclsparse_status aoclsparse_zsyprd(const aoclsparse_operation op, const aoclsparse_matrix A, const aoclsparse_double_complex *B, const aoclsparse_order orderB, const aoclsparse_int ldb, const aoclsparse_double_complex alpha, const aoclsparse_double_complex beta, aoclsparse_double_complex *C, const aoclsparse_order orderC, const aoclsparse_int ldc)#

Performs symmetric triple product of a sparse matrix and a dense matrix and stores the output as a dense matrix.

aoclsparse_?syprd performs product of a scalar \(\alpha\), with the symmetric triple product of a sparse \(m \times k\) matrix \(A\), defined in CSR or CSC format, with a \(k \times k\) symmetric dense (or Hermitian) matrix \(B\), and a \(k \times m\) \(op(A)\). Adds the resulting matrix to \(m \times m\) symmetric dense (or Hermitian) matrix \(C\) that is multiplied by a scalar \(\beta\), such that

\[ C := \alpha \cdot A \cdot B \cdot op(A) + \beta \cdot C \]
if \(op\) is aoclsparse_operation_none.

Otherwise,

\[ C := \alpha \cdot op(A) \cdot B \cdot A + \beta \cdot C \]

\[\begin{split} op(A) = \left\{ \begin{array}{ll} A^T, & \text{if } {\bf\mathsf{op}} = \text{aoclsparse}\_\text{operation}\_\text{transpose} \text{ (real matrices)}\\ A^H, & \text{if } {\bf\mathsf{op}} = \text{aoclsparse}\_\text{operation}\_\text{conjugate}\_\text{transpose} \text{ (complex matrices)} \end{array} \right. \end{split}\]

Notes

1. This routine assumes the dense matrices (B and C) are stored in full although the computations happen on the upper triangular portion of the matrices.

2. aoclsparse_operation_transpose is only supported for real matrices.

3. aoclsparse_operation_conjugate_transpose is only supported for complex matrices.

4. Complex dense matrices are assumed to be Hermitian matrices.

5. Both CSR and CSC storage formats are accepted. For CSC input, the stored data is interpreted as \(A^T\); the operation is remapped internally so the result is mathematically identical to the CSR path.

Parameters:

  • op – [in] Matrix \(A\) operation type.

  • A – [in] Sparse CSR or CSC matrix \(A\) structure.

  • B – [in] Array of dimension \(ldb \times ldb\). Only the upper triangular matrix is used for computation.

  • orderB – [in] aoclsparse_order_row or aoclsparse_order_column for dense matrix B.

  • ldb – [in] Leading dimension of \(B\), must be at least \(\max{(1, k)}\) ( \(op(A) = A\)) or \(\max{(1, m)}\) ( \(op(A) = A^T\) or \(op(A) = A^H\)).

  • alpha – [in] Scalar \(\alpha\).

  • beta – [in] Scalar \(\beta\).

  • C – [inout] Array of dimension \(ldc \times ldc\). Only upper triangular part of the matrix is processed.

  • orderC – [in] aoclsparse_order_row or aoclsparse_order_column for dense matrix C.

  • ldc – [in] Leading dimension of \(C\), must be at least \(\max{(1, m)}\) ( \(op(A) = A\)) or \(\max{(1, k)}\) ( \(op(A) = A^T\) or \(op(A) = A^H\)).

Return values:

  • aoclsparse_status_success – The operation completed successfully.

  • aoclsparse_status_invalid_operation – The operation is invalid if the matrix B and C has a different layout ordering.

  • aoclsparse_status_wrong_type – The data type of the matrices are not matching or invalid.

  • aoclsparse_status_invalid_size – The value of m, k, ldb or ldc is invalid.

  • aoclsparse_status_invalid_pointer – The pointer A, B, or C is invalid.

  • aoclsparse_status_not_implemented – The input matrix A is not CSR or CSC , or op is aoclsparse_operation_transpose and A has complex values.

  • aoclsparse_status_memory_error – Memory allocation failure.