rocsparse_scoomv Interface Reference

rocsparse_scoomv Interface Reference#

HIPFORT API Reference: hipfort_rocsparse::rocsparse_scoomv Interface Reference

Sparse matrix vector multiplication using the COO storage format. More...

Public Member Functions
integer(kind(rocsparse_status_success)) function	rocsparse_scoomv_ (handle, trans, m, n, nnz, alpha, descr, coo_val, coo_row_ind, coo_col_ind, x, beta, y)

integer(kind(rocsparse_status_success)) function	rocsparse_scoomv_rank_0 (handle, trans, m, n, nnz, alpha, descr, coo_val, coo_row_ind, coo_col_ind, x, beta, y)

integer(kind(rocsparse_status_success)) function	rocsparse_scoomv_rank_1 (handle, trans, m, n, nnz, alpha, descr, coo_val, coo_row_ind, coo_col_ind, x, beta, y)

Detailed Description

Sparse matrix vector multiplication using the COO storage format.

rocsparse_coomv multiplies the scalar \(\alpha\) with a sparse \(m \times n\) matrix, defined in COO storage format, and the dense vector \(x\) and adds the result to the dense vector \(y\) that is multiplied by the scalar \(\beta\), such that

\[ y := \alpha \cdot op(A) \cdot x + \beta \cdot y, \]

with

\[ op(A) = \left\{ \begin{array}{ll} A, & \text{if trans == rocsparse_operation_none} \\% A^T, & \text{if trans == rocsparse_operation_transpose} \\% A^H, & \text{if trans == rocsparse_operation_conjugate_transpose} \end{array} \right. \]

The COO matrix has to be sorted by row indices. This can be achieved by using rocsparse_coosort_by_row().

for(i = 0; i < m; ++i)
{
    y[i] = beta * y[i];
}
 
for(i = 0; i < nnz; ++i)
{
    y[coo_row_ind[i]] += alpha * coo_val[i] * x[coo_col_ind[i]];
}

Note: This function does not produce deterministic results when A is transposed.; This function is non-blocking and executed asynchronously with respect to the host. It can return before the actual computation has finished.; This routine supports execution in a hipGraph context.

Parameters

[in]	handle	- handle to the rocSPARSE library context queue.
[in]	trans	- matrix operation type.
[in]	m	- number of rows of the sparse COO matrix.
[in]	n	- number of columns of the sparse COO matrix.
[in]	nnz	- number of non-zero entries of the sparse COO matrix.
[in]	alpha	- scalar \(\alpha\).
[in]	descr	- descriptor of the sparse COO matrix. Currently, only `rocsparse_matrix_type_general` is supported.
[in]	coo_val	- array of `nnz` elements of the sparse COO matrix.
[in]	coo_row_ind	- array of `nnz` elements containing the row indices of the sparse COO matrix.
[in]	coo_col_ind	- array of `nnz` elements containing the column indices of the sparse COO matrix.
[in]	x	- array of `n` elements ( \(op(A) = A\)) or `m` elements ( \(op(A) = A^T\) or \(op(A) = A^H\)).
[in]	beta	- scalar \(\beta\).
[in,out]	y	- array of `m` elements ( \(op(A) = A\)) or `n` elements ( \(op(A) = A^T\) or \(op(A) = A^H\)).

Return values

rocsparse_status_success	the operation completed successfully.
rocsparse_status_invalid_handle	the library context was not initialized.
rocsparse_status_invalid_size	`m`, `n`, or `nnz` is invalid.
rocsparse_status_invalid_pointer	`descr`, `alpha`, `coo_val`, `coo_row_ind`, `coo_col_ind`, `x`, `beta`, or `y` pointer is invalid.
rocsparse_status_arch_mismatch	the device is not supported.
rocsparse_status_not_implemented	`rocsparse_matrix_type` != `rocsparse_matrix_type_general`.

Example: This example performs a sparse matrix vector multiplication in COO format.

Member Function/Subroutine Documentation