rocsparse_scsrmm Interface Reference

rocsparse_scsrmm Interface Reference#

HIPFORT API Reference: hipfort_rocsparse::rocsparse_scsrmm Interface Reference

Sparse matrix dense matrix multiplication using the CSR storage format. More...

Public Member Functions
integer(kind(rocsparse_status_success)) function	rocsparse_scsrmm_ (handle, trans_a, trans_b, m, n, k, nnz, alpha, descr, csr_val, csr_row_ptr, csr_col_ind, b, ldb, beta, c, ldc)

integer(kind(rocsparse_status_success)) function	rocsparse_scsrmm_rank_0 (handle, trans_a, trans_b, m, n, k, nnz, alpha, descr, csr_val, csr_row_ptr, csr_col_ind, b, ldb, beta, c, ldc)

integer(kind(rocsparse_status_success)) function	rocsparse_scsrmm_rank_1 (handle, trans_a, trans_b, m, n, k, nnz, alpha, descr, csr_val, csr_row_ptr, csr_col_ind, b, ldb, beta, c, ldc)

integer(kind(rocsparse_status_success)) function	rocsparse_scsrmm_full_rank (handle, trans_a, trans_b, m, n, k, nnz, alpha, descr, csr_val, csr_row_ptr, csr_col_ind, b, ldb, beta, c, ldc)

Detailed Description

Sparse matrix dense matrix multiplication using the CSR storage format.

rocsparse_csrmm multiplies the scalar \(\alpha\) with a sparse \(m \times k\) matrix \(A\), defined in CSR storage format, and the column-oriented dense \(k \times n\) matrix \(B\) and adds the result to the column-oriented dense \(m \times n\) matrix \(C\) that is multiplied by the scalar \(\beta\), such that

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

with

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

and

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

for(i = 0; i < ldc; ++i)
{
    for(j = 0; j < n; ++j)
    {
        C[i][j] = beta * C[i][j];
 
        for(k = csr_row_ptr[i]; k < csr_row_ptr[i + 1]; ++k)
        {
            C[i][j] += alpha * csr_val[k] * B[csr_col_ind[k]][j];
        }
    }
}

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_A	- matrix \(A\) operation type.
[in]	trans_B	- matrix \(B\) operation type.
[in]	m	- number of rows of the sparse CSR matrix \(A\).
[in]	n	- number of columns of the column-oriented dense matrix \(op(B)\) and \(C\).
[in]	k	- number of columns of the sparse CSR matrix \(A\).
[in]	nnz	- number of non-zero entries of the sparse CSR matrix \(A\).
[in]	alpha	- scalar \(\alpha\).
[in]	descr	- descriptor of the sparse CSR matrix \(A\). Currently, only `rocsparse_matrix_type_general` is supported.
[in]	csr_val	- array of `nnz` elements of the sparse CSR matrix \(A\).
[in]	csr_row_ptr	- array of `m+1` elements that point to the start of every row of the sparse CSR matrix \(A\).
[in]	csr_col_ind	- array of `nnz` elements containing the column indices of the sparse CSR matrix \(A\).
[in]	B	- column-oriented dense matrix of dimension \(ldb \times n\) ( \(op(B) == B\)), \(ldb \times k\) otherwise.
[in]	ldb	- leading dimension of \(B\), must be at least \(\max{(1, k)}\) ( \(op(B) == B\)), \(\max{(1, n)}\) otherwise.
[in]	beta	- scalar \(\beta\).
[in,out]	C	- column-oriented dense matrix of dimension \(ldc \times n\).
[in]	ldc	- leading dimension of \(C\), must be at least \(\max{(1, m)}\) ( \(op(A) == A\)), \(\max{(1, k)}\) otherwise.

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`, `k`, `nnz`, `ldb`, or `ldc` is invalid.
rocsparse_status_invalid_pointer	`descr`, `alpha`, `csr_val`, `csr_row_ptr`, `csr_col_ind`, `B`, `beta`, or `C` 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 multiplies a CSR matrix with a column-oriented dense matrix.

Member Function/Subroutine Documentation