# hipblasztrmmstridedbatched Interface Reference#

HIPFORT API Reference: hipfort_hipblas::hipblasztrmmstridedbatched Interface Reference
hipfort_hipblas::hipblasztrmmstridedbatched Interface Reference

BLAS Level 3 API. More...

## Public Member Functions

integer(kind(hipblas_status_success)) function hipblasztrmmstridedbatched_ (handle, side, uplo, transA, diag, m, n, alpha, A, lda, strideA, B, ldb, strideB, batchCount)

integer(kind(hipblas_status_success)) function hipblasztrmmstridedbatched_full_rank (handle, side, uplo, transA, diag, m, n, alpha, A, lda, strideA, B, ldb, strideB, batchCount)

integer(kind(hipblas_status_success)) function hipblasztrmmstridedbatched_rank_0 (handle, side, uplo, transA, diag, m, n, alpha, A, lda, strideA, B, ldb, strideB, batchCount)

integer(kind(hipblas_status_success)) function hipblasztrmmstridedbatched_rank_1 (handle, side, uplo, transA, diag, m, n, alpha, A, lda, strideA, B, ldb, strideB, batchCount)

## Detailed Description

BLAS Level 3 API.

trmmStridedBatched performs one of the strided_batched matrix-matrix operations

B_i := alpha*op( A_i )*B_i, or B_i := alpha*B_i*op( A_i ) for i = 0, 1, ... batchCount -1

where alpha is a scalar, B_i is an m by n matrix, A_i is a unit, or non-unit, upper or lower triangular matrix and op( A_i ) is one of

op( A_i ) = A_i   or   op( A_i ) = A_i^T   or   op( A_i ) = A_i^H.

Parameters
 [in] handle [hipblasHandle_t] handle to the hipblas library context queue. [in] side [hipblasSideMode_t] Specifies whether op(A_i) multiplies B_i from the left or right as follows: HIPBLAS_SIDE_LEFT: B_i := alpha*op( A_i )*B_i. HIPBLAS_SIDE_RIGHT: B_i := alpha*B_i*op( A_i ). [in] uplo [hipblasFillMode_t] Specifies whether the matrix A is an upper or lower triangular matrix as follows: HIPBLAS_FILL_MODE_UPPER: A is an upper triangular matrix. HIPBLAS_FILL_MODE_LOWER: A is a lower triangular matrix. [in] transA [hipblasOperation_t] Specifies the form of op(A_i) to be used in the matrix multiplication as follows: HIPBLAS_OP_N: op(A_i) = A_i. HIPBLAS_OP_T: op(A_i) = A_i^T. HIPBLAS_OP_C: op(A_i) = A_i^H. [in] diag [hipblasDiagType_t] Specifies whether or not A_i is unit triangular as follows: HIPBLAS_DIAG_UNIT: A_i is assumed to be unit triangular. HIPBLAS_DIAG_NON_UNIT: A_i is not assumed to be unit triangular. [in] m [int] m specifies the number of rows of B_i. m >= 0. [in] n [int] n specifies the number of columns of B_i. n >= 0. [in] alpha alpha specifies the scalar alpha. When alpha is zero then A_i is not referenced and B_i need not be set before entry. [in] A Device pointer to the first matrix A_0 on the GPU. Each A_i is of dimension ( lda, k ), where k is m when side == HIPBLAS_SIDE_LEFT and is n when side == HIPBLAS_SIDE_RIGHT.

When uplo == HIPBLAS_FILL_MODE_UPPER the leading k by k upper triangular part of the array A must contain the upper triangular matrix and the strictly lower triangular part of A is not referenced.

When uplo == HIPBLAS_FILL_MODE_LOWER the leading k by k lower triangular part of the array A must contain the lower triangular matrix and the strictly upper triangular part of A is not referenced.

Note that when diag == HIPBLAS_DIAG_UNIT the diagonal elements of A_i are not referenced either, but are assumed to be unity.

Parameters
 [in] lda [int] lda specifies the first dimension of A. if side == HIPBLAS_SIDE_LEFT, lda >= max( 1, m ), if side == HIPBLAS_SIDE_RIGHT, lda >= max( 1, n ). [in] strideA [hipblasStride] stride from the start of one matrix (A_i) and the next one (A_i+1) [in,out] B Device pointer to the first matrix B_0 on the GPU. On entry, the leading m by n part of the array B_i must contain the matrix B_i, and on exit is overwritten by the transformed matrix. [in] ldb [int] ldb specifies the first dimension of B_i. ldb >= max( 1, m ). [in] strideB [hipblasStride] stride from the start of one matrix (B_i) and the next one (B_i+1) [in] batchCount [int] number of instances i in the batch.

## ◆ hipblasztrmmstridedbatched_()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrmmstridedbatched::hipblasztrmmstridedbatched_ ( type(c_ptr), value handle, integer(kind(hipblas_side_left)), value side, integer(kind(hipblas_fill_mode_upper)), value uplo, integer(kind(hipblas_op_n)), value transA, integer(kind(hipblas_diag_non_unit)), value diag, integer(c_int), value m, integer(c_int), value n, complex(c_double_complex) alpha, type(c_ptr), value A, integer(c_int), value lda, integer(c_int64_t), value strideA, type(c_ptr), value B, integer(c_int), value ldb, integer(c_int64_t), value strideB, integer(c_int), value batchCount )

## ◆ hipblasztrmmstridedbatched_full_rank()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrmmstridedbatched::hipblasztrmmstridedbatched_full_rank ( type(c_ptr) handle, integer(kind(hipblas_side_left)) side, integer(kind(hipblas_fill_mode_upper)) uplo, integer(kind(hipblas_op_n)) transA, integer(kind(hipblas_diag_non_unit)) diag, integer(c_int) m, integer(c_int) n, complex(c_double_complex) alpha, complex(c_double_complex), dimension(:,:), target A, integer(c_int) lda, integer(c_int64_t) strideA, complex(c_double_complex), dimension(:,:), target B, integer(c_int) ldb, integer(c_int64_t) strideB, integer(c_int) batchCount )

## ◆ hipblasztrmmstridedbatched_rank_0()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrmmstridedbatched::hipblasztrmmstridedbatched_rank_0 ( type(c_ptr) handle, integer(kind(hipblas_side_left)) side, integer(kind(hipblas_fill_mode_upper)) uplo, integer(kind(hipblas_op_n)) transA, integer(kind(hipblas_diag_non_unit)) diag, integer(c_int) m, integer(c_int) n, complex(c_double_complex) alpha, complex(c_double_complex), target A, integer(c_int) lda, integer(c_int64_t) strideA, complex(c_double_complex), target B, integer(c_int) ldb, integer(c_int64_t) strideB, integer(c_int) batchCount )

## ◆ hipblasztrmmstridedbatched_rank_1()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrmmstridedbatched::hipblasztrmmstridedbatched_rank_1 ( type(c_ptr) handle, integer(kind(hipblas_side_left)) side, integer(kind(hipblas_fill_mode_upper)) uplo, integer(kind(hipblas_op_n)) transA, integer(kind(hipblas_diag_non_unit)) diag, integer(c_int) m, integer(c_int) n, complex(c_double_complex) alpha, complex(c_double_complex), dimension(:), target A, integer(c_int) lda, integer(c_int64_t) strideA, complex(c_double_complex), dimension(:), target B, integer(c_int) ldb, integer(c_int64_t) strideB, integer(c_int) batchCount )

The documentation for this interface was generated from the following file: