# hipblasztrsmstridedbatched Interface Reference#

HIPFORT API Reference: hipfort_hipblas::hipblasztrsmstridedbatched Interface Reference
hipfort_hipblas::hipblasztrsmstridedbatched Interface Reference

BLAS Level 3 API. More...

## Public Member Functions

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

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

integer(kind(hipblas_status_success)) function hipblasztrsmstridedbatched_rank_0 (handle, side, uplo, transA, diag, m, n, alpha, A, lda, strideA, B, ldb, strideB, batchCount)

integer(kind(hipblas_status_success)) function hipblasztrsmstridedbatched_rank_1 (handle, side, uplo, transA, diag, m, n, alpha, A, lda, strideA, B, ldb, strideB, batchCount)

## Detailed Description

BLAS Level 3 API.

trsmSridedBatched performs the following strided batched operation:

op(A_i)*X_i = alpha*B_i or  X_i*op(A_i) = alpha*B_i, for i = 1, ..., batchCount.


where alpha is a scalar, X and B are strided batched m by n matrices, A is triangular strided batched matrix and op(A) is one of

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


Each matrix X_i is overwritten on B_i for i = 1, ..., batchCount.

Note about memory allocation: When trsm is launched with a k evenly divisible by the internal block size of 128, and is no larger than 10 of these blocks, the API takes advantage of utilizing pre-allocated memory found in the handle to increase overall performance. This memory can be managed by using the environment variable WORKBUF_TRSM_B_CHNK. When this variable is not set the device memory used for temporary storage will default to 1 MB and may result in chunking, which in turn may reduce performance. Under these circumstances it is recommended that WORKBUF_TRSM_B_CHNK be set to the desired chunk of right hand sides to be used at a time. (where k is m when HIPBLAS_SIDE_LEFT and is n when HIPBLAS_SIDE_RIGHT)

Parameters
 [in] handle [hipblasHandle_t] handle to the hipblas library context queue. [in] side [hipblasSideMode_t] HIPBLAS_SIDE_LEFT: op(A)*X = alpha*B. HIPBLAS_SIDE_RIGHT: X*op(A) = alpha*B. [in] uplo [hipblasFillMode_t] HIPBLAS_FILL_MODE_UPPER: each A_i is an upper triangular matrix. HIPBLAS_FILL_MODE_LOWER: each A_i is a lower triangular matrix. [in] transA [hipblasOperation_t] HIPBLAS_OP_N: op(A) = A. HIPBLAS_OP_T: op(A) = A^T. HIPBLAS_OP_C: op(A) = A^H. [in] diag [hipblasDiagType_t] HIPBLAS_DIAG_UNIT: each A_i is assumed to be unit triangular. HIPBLAS_DIAG_NON_UNIT: each A_i is not assumed to be unit triangular. [in] m [int] m specifies the number of rows of each B_i. m >= 0. [in] n [int] n specifies the number of columns of each B_i. n >= 0. [in] alpha device pointer or host pointer specifying the scalar alpha. When alpha is &zero then A is not referenced and B need not be set before entry. [in] A device pointer pointing to the first matrix A_1. of dimension ( lda, k ), where k is m when HIPBLAS_SIDE_LEFT and is n when HIPBLAS_SIDE_RIGHT only the upper/lower triangular part is accessed. [in] lda [int] lda specifies the first dimension of each A_i. 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 A_i matrix to the next A_(i + 1). [in,out] B device pointer pointing to the first matrix B_1. [in] ldb [int] ldb specifies the first dimension of each B_i. ldb >= max( 1, m ). [in] strideB [hipblasStride] stride from the start of one B_i matrix to the next B_(i + 1). [in] batchCount [int] number of trsm operatons in the batch.

## ◆ hipblasztrsmstridedbatched_()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrsmstridedbatched::hipblasztrsmstridedbatched_ ( 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 )

## ◆ hipblasztrsmstridedbatched_full_rank()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrsmstridedbatched::hipblasztrsmstridedbatched_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 )

## ◆ hipblasztrsmstridedbatched_rank_0()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrsmstridedbatched::hipblasztrsmstridedbatched_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 )

## ◆ hipblasztrsmstridedbatched_rank_1()

 integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasztrsmstridedbatched::hipblasztrsmstridedbatched_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: