rocblas_sgemmt_batched Interface Reference

rocblas_sgemmt_batched Interface Reference#

HIPFORT API Reference: hipfort_rocblas::rocblas_sgemmt_batched Interface Reference

BLAS Level 3 API. More...

Public Member Functions
integer(kind(rocblas_status_success)) function	rocblas_sgemmt_batched_ (handle, uplo, transa, transb, n, k, alpha, a, lda, b, ldb, beta, c, ldc, batch_count)

Detailed Description

BLAS Level 3 API.

The gemmt_batched functions perform matrix-matrix operations and update the upper or lower triangular part of the result matrix:

C_i = alpha*op( A_i )*op( B_i ) + beta*C_i, for i = 1, ..., batch_count,

where op( X ) is one of

op( X ) = X      or
op( X ) = X**T   or
op( X ) = X**H,

alpha and beta are scalars, A and B are general matrices, and C is either an upper or lower triangular matrix, with op( A ) consisting of n by k by batch_count matrices, op( B ) consisting of k by n by batch_count matrices, and C consisting of n by n by batch_count matrices.

Parameters

[in]	handle	- [rocblas_handle handle to the rocBLAS library context queue.
[in]	uplo	- [rocblas_fill] rocblas_fill_upper: C is an upper triangular matrix. rocblas_fill_lower: C is a lower triangular matrix.
[in]	transA	- [rocblas_operation] rocblas_operation_none: op(A_i) = A_i. rocblas_operation_transpose: op(A_i) = A_i^T rocblas_operation_conjugate_transpose: op(A_i) = A_i^H
[in]	transB	- [rocblas_operation] rocblas_operation_none: op(B_i) = B_i. rocblas_operation_transpose: op(B_i) = B_i^T rocblas_operation_conjugate_transpose: op(B_i) = B_i^H
[in]	n	- [rocblas_int] number or rows of matrices op( A_i ), columns of op( B_i ), and (rows, columns) of C_i.
[in]	k	- [rocblas_int] number of rows of matrices op( B_i ) and columns of op( A_i ).
[in]	alpha	- device pointer or host pointer specifying the scalar alpha.
[in]	A	- device array of device pointers storing each matrix A_i. If transa = rocblas_operation_none, then the leading n-by-k part of the array contains each matrix A_i. Otherwise, the leading k-by-n part of the array contains each matrix A_i.
[in]	lda	- [rocblas_int] specifies the leading dimension of each A_i. If transA == rocblas_operation_none, must have lda >= max(1, n). Otherwise, must have lda >= max(1, k).
[in]	B	- device array of device pointers storing each matrix B_i. If transB = rocblas_operation_none, then the leading k-by-n part of the array contains each matrix B_i. Otherwise, the leading n-by-k part of the array contains each matrix B_i.
[in]	ldb	- [rocblas_int] specifies the leading dimension of each B_i. If transB == rocblas_operation_none, must have ldb >= max(1, k). Otherwise, must have ldb >= max(1, n).
[in]	beta	- device pointer or host pointer specifying the scalar beta.
[in,out]	C	- device array of device pointers storing each matrix C_i. If uplo == rocblas_fill_upper, the upper triangular part of the leading n-by-n array contains each matrix C_i. Otherwise, the lower triangular part of the leading n-by-n array contains each matrix C_i.
[in]	ldc	- [rocblas_int] specifies the leading dimension of each C_i. Must have ldc >= max(1, n).
[in]	batch_count	[rocblas_int] number of gemm operations in the batch.

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