hipblassgemvstridedbatched Interface Reference

• hipfort_hipblas
• hipblassgemvstridedbatched

Public Member Functions | List of all members

hipfort_hipblas::hipblassgemvstridedbatched Interface Reference

BLAS Level 2 API. More...

Public Member Functions
integer(kind(hipblas_status_success)) function	hipblassgemvstridedbatched_ (handle, transa, m, n, alpha, ap, lda, stridea, x, incx, stridex, beta, y, incy, stridey, batchcount)
integer(kind(hipblas_status_success)) function	hipblassgemvstridedbatched_rank_0 (handle, transa, m, n, alpha, ap, lda, stridea, x, incx, stridex, beta, y, incy, stridey, batchcount)
integer(kind(hipblas_status_success)) function	hipblassgemvstridedbatched_rank_1 (handle, transa, m, n, alpha, ap, lda, stridea, x, incx, stridex, beta, y, incy, stridey, batchcount)
integer(kind(hipblas_status_success)) function	hipblassgemvstridedbatched_full_rank (handle, transa, m, n, alpha, ap, lda, stridea, x, incx, stridex, beta, y, incy, stridey, batchcount)

Detailed Description

BLAS Level 2 API.

The gemvStridedBatched functions perform a batch of matrix-vector operations:

y_i := alpha*A_i*x_i    + beta*y_i,   or
y_i := alpha*A_i**T*x_i + beta*y_i,   or
y_i := alpha*A_i**H*x_i + beta*y_i,

where (A_i, x_i, y_i) is the i-th instance of the batch, alpha and beta are scalars, x_i and y_i are vectors, and A_i is an m by n matrix, for i = 1, ..., batchCount.

• Supported precisions in rocBLAS : s, d, c, and z.
• Supported precisions in cuBLAS : No support.

Parameters

[in]	handle	- [hipblasHandle_t] handle to the hipBLAS library context queue.
[in]	transA	- [hipblasOperation_t] indicates whether matrices A_i are tranposed (conjugated) or not.
[in]	m	- [int] number of rows of matrices A_i.
[in]	n	- [int] number of columns of matrices A_i.
[in]	alpha	- device pointer or host pointer to scalar alpha.
[in]	AP	- device pointer to the first matrix (A_1) in the batch.
[in]	lda	- [int] specifies the leading dimension of matrices A_i.
[in]	strideA	- [hipblasStride] stride from the start of one matrix (A_i) to the next one (A_i+1).
[in]	x	- device pointer to the first vector (x_1) in the batch.
[in]	incx	- [int] specifies the increment for the elements of vectors x_i.
[in]	stridex	- [hipblasStride] stride from the start of one vector (x_i) to the next one (x_i+1). There are no restrictions placed on stridex. However, the user should ensure that stridex is of an appropriate size. When trans equals HIPBLAS_OP_N, this typically means stridex >= n * incx. Otherwise, stridex >= m * incx.
[in]	beta	- device pointer or host pointer to scalar beta.
[in,out]	y	- device pointer to the first vector (y_1) in the batch.
[in]	incy	- [int] specifies the increment for the elements of vectors y_i.
[in]	stridey	- [hipblasStride] stride from the start of one vector (y_i) to the next one (y_i+1). There are no restrictions placed on stridey. However, the user should ensure that stridey is of an appropriate size. When trans equals HIPBLAS_OP_N, this typically means stridey >= m * incy. Otherwise, stridey >= n * incy. stridey should be non zero.
[in]	batchCount	- [int] number of instances in the batch.

Member Function/Subroutine Documentation

◆ hipblassgemvstridedbatched_()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblassgemvstridedbatched::hipblassgemvstridedbatched_	(	type(c_ptr), value	handle,
		integer(kind(hipblas_op_n)), value	transa,
		integer(c_int), value	m,
		integer(c_int), value	n,
		real(c_float)	alpha,
		type(c_ptr), value	ap,
		integer(c_int), value	lda,
		integer(c_int64_t), value	stridea,
		type(c_ptr), value	x,
		integer(c_int), value	incx,
		integer(c_int64_t), value	stridex,
		real(c_float)	beta,
		type(c_ptr), value	y,
		integer(c_int), value	incy,
		integer(c_int64_t), value	stridey,
		integer(c_int), value	batchcount
	)

◆ hipblassgemvstridedbatched_full_rank()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblassgemvstridedbatched::hipblassgemvstridedbatched_full_rank	(	type(c_ptr)	handle,
		integer(kind(hipblas_op_n))	transa,
		integer(c_int)	m,
		integer(c_int)	n,
		real(c_float)	alpha,
		real(c_float), dimension(:,:), target	ap,
		integer(c_int)	lda,
		integer(c_int64_t)	stridea,
		real(c_float), dimension(:), target	x,
		integer(c_int)	incx,
		integer(c_int64_t)	stridex,
		real(c_float)	beta,
		real(c_float), dimension(:), target	y,
		integer(c_int)	incy,
		integer(c_int64_t)	stridey,
		integer(c_int)	batchcount
	)

◆ hipblassgemvstridedbatched_rank_0()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblassgemvstridedbatched::hipblassgemvstridedbatched_rank_0	(	type(c_ptr)	handle,
		integer(kind(hipblas_op_n))	transa,
		integer(c_int)	m,
		integer(c_int)	n,
		real(c_float)	alpha,
		real(c_float), target	ap,
		integer(c_int)	lda,
		integer(c_int64_t)	stridea,
		real(c_float), target	x,
		integer(c_int)	incx,
		integer(c_int64_t)	stridex,
		real(c_float)	beta,
		real(c_float), target	y,
		integer(c_int)	incy,
		integer(c_int64_t)	stridey,
		integer(c_int)	batchcount
	)

◆ hipblassgemvstridedbatched_rank_1()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblassgemvstridedbatched::hipblassgemvstridedbatched_rank_1	(	type(c_ptr)	handle,
		integer(kind(hipblas_op_n))	transa,
		integer(c_int)	m,
		integer(c_int)	n,
		real(c_float)	alpha,
		real(c_float), dimension(:), target	ap,
		integer(c_int)	lda,
		integer(c_int64_t)	stridea,
		real(c_float), dimension(:), target	x,
		integer(c_int)	incx,
		integer(c_int64_t)	stridex,
		real(c_float)	beta,
		real(c_float), dimension(:), target	y,
		integer(c_int)	incy,
		integer(c_int64_t)	stridey,
		integer(c_int)	batchcount
	)

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

• hipfort_hipblas.F90