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hipblasdsbmvstridedbatched Interface Reference

hipblasdsbmvstridedbatched Interface Reference#

HIPFORT API Reference: hipfort_hipblas::hipblasdsbmvstridedbatched Interface Reference
hipfort_hipblas::hipblasdsbmvstridedbatched Interface Reference

BLAS Level 2 API. More...

Public Member Functions

integer(kind(hipblas_status_success)) function hipblasdsbmvstridedbatched_ (handle, uplo, n, k, alpha, A, lda, strideA, x, incx, stridex, beta, y, incy, stridey, batchCount)
 
integer(kind(hipblas_status_success)) function hipblasdsbmvstridedbatched_full_rank (handle, uplo, n, k, alpha, A, lda, strideA, x, incx, stridex, beta, y, incy, stridey, batchCount)
 
integer(kind(hipblas_status_success)) function hipblasdsbmvstridedbatched_rank_0 (handle, uplo, n, k, alpha, A, lda, strideA, x, incx, stridex, beta, y, incy, stridey, batchCount)
 
integer(kind(hipblas_status_success)) function hipblasdsbmvstridedbatched_rank_1 (handle, uplo, n, k, alpha, A, lda, strideA, x, incx, stridex, beta, y, incy, stridey, batchCount)
 

Detailed Description

BLAS Level 2 API.

sbmvStridedBatched performs the matrix-vector operation:

y_i := alpha*A_i*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 n by n symmetric banded matrix, for i = 1, ..., batchCount. A should contain an upper or lower triangular n by n symmetric banded matrix.

Parameters
[in]handle[hipblasHandle_t] handle to the hipblas library context queue
[in]uplo[hipblasFillMode_t] specifies whether the upper 'HIPBLAS_FILL_MODE_UPPER' or lower 'HIPBLAS_FILL_MODE_LOWER' if HIPBLAS_FILL_MODE_UPPER, the lower part of A is not referenced if HIPBLAS_FILL_MODE_LOWER, the upper part of A is not referenced
[in]n[int] number of rows and columns of each matrix A_i
[in]k[int] specifies the number of sub- and super-diagonals
[in]alphadevice pointer or host pointer to scalar alpha
[in]ADevice pointer to the first matrix A_1 on the GPU
[in]lda[int] specifies the leading dimension of each matrix A_i
[in]strideA[hipblasStride] stride from the start of one matrix (A_i) and the next one (A_i+1)
[in]xDevice pointer to the first vector x_1 on the GPU
[in]incx[int] specifies the increment for the elements of each vector x_i
[in]stridex[hipblasStride] stride from the start of one vector (x_i) and the next one (x_i+1). There are no restrictions placed on stridex, however the user should take care to ensure that stridex is of appropriate size. This typically means stridex >= n * incx. stridex should be non zero.
[in]betadevice pointer or host pointer to scalar beta
[out]yDevice pointer to the first vector y_1 on the GPU
[in]incy[int] specifies the increment for the elements of each vector y_i
[in]stridey[hipblasStride] stride from the start of one vector (y_i) and the next one (y_i+1). There are no restrictions placed on stridey, however the user should take care to ensure that stridey is of appropriate size. This typically means stridey >= n * incy. stridey should be non zero.
[in]batchCount[int] number of instances in the batch

Member Function/Subroutine Documentation

◆ hipblasdsbmvstridedbatched_()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasdsbmvstridedbatched::hipblasdsbmvstridedbatched_ ( type(c_ptr), value  handle,
integer(kind(hipblas_fill_mode_upper)), value  uplo,
integer(c_int), value  n,
integer(c_int), value  k,
real(c_double)  alpha,
type(c_ptr), value  A,
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_double)  beta,
type(c_ptr), value  y,
integer(c_int), value  incy,
integer(c_int64_t), value  stridey,
integer(c_int), value  batchCount 
)

◆ hipblasdsbmvstridedbatched_full_rank()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasdsbmvstridedbatched::hipblasdsbmvstridedbatched_full_rank ( type(c_ptr)  handle,
integer(kind(hipblas_fill_mode_upper))  uplo,
integer(c_int)  n,
integer(c_int)  k,
real(c_double)  alpha,
real(c_double), dimension(:,:), target  A,
integer(c_int)  lda,
integer(c_int64_t)  strideA,
real(c_double), dimension(:), target  x,
integer(c_int)  incx,
integer(c_int64_t)  stridex,
real(c_double)  beta,
real(c_double), dimension(:), target  y,
integer(c_int)  incy,
integer(c_int64_t)  stridey,
integer(c_int)  batchCount 
)

◆ hipblasdsbmvstridedbatched_rank_0()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasdsbmvstridedbatched::hipblasdsbmvstridedbatched_rank_0 ( type(c_ptr)  handle,
integer(kind(hipblas_fill_mode_upper))  uplo,
integer(c_int)  n,
integer(c_int)  k,
real(c_double)  alpha,
real(c_double), target  A,
integer(c_int)  lda,
integer(c_int64_t)  strideA,
real(c_double), target  x,
integer(c_int)  incx,
integer(c_int64_t)  stridex,
real(c_double)  beta,
real(c_double), target  y,
integer(c_int)  incy,
integer(c_int64_t)  stridey,
integer(c_int)  batchCount 
)

◆ hipblasdsbmvstridedbatched_rank_1()

integer(kind(hipblas_status_success)) function hipfort_hipblas::hipblasdsbmvstridedbatched::hipblasdsbmvstridedbatched_rank_1 ( type(c_ptr)  handle,
integer(kind(hipblas_fill_mode_upper))  uplo,
integer(c_int)  n,
integer(c_int)  k,
real(c_double)  alpha,
real(c_double), dimension(:), target  A,
integer(c_int)  lda,
integer(c_int64_t)  strideA,
real(c_double), dimension(:), target  x,
integer(c_int)  incx,
integer(c_int64_t)  stridex,
real(c_double)  beta,
real(c_double), dimension(:), target  y,
integer(c_int)  incy,
integer(c_int64_t)  stridey,
integer(c_int)  batchCount 
)

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