rocsolver_ssyevd_batched Interface Reference

rocsolver_ssyevd_batched Interface Reference#

HIPFORT API Reference: hipfort_rocsolver::rocsolver_ssyevd_batched Interface Reference

SYEVD_BATCHED computes the eigenvalues and optionally the eigenvectors of a batch of real symmetric matrices A_j. More...

Public Member Functions
integer(kind(rocblas_status_success)) function	rocsolver_ssyevd_batched_ (handle, evect, uplo, n, A, lda, D, strideD, E, strideE, myInfo, batch_count)

integer(kind(rocblas_status_success)) function	rocsolver_ssyevd_batched_full_rank (handle, evect, uplo, n, A, lda, D, strideD, E, strideE, myInfo, batch_count)

integer(kind(rocblas_status_success)) function	rocsolver_ssyevd_batched_rank_0 (handle, evect, uplo, n, A, lda, D, strideD, E, strideE, myInfo, batch_count)

integer(kind(rocblas_status_success)) function	rocsolver_ssyevd_batched_rank_1 (handle, evect, uplo, n, A, lda, D, strideD, E, strideE, myInfo, batch_count)

Detailed Description

SYEVD_BATCHED computes the eigenvalues and optionally the eigenvectors of a batch of real symmetric matrices A_j.

The eigenvalues are returned in ascending order. The eigenvectors are computed using a divide-and-conquer algorithm, depending on the value of evect. The computed eigenvectors are orthonormal.

Parameters

[in]	handle	rocblas_handle.
[in]	evect	rocblas_evect. Specifies whether the eigenvectors are to be computed. If evect is rocblas_evect_original, then the eigenvectors are computed. rocblas_evect_tridiagonal is not supported.
[in]	uplo	rocblas_fill. Specifies whether the upper or lower part of the symmetric matrices A_j is stored. If uplo indicates lower (or upper), then the upper (or lower) part of A_j is not used.
[in]	n	rocblas_int. n >= 0. Number of rows and columns of matrices A_j.
[in,out]	A	Array of pointers to type. Each pointer points to an array on the GPU of dimension lda*n. On entry, the matrices A_j. On exit, the eigenvectors of A_j if they were computed and the algorithm converged; otherwise the contents of A_j are destroyed.
[in]	lda	rocblas_int. lda >= n. Specifies the leading dimension of matrices A_j.
[out]	D	pointer to type. Array on the GPU (the size depends on the value of strideD). The eigenvalues of A_j in increasing order.
[in]	strideD	rocblas_stride. Stride from the start of one vector D_j to the next one D_(j+1). There is no restriction for the value of strideD. Normal use case is strideD >= n.
[out]	E	pointer to type. Array on the GPU (the size depends on the value of strideE). This array is used to work internally with the tridiagonal matrix T_j associated with A_j. On exit, if info[j] > 0, E_j contains the unconverged off-diagonal elements of T_j (or properly speaking, a tridiagonal matrix equivalent to T_j). The diagonal elements of this matrix are in D_j; those that converged correspond to a subset of the eigenvalues of A_j (not necessarily ordered).
[in]	strideE	rocblas_stride. Stride from the start of one vector E_j to the next one E_(j+1). There is no restriction for the value of strideE. Normal use case is strideE >= n.
[out]	info	pointer to rocblas_int. Array of batch_count integers on the GPU. If info[j] = 0, successful exit for matrix A_j. If info[j] = i > 0 and evect is rocblas_evect_none, the algorithm did not converge. i elements of E_j did not converge to zero. If info[j] = i > 0 and evect is rocblas_evect_original, the algorithm failed to compute an eigenvalue in the submatrix from [i/(n+1), i/(n+1)] to [i%(n+1), i%(n+1)].
[in]	batch_count	rocblas_int. batch_count >= 0. Number of matrices in the batch.

Member Function/Subroutine Documentation