# rocsolver_chegvd_strided_batched Interface Reference#

HIPFORT API Reference: hipfort_rocsolver::rocsolver_chegvd_strided_batched Interface Reference
hipfort_rocsolver::rocsolver_chegvd_strided_batched Interface Reference

HEGVD_STRIDED_BATCHED computes the eigenvalues and (optionally) eigenvectors of a batch of complex generalized hermitian-definite eigenproblems. More...

## Public Member Functions

integer(kind(rocblas_status_success)) function rocsolver_chegvd_strided_batched_ (handle, itype, evect, uplo, n, A, lda, strideA, B, ldb, strideB, D, strideD, E, strideE, myInfo, batch_count)

integer(kind(rocblas_status_success)) function rocsolver_chegvd_strided_batched_full_rank (handle, itype, evect, uplo, n, A, lda, strideA, B, ldb, strideB, D, strideD, E, strideE, myInfo, batch_count)

integer(kind(rocblas_status_success)) function rocsolver_chegvd_strided_batched_rank_0 (handle, itype, evect, uplo, n, A, lda, strideA, B, ldb, strideB, D, strideD, E, strideE, myInfo, batch_count)

integer(kind(rocblas_status_success)) function rocsolver_chegvd_strided_batched_rank_1 (handle, itype, evect, uplo, n, A, lda, strideA, B, ldb, strideB, D, strideD, E, strideE, myInfo, batch_count)

## Detailed Description

HEGVD_STRIDED_BATCHED computes the eigenvalues and (optionally) eigenvectors of a batch of complex generalized hermitian-definite eigenproblems.

For each instance in the batch, the problem solved by this function is either of the form

$\begin{array}{cl} A_i X_i = \lambda B_i X_i & \: \text{1st form,}\newline A_i B_i X_i = \lambda X_i & \: \text{2nd form, or}\newline B_i A_i X_i = \lambda X_i & \: \text{3rd form,} \end{array}$

depending on the value of itype. The eigenvectors are computed using a divide-and-conquer algorithm, depending on the value of evect.

When computed, the matrix $$Z_i$$ of eigenvectors is normalized as follows:

$\begin{array}{cl} Z_i^H B_i Z_i=I & \: \text{if 1st or 2nd form, or}\newline Z_i^H B_i^{-1} Z_i=I & \: \text{if 3rd form.} \end{array}$

Parameters
 [in] handle rocblas_handle. [in] itype rocblas_eform. Specifies the form of the generalized eigenproblems. [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 parts of the matrices A_i and B_i are stored. If uplo indicates lower (or upper), then the upper (or lower) parts of A_i and B_i are not used. [in] n rocblas_int. n >= 0. The matrix dimensions. [in,out] A pointer to type. Array on the GPU (the size depends on the value of strideA). On entry, the hermitian matrices A_i. On exit, if evect is original, the normalized matrix Z_i of eigenvectors. If evect is none, then the upper or lower triangular part of the matrices A_i (including the diagonal) are destroyed, depending on the value of uplo. [in] lda rocblas_int. lda >= n. Specifies the leading dimension of A_i. [in] strideA rocblas_stride. Stride from the start of one matrix A_i to the next one A_(i+1). There is no restriction for the value of strideA. Normal use is strideA >= lda*n. [out] B pointer to type. Array on the GPU (the size depends on the value of strideB). On entry, the hermitian positive definite matrices B_i. On exit, the triangular factor of B_i as returned by POTRF_STRIDED_BATCHED. [in] ldb rocblas_int. ldb >= n. Specifies the leading dimension of B_i. [in] strideB rocblas_stride. Stride from the start of one matrix B_i to the next one B_(i+1). There is no restriction for the value of strideB. Normal use is strideB >= ldb*n. [out] D pointer to real type. Array on the GPU (the size depends on the value of strideD). On exit, the eigenvalues in increasing order. [in] strideD rocblas_stride. Stride from the start of one vector D_i to the next one D_(i+1). There is no restriction for the value of strideD. Normal use is strideD >= n. [out] E pointer to real 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_i associated with the ith reduced eigenvalue problem. On exit, if 0 < info[i] <= n, it contains the unconverged off-diagonal elements of T_i (or properly speaking, a tridiagonal matrix equivalent to T_i). The diagonal elements of this matrix are in D_i; those that converged correspond to a subset of the eigenvalues (not necessarily ordered). [in] strideE rocblas_stride. Stride from the start of one vector E_i to the next one E_(i+1). There is no restriction for the value of strideE. Normal use is strideE >= n. [out] info pointer to rocblas_int. Array of batch_count integers on the GPU. If info[i] = 0, successful exit of batch i. If info[i] = j <= n and evect is rocblas_evect_none, j off-diagonal elements of an intermediate tridiagonal form did not converge to zero. If info[i] = j <= n and evect is rocblas_evect_original, the algorithm failed to compute an eigenvalue in the submatrix from [j/(n+1), j/(n+1)] to [j%(n+1), j%(n+1)]. If info[i] = n + j, the leading minor of order j of B_i is not positive definite. [in] batch_count rocblas_int. batch_count >= 0. Number of matrices in the batch.

## ◆ rocsolver_chegvd_strided_batched_()

 integer(kind(rocblas_status_success)) function hipfort_rocsolver::rocsolver_chegvd_strided_batched::rocsolver_chegvd_strided_batched_ ( type(c_ptr), value handle, integer(kind(rocblas_eform_ax)), value itype, integer(kind(rocblas_evect_original)), value evect, integer(kind(rocblas_fill_upper)), value uplo, integer(c_int), value n, 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, type(c_ptr), value D, integer(c_int64_t), value strideD, type(c_ptr), value E, integer(c_int64_t), value strideE, integer(c_int) myInfo, integer(c_int), value batch_count )

## ◆ rocsolver_chegvd_strided_batched_full_rank()

 integer(kind(rocblas_status_success)) function hipfort_rocsolver::rocsolver_chegvd_strided_batched::rocsolver_chegvd_strided_batched_full_rank ( type(c_ptr) handle, integer(kind(rocblas_eform_ax)) itype, integer(kind(rocblas_evect_original)) evect, integer(kind(rocblas_fill_upper)) uplo, integer(c_int) n, complex(c_float_complex), dimension(:,:), target A, integer(c_int) lda, integer(c_int64_t) strideA, complex(c_float_complex), dimension(:,:), target B, integer(c_int) ldb, integer(c_int64_t) strideB, real(c_float), dimension(:), target D, integer(c_int64_t) strideD, real(c_float), dimension(:), target E, integer(c_int64_t) strideE, integer(c_int) myInfo, integer(c_int) batch_count )

## ◆ rocsolver_chegvd_strided_batched_rank_0()

 integer(kind(rocblas_status_success)) function hipfort_rocsolver::rocsolver_chegvd_strided_batched::rocsolver_chegvd_strided_batched_rank_0 ( type(c_ptr) handle, integer(kind(rocblas_eform_ax)) itype, integer(kind(rocblas_evect_original)) evect, integer(kind(rocblas_fill_upper)) uplo, integer(c_int) n, complex(c_float_complex), target A, integer(c_int) lda, integer(c_int64_t) strideA, complex(c_float_complex), target B, integer(c_int) ldb, integer(c_int64_t) strideB, real(c_float), target D, integer(c_int64_t) strideD, real(c_float), target E, integer(c_int64_t) strideE, integer(c_int) myInfo, integer(c_int) batch_count )

## ◆ rocsolver_chegvd_strided_batched_rank_1()

 integer(kind(rocblas_status_success)) function hipfort_rocsolver::rocsolver_chegvd_strided_batched::rocsolver_chegvd_strided_batched_rank_1 ( type(c_ptr) handle, integer(kind(rocblas_eform_ax)) itype, integer(kind(rocblas_evect_original)) evect, integer(kind(rocblas_fill_upper)) uplo, integer(c_int) n, complex(c_float_complex), dimension(:), target A, integer(c_int) lda, integer(c_int64_t) strideA, complex(c_float_complex), dimension(:), target B, integer(c_int) ldb, integer(c_int64_t) strideB, real(c_float), dimension(:), target D, integer(c_int64_t) strideD, real(c_float), dimension(:), target E, integer(c_int64_t) strideE, integer(c_int) myInfo, integer(c_int) batch_count )

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