sygvd

Computes all eigenvalues and, optionally, eigenvectors of a real generalized symmetric definite eigenproblem using a divide and conquer method.

sygvd supports the following precisions.

T
float
double

Description

The routine computes all the eigenvalues, and optionally, the eigenvectors of a real generalized symmetric-definite eigenproblem, of the form

A*x = λ*B*x, A*B*x = λ*x, or B*A*x = λ*x .

Here A and B are assumed to be symmetric and B is also positive definite.

It uses a divide and conquer algorithm.

sygvd (BUFFER Version)

Syntax

void onemkl::lapack::sygvd(cl::sycl::queue &queue, std::int64_t itype, onemkl::job jobz, onemkl::uplo upper_lower, std::int64_t n, cl::sycl::buffer<T, 1> &a, std::int64_t lda, cl::sycl::buffer<T, 1> &b, std::int64_t ldb, cl::sycl::buffer<T, 1> &w, cl::sycl::buffer<T, 1> &scratchpad, std::int64_t scratchpad_size)

Input Parameters

queue

The queue where the routine should be executed.

itype

Must be 1 or 2 or 3. Specifies the problem type to be solved:

if itype= 1, the problem type is A*x = lambda*B*x;

if itype= 2, the problem type is A*B*x = lambda*x;

if itype= 3, the problem type is B*A*x = lambda*x.

jobz

Must be job::novec or job::vec.

If jobz = job::novec, then only eigenvalues are computed.

If jobz = job::vec, then eigenvalues and eigenvectors are computed.

upper_lower

Must be uplo::upper or uplo::lower.

If upper_lower = job::upper, a and b store the upper triangular part of A and B.

If upper_lower = job::lower, a and b stores the lower triangular part of A and B.

n

The order of the matrices A and B(0≤n).

a

Buffer, size a(lda,*) contains the upper or lower triangle of the symmetric matrix A, as specified by upper_lower. The second dimension of a must be at least max(1, n).

lda

The leading dimension of a; at least max(1, n).

b

Buffer, size b(ldb,*) contains the upper or lower triangle of the symmetric matrix B, as specified by upper_lower. The second dimension of b must be at least max(1, n).

ldb

The leading dimension of b; at least max(1, n).

scratchpad_size

Size of scratchpad memory as a number of floating point elements of type T. Size should not be less than the value returned by sygvd_scratchpad_size function.

Output Parameters

a

On exit, if jobz = job::vec, then if info = 0, a contains the matrix Z of eigenvectors. The eigenvectors are normalized as follows:

if itype= 1or 2 , Z^T*B*Z = I;

if itype= 3 , Z^T*inv(B)*Z = I;

If jobz = job::novec, then on exit the upper triangle (if upper_lower = uplo::upper) or the lower triangle (if upper_lower = uplo::lower) of A, including the diagonal, is destroyed.

b

On exit, if info≤n, the part of b containing the matrix is overwritten by the triangular factor U or L from the Cholesky factorization B = U^T*U or B = L*L^T.

w

Buffer, size at least n. If info = 0, contains the eigenvalues of the matrix A in ascending order.

scratchpad

Buffer holding scratchpad memory to be used by routine for storing intermediate results.

Throws

onemkl::lapack::exception

Exception is thrown in case of problems happened during calculations. The info code of the problem can be obtained by get_info() method of exception object:

If info=-i, the i-th parameter had an illegal value.

For info≤n:

If info=i, and jobz = onemkl::job::novec, then the algorithm failed to converge; i indicates the number of off-diagonal elements of an intermediate tridiagonal form which did not converge to zero.

If info=i, and jobz = onemkl::job::vec, then the algorithm failed to compute an eigenvalue while working on the submatrix lying in rows and columns info/(n+1) through mod(info,n+1).

For info>n:

If info=n+i, for 1≤i≤n, then the leading minor of order i of B is not positive-definite. The factorization of B could not be completed and no eigenvalues or eigenvectors were computed.

If info equals to value passed as scratchpad size, and get_detail() returns non zero, then passed scratchpad is of insufficient size, and required size should not be less than value return by get_detail() method of exception object.

sygvd (USM Version)

Syntax

cl::sycl::event onemkl::lapack::sygvd(cl::sycl::queue &queue, std::int64_t itype, onemkl::job jobz, onemkl::uplo upper_lower, std::int64_t n, T *a, std::int64_t lda, T *b, std::int64_t ldb, T *w, T *scratchpad, std::int64_t scratchpad_size, const cl::sycl::vector_class<cl::sycl::event> &events = {})

Input Parameters

queue

The queue where the routine should be executed.

itype

Must be 1 or 2 or 3. Specifies the problem type to be solved:

if itype= 1, the problem type is A*x = lambda*B*x;

if itype= 2, the problem type is A*B*x = lambda*x;

if itype= 3, the problem type is B*A*x = lambda*x.

jobz

Must be job::novec or job::vec.

If jobz = job::novec, then only eigenvalues are computed.

If jobz = job::vec, then eigenvalues and eigenvectors are computed.

upper_lower

Must be uplo::upper or uplo::lower.

If upper_lower = job::upper, a and b store the upper triangular part of A and B.

If upper_lower = job::lower, a and b stores the lower triangular part of A and B.

n

The order of the matrices A and B(0≤n).

a

Pointer to array of size a(lda,*) containing the upper or lower triangle of the symmetric matrix A, as specified by upper_lower. The second dimension of a must be at least max(1, n).

lda

The leading dimension of a; at least max(1, n).

b

Pointer to array of size b(ldb,*) contains the upper or lower triangle of the symmetric matrix B, as specified by upper_lower. The second dimension of b must be at least max(1, n).

ldb

The leading dimension of b; at least max(1, n).

scratchpad_size

Size of scratchpad memory as a number of floating point elements of type T. Size should not be less than the value returned by sygvd_scratchpad_size function.

events

List of events to wait for before starting computation. Defaults to empty list.

Output Parameters

a

On exit, if jobz = job::vec, then if info = 0, a contains the matrix Z of eigenvectors. The eigenvectors are normalized as follows:

if itype= 1or 2 , Z^T*B*Z = I;

if itype= 3 , Z^T*inv(B)*Z = I;

If jobz = job::novec, then on exit the upper triangle (if upper_lower = uplo::upper) or the lower triangle (if upper_lower = uplo::lower) of A, including the diagonal, is destroyed.

b

On exit, if info≤n, the part of b containing the matrix is overwritten by the triangular factor U or L from the Cholesky factorization B = U^T*U or B = L*L^T.

w

Pointer to array of size at least n. If info = 0, contains the eigenvalues of the matrix A in ascending order.

scratchpad

Pointer to scratchpad memory to be used by routine for storing intermediate results.

Throws

onemkl::lapack::exception

Exception is thrown in case of problems happened during calculations. The info code of the problem can be obtained by get_info() method of exception object:

If info=-i, the i-th parameter had an illegal value.

For info≤n:

If info=i, and jobz = onemkl::job::novec, then the algorithm failed to converge; i indicates the number of off-diagonal elements of an intermediate tridiagonal form which did not converge to zero.

If info=i, and jobz = onemkl::job::vec, then the algorithm failed to compute an eigenvalue while working on the submatrix lying in rows and columns info/(n+1) through mod(info,n+1).

For info>n:

If info=n+i, for 1≤i≤n, then the leading minor of order i of B is not positive-definite. The factorization of B could not be completed and no eigenvalues or eigenvectors were computed.

If info equals to value passed as scratchpad size, and get_detail() returns non zero, then passed scratchpad is of insufficient size, and required size should not be less than value return by get_detail() method of exception object.

Return Values

Output event to wait on to ensure computation is complete.

Parent topic: LAPACK Singular Value and Eigenvalue Problem Routines