Developer Reference for Intel® oneAPI Math Kernel Library - C

Developer Reference

  • 2021.1
  • 12/04/2020
  • Public Content
Contents

mkl_sparse_?_gv

Computes the largest/smallest eigenvalues and corresponding eigenvectors of a generalized eigenvalue problem

Syntax

sparse_status_t
mkl_sparse_s_gv
(
char
*which
,
MKL_INT
*pm
,
sparse_matrix_t
A
,
struct
matrix_descr
descrA
,
sparse_matrix_t
B
,
struct
matrix_descr
descrB
,
MKL_INT
k0
,
MKL_INT
*k
,
float
*E
,
float
*X
,
float
*res
);
sparse_status_t
mkl_sparse_d_gv
(
char
*which
,
MKL_INT
*pm
,
sparse_matrix_t
A
,
struct
matrix_descr
descrA
,
sparse_matrix_t
B
,
struct
matrix_descr
descrB
,
MKL_INT
k0
,
MKL_INT
*k
,
double
*E
,
double
*X
,
double
*res
);
Include Files
  • mkl_solvers_ee.h
Description
The
mkl_sparse_?_gv
 routine computes the largest/smallest eigenvalues and corresponding eigenvectors of a generalized eigenvalue problem.
Ax = lambda Bx
where
A
 is the real symmetric matrix and
B
 is the real symmetric positive definite matrix.
Input Parameters
which
Indicates eigenvalues for which to search:
  • which = 'L'
     indicates the largest eigenvalues.
  • which = 'S'
     indicates the smallest eigenvalues.
pm
Array of size 128. This array is used to pass various parameters to Extended Eigensolver routines. See • Extended Eigensolver Input Parameters for Extremal Eigenvalue Problem for a complete description of the parameters and their default values.
A
Handle containing sparse matrix in internal data structure.
descrA
Structure specifying sparse matrix properties.
sparse_matrix_type_t
type
Specifies the type of a sparse matrix:
  • SPARSE_MATRIX_TYPE_GENERAL
    The matrix is processed as-is.
  • SPARSE_MATRIX_TYPE_SYMMETRIC
    The matrix is symmetric (only the requested triangle is processed).
sparse_fill_mode_t
mode
Specifies the triangular matrix part for symmetric, Hermitian, triangular, and block-triangular matrices:
  • SPARSE_FILL_MODE_LOWER
    The lower triangular matrix part is processed.
  • SPARSE_FILL_MODE_UPPER
    The upper triangular matrix part is processed.
sparse_diag_type_t
diag
Specifies the diagonal type for non-general matrices:
  • SPARSE_DIAG_NON_UNIT
    Diagonal elements might not be equal to one.
  • SPARSE_DIAG_UNIT
    Diagonal elements are equal to one
B
Handle containing sparse matrix in internal data structure.
descrB
Structure specifying sparse matrix properties.
sparse_matrix_type_t
type
Specifies the type of a sparse matrix:
  • SPARSE_MATRIX_TYPE_GENERAL
    The matrix is processed as-is.
  • SPARSE_MATRIX_TYPE_SYMMETRIC
    The matrix is symmetric (only the requested triangle is processed).
sparse_fill_mode_t
mode
Specifies the triangular matrix part for symmetric, Hermitian, triangular, and block-triangular matrices:
  • SPARSE_FILL_MODE_LOWER
    The lower triangular matrix part is processed.
  • SPARSE_FILL_MODE_UPPER
    The upper triangular matrix part is processed.
sparse_diag_type_t
diag
Specifies the diagonal type for non-general matrices:
  • SPARSE_DIAG_NON_UNIT
    Diagonal elements might not be equal to one.
  • SPARSE_DIAG_UNIT
    Diagonal elements are equal to one
k0
The desired number of the largest/smallest eigenvalues to find.
Output Parameters
k
Number of eigenvalues found.
E
Array of size
k0
. Contains
k
 largest/smallest eigenvalues.
X
Array of size
k0
*Number of columns of matrix A. Contains
k
 eigenvectors.
Res
Array of size
k0
. Contains
k
 residuals.
Return Values
The function returns a value indicating whether the operation was successful or not, and why.
SPARSE_STATUS_SUCCESS
The operation was successful.
SPARSE_STATUS_NOT_INITIALIZED
The routine encountered an empty handle or matrix array.
SPARSE_STATUS_ALLOC_FAILED
Internal memory allocation failed.
SPARSE_STATUS_INVALID_VALUE
The input parameters contain an invalid value.
SPARSE_STATUS_EXECUTION_FAILED
Execution failed.
SPARSE_STATUS_INTERNAL_ERROR
An error in algorithm implementation occurred.
SPARSE_STATUS_NOT_SUPPORTED
The requested operation is not supported.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.