elpa_generated_legacy.h File Reference

#include <complex.h>

Go to the source code of this file.

Functions
int	elpa_solve_evp_real_double (int na, int nev, double *a, int lda, double *ev, double *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_REAL_ELPA_KERNEL_API, int useQR, int useGPU, char *method)
	C interface to driver function "elpa_solve_evp_real_double". More...
int	elpa_solve_evp_real_single (int na, int nev, float *a, int lda, float *ev, float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_REAL_ELPA_KERNEL_API, int useQR, int useGPU, char *method)
	C interface to driver function "elpa_solve_evp_real_single". More...
int	elpa_solve_evp_complex_double (int na, int nev, double complex *a, int lda, double *ev, double complex *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_COMPLEX_ELPA_KERNEL_API, int useGPU, char *method)
	C interface to driver function "elpa_solve_evp_complex_double". More...
int	elpa_solve_evp_complex_single (int na, int nev, complex float *a, int lda, float *ev, complex float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_COMPLEX_ELPA_KERNEL_API, int useGPU, char *method)
	C interface to driver function "elpa_solve_evp_complex_single". More...
int	elpa_get_communicators (int mpi_comm_world, int my_prow, int my_pcol, int *mpi_comm_rows, int *mpi_comm_cols)
	C interface to create ELPA communicators. More...
int	elpa_solve_evp_real_1stage_double_precision (int na, int nev, double *a, int lda, double *ev, double *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int useGPU)
	C interface to solve the double-precision real eigenvalue problem with 1-stage solver. More...
int	elpa_solve_evp_real_1stage_single_precision (int na, int nev, float *a, int lda, float *ev, float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int useGPU)
	C interface to solve the single-precision real eigenvalue problem with 1-stage solver. More...
int	elpa_solve_evp_complex_1stage_double_precision (int na, int nev, double complex *a, int lda, double *ev, double complex *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int useGPU)
	C interface to solve the double-precision complex eigenvalue problem with 1-stage solver. More...
int	elpa_solve_evp_complex_1stage_single_precision (int na, int nev, complex float *a, int lda, float *ev, complex float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int useGPU)
	C interface to solve the single-precision complex eigenvalue problem with 1-stage solver. More...
int	elpa_solve_tridi_double (int na, int nev, double *d, double *e, double *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_solve_tridi_single (int na, int nev, float *d, float *e, float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_mult_at_b_real_double (char uplo_a, char uplo_c, int na, int ncb, double *a, int lda, int ldaCols, double *b, int ldb, int ldbCols, int nlbk, int mpi_comm_rows, int mpi_comm_cols, double *c, int ldc, int ldcCols)
int	elpa_mult_at_b_real_single (char uplo_a, char uplo_c, int na, int ncb, float *a, int lda, int ldaCols, float *b, int ldb, int ldbCols, int nlbk, int mpi_comm_rows, int mpi_comm_cols, float *c, int ldc, int ldcCols)
int	elpa_mult_ah_b_complex_double (char uplo_a, char uplo_c, int na, int ncb, double complex *a, int lda, int ldaCols, double complex *b, int ldb, int ldbCols, int nblk, int mpi_comm_rows, int mpi_comm_cols, double complex *c, int ldc, int ldcCols)
int	elpa_mult_ah_b_complex_single (char uplo_a, char uplo_c, int na, int ncb, complex float *a, int lda, int ldaCols, complex float *b, int ldb, int ldbCols, int nblk, int mpi_comm_rows, int mpi_comm_cols, complex float *c, int ldc, int ldcCols)
int	elpa_invert_trm_real_double (int na, double *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_invert_trm_real_single (int na, float *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_invert_trm_complex_double (int na, double complex *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_invert_trm_complex_single (int na, complex float *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_cholesky_real_double (int na, double *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_cholesky_real_single (int na, float *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_cholesky_complex_double (int na, double complex *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_cholesky_complex_single (int na, complex float *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug)
int	elpa_solve_evp_real_2stage_double_precision (int na, int nev, double *a, int lda, double *ev, double *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_REAL_ELPA_KERNEL_API, int useQR, int useGPU)
	C interface to solve the double-precision real eigenvalue problem with 2-stage solver. More...
int	elpa_solve_evp_real_2stage_single_precision (int na, int nev, float *a, int lda, float *ev, float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_REAL_ELPA_KERNEL_API, int useQR, int useGPU)
	C interface to solve the single-precision real eigenvalue problem with 2-stage solver. More...
int	elpa_solve_evp_complex_2stage_double_precision (int na, int nev, double complex *a, int lda, double *ev, double complex *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_COMPLEX_ELPA_KERNEL_API, int useGPU)
	C interface to solve the double-precision complex eigenvalue problem with 2-stage solver. More...
int	elpa_solve_evp_complex_2stage_single_precision (int na, int nev, complex float *a, int lda, float *ev, complex float *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int THIS_COMPLEX_ELPA_KERNEL_API, int useGPU)
	C interface to solve the single-precision complex eigenvalue problem with 2-stage solver. More...

Function Documentation

elpa_cholesky_complex_double()

int elpa_cholesky_complex_double	(	int	na,
		double complex *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_cholesky_complex_single()

int elpa_cholesky_complex_single	(	int	na,
		complex float *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_cholesky_real_double()

int elpa_cholesky_real_double	(	int	na,
		double *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_cholesky_real_single()

int elpa_cholesky_real_single	(	int	na,
		float *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_get_communicators()

int elpa_get_communicators	(	int	mpi_comm_world,
		int	my_prow,
		int	my_pcol,
		int *	mpi_comm_rows,
		int *	mpi_comm_cols
	)

C interface to create ELPA communicators.

Parameters

mpi_comm_word	MPI global communicator (in)
my_prow	Row coordinate of the calling process in the process grid (in)
my_pcol	Column coordinate of the calling process in the process grid (in)
mpi_comm_rows	Communicator for communicating within rows of processes (out)

Returns

int integer error value of mpi_comm_split function

elpa_invert_trm_complex_double()

int elpa_invert_trm_complex_double	(	int	na,
		double complex *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_invert_trm_complex_single()

int elpa_invert_trm_complex_single	(	int	na,
		complex float *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_invert_trm_real_double()

int elpa_invert_trm_real_double	(	int	na,
		double *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_invert_trm_real_single()

int elpa_invert_trm_real_single	(	int	na,
		float *	a,
		int	lda,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_mult_ah_b_complex_double()

int elpa_mult_ah_b_complex_double	(	char	uplo_a,
		char	uplo_c,
		int	na,
		int	ncb,
		double complex *	a,
		int	lda,
		int	ldaCols,
		double complex *	b,
		int	ldb,
		int	ldbCols,
		int	nblk,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		double complex *	c,
		int	ldc,
		int	ldcCols
	)

elpa_mult_ah_b_complex_single()

int elpa_mult_ah_b_complex_single	(	char	uplo_a,
		char	uplo_c,
		int	na,
		int	ncb,
		complex float *	a,
		int	lda,
		int	ldaCols,
		complex float *	b,
		int	ldb,
		int	ldbCols,
		int	nblk,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		complex float *	c,
		int	ldc,
		int	ldcCols
	)

elpa_mult_at_b_real_double()

int elpa_mult_at_b_real_double	(	char	uplo_a,
		char	uplo_c,
		int	na,
		int	ncb,
		double *	a,
		int	lda,
		int	ldaCols,
		double *	b,
		int	ldb,
		int	ldbCols,
		int	nlbk,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		double *	c,
		int	ldc,
		int	ldcCols
	)

elpa_mult_at_b_real_single()

int elpa_mult_at_b_real_single	(	char	uplo_a,
		char	uplo_c,
		int	na,
		int	ncb,
		float *	a,
		int	lda,
		int	ldaCols,
		float *	b,
		int	ldb,
		int	ldbCols,
		int	nlbk,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		float *	c,
		int	ldc,
		int	ldcCols
	)

elpa_solve_evp_complex_1stage_double_precision()

int elpa_solve_evp_complex_1stage_double_precision	(	int	na,
		int	nev,
		double complex *	a,
		int	lda,
		double *	ev,
		double complex *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	useGPU
	)

C interface to solve the double-precision complex eigenvalue problem with 1-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_complex_1stage_single_precision()

int elpa_solve_evp_complex_1stage_single_precision	(	int	na,
		int	nev,
		complex float *	a,
		int	lda,
		float *	ev,
		complex float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	useGPU
	)

C interface to solve the single-precision complex eigenvalue problem with 1-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_complex_2stage_double_precision()

int elpa_solve_evp_complex_2stage_double_precision	(	int	na,
		int	nev,
		double complex *	a,
		int	lda,
		double *	ev,
		double complex *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_COMPLEX_ELPA_KERNEL_API,
		int	useGPU
	)

C interface to solve the double-precision complex eigenvalue problem with 2-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_COMPLEX_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_complex_2stage_single_precision()

int elpa_solve_evp_complex_2stage_single_precision	(	int	na,
		int	nev,
		complex float *	a,
		int	lda,
		float *	ev,
		complex float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_COMPLEX_ELPA_KERNEL_API,
		int	useGPU
	)

C interface to solve the single-precision complex eigenvalue problem with 2-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_REAL_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_complex_double()

int elpa_solve_evp_complex_double	(	int	na,
		int	nev,
		double complex *	a,
		int	lda,
		double *	ev,
		double complex *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_COMPLEX_ELPA_KERNEL_API,
		int	useGPU,
		char *	method
	)

C interface to driver function "elpa_solve_evp_complex_double".

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_COMPLEX_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useGPU	use GPU (1=yes, 0=No)
method	choose whether to use ELPA 1stage or 2stage solver possible values: "1stage" => use ELPA 1stage solver "2stage" => use ELPA 2stage solver "auto" => (at the moment) use ELPA 2stage solver

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_complex_single()

int elpa_solve_evp_complex_single	(	int	na,
		int	nev,
		complex float *	a,
		int	lda,
		float *	ev,
		complex float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_COMPLEX_ELPA_KERNEL_API,
		int	useGPU,
		char *	method
	)

C interface to driver function "elpa_solve_evp_complex_single".

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_COMPLEX_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useGPU	use GPU (1=yes, 0=No)
method	choose whether to use ELPA 1stage or 2stage solver possible values: "1stage" => use ELPA 1stage solver "2stage" => use ELPA 2stage solver "auto" => (at the moment) use ELPA 2stage solver

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_real_1stage_double_precision()

int elpa_solve_evp_real_1stage_double_precision	(	int	na,
		int	nev,
		double *	a,
		int	lda,
		double *	ev,
		double *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	useGPU
	)

C interface to solve the double-precision real eigenvalue problem with 1-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_real_1stage_single_precision()

int elpa_solve_evp_real_1stage_single_precision	(	int	na,
		int	nev,
		float *	a,
		int	lda,
		float *	ev,
		float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	useGPU
	)

C interface to solve the single-precision real eigenvalue problem with 1-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_real_2stage_double_precision()

int elpa_solve_evp_real_2stage_double_precision	(	int	na,
		int	nev,
		double *	a,
		int	lda,
		double *	ev,
		double *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_REAL_ELPA_KERNEL_API,
		int	useQR,
		int	useGPU
	)

C interface to solve the double-precision real eigenvalue problem with 2-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_REAL_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useQR	use QR decomposition 1 = yes, 0 = no
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_real_2stage_single_precision()

int elpa_solve_evp_real_2stage_single_precision	(	int	na,
		int	nev,
		float *	a,
		int	lda,
		float *	ev,
		float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_REAL_ELPA_KERNEL_API,
		int	useQR,
		int	useGPU
	)

C interface to solve the single-precision real eigenvalue problem with 2-stage solver.

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_REAL_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useQR	use QR decomposition 1 = yes, 0 = no
useGPU	use GPU (1=yes, 0=No)

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_real_double()

int elpa_solve_evp_real_double	(	int	na,
		int	nev,
		double *	a,
		int	lda,
		double *	ev,
		double *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_REAL_ELPA_KERNEL_API,
		int	useQR,
		int	useGPU,
		char *	method
	)

C interface to driver function "elpa_solve_evp_real_double".

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_REAL_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useQR	use QR decomposition 1 = yes, 0 = no
useGPU	use GPU (1=yes, 0=No)
method	choose whether to use ELPA 1stage or 2stage solver possible values: "1stage" => use ELPA 1stage solver "2stage" => use ELPA 2stage solver "auto" => (at the moment) use ELPA 2stage solver

Returns

int: 1 if error occured, otherwise 0

elpa_solve_evp_real_single()

int elpa_solve_evp_real_single	(	int	na,
		int	nev,
		float *	a,
		int	lda,
		float *	ev,
		float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	mpi_comm_all,
		int	THIS_REAL_ELPA_KERNEL_API,
		int	useQR,
		int	useGPU,
		char *	method
	)

C interface to driver function "elpa_solve_evp_real_single".

Parameters

na	Order of matrix a
nev	Number of eigenvalues needed. The smallest nev eigenvalues/eigenvectors are calculated.
a	Distributed matrix for which eigenvalues are to be computed. Distribution is like in Scalapack. The full matrix must be set (not only one half like in scalapack).
lda	Leading dimension of a
ev(na)	On output: eigenvalues of a, every processor gets the complete set
q	On output: Eigenvectors of a Distribution is like in Scalapack. Must be always dimensioned to the full size (corresponding to (na,na)) even if only a part of the eigenvalues is needed.
ldq	Leading dimension of q
nblk	blocksize of cyclic distribution, must be the same in both directions!
matrixCols	distributed number of matrix columns
mpi_comm_rows	MPI-Communicator for rows
mpi_comm_cols	MPI-Communicator for columns
mpi_coll_all	MPI communicator for the total processor set
THIS_REAL_ELPA_KERNEL_API	specify used ELPA2 kernel via API
useQR	use QR decomposition 1 = yes, 0 = no
useGPU	use GPU (1=yes, 0=No)
method	choose whether to use ELPA 1stage or 2stage solver possible values: "1stage" => use ELPA 1stage solver "2stage" => use ELPA 2stage solver "auto" => (at the moment) use ELPA 2stage solver

Returns

int: 1 if error occured, otherwise 0

elpa_solve_tridi_double()

int elpa_solve_tridi_double	(	int	na,
		int	nev,
		double *	d,
		double *	e,
		double *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)

elpa_solve_tridi_single()

int elpa_solve_tridi_single	(	int	na,
		int	nev,
		float *	d,
		float *	e,
		float *	q,
		int	ldq,
		int	nblk,
		int	matrixCols,
		int	mpi_comm_rows,
		int	mpi_comm_cols,
		int	wantDebug
	)