! This file is part of ELPA.
!
! The ELPA library was originally created by the ELPA consortium,
! consisting of the following organizations:
!
! - Max Planck Computing and Data Facility (MPCDF), formerly known as
! Rechenzentrum Garching der Max-Planck-Gesellschaft (RZG),
! - Bergische Universität Wuppertal, Lehrstuhl für angewandte
! Informatik,
! - Technische Universität München, Lehrstuhl für Informatik mit
! Schwerpunkt Wissenschaftliches Rechnen ,
! - Fritz-Haber-Institut, Berlin, Abt. Theorie,
! - Max-Plack-Institut für Mathematik in den Naturwissenschaften,
! Leipzig, Abt. Komplexe Strukutren in Biologie und Kognition,
! and
! - IBM Deutschland GmbH
!
!
! More information can be found here:
! http://elpa.mpcdf.mpg.de/
!
! ELPA is free software: you can redistribute it and/or modify
! it under the terms of the version 3 of the license of the
! GNU Lesser General Public License as published by the Free
! Software Foundation.
!
! ELPA is distributed in the hope that it will be useful,
! but WITHOUT ANY WARRANTY; without even the implied warranty of
! MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
! GNU Lesser General Public License for more details.
!
! You should have received a copy of the GNU Lesser General Public License
! along with ELPA. If not, see
!
! ELPA reflects a substantial effort on the part of the original
! ELPA consortium, and we ask you to respect the spirit of the
! license that we chose: i.e., please contribute any changes you
! may have back to the original ELPA library distribution, and keep
! any derivatives of ELPA under the same license that we chose for
! the original distribution, the GNU Lesser General Public License.
!
! Author: Andreas Marek, MCPDF
#include "config-f90.h"
!c> #include
!c> /*! \brief C old, deprecated interface, will be deleted. Use "elpa_get_communicators"
!c> *
!c> * \param mpi_comm_word MPI global communicator (in)
!c> * \param my_prow Row coordinate of the calling process in the process grid (in)
!c> * \param my_pcol Column coordinate of the calling process in the process grid (in)
!c> * \param mpi_comm_rows Communicator for communicating within rows of processes (out)
!c> * \result int integer error value of mpi_comm_split function
!c> */
!c> int get_elpa_row_col_comms(int mpi_comm_world, int my_prow, int my_pcol, int *mpi_comm_rows, int *mpi_comm_cols);
function get_elpa_row_col_comms_wrapper_c_name1(mpi_comm_world, my_prow, my_pcol, &
mpi_comm_rows, mpi_comm_cols) &
result(mpierr) bind(C,name="get_elpa_row_col_comms")
use, intrinsic :: iso_c_binding
use elpa1, only : get_elpa_row_col_comms
implicit none
integer(kind=c_int) :: mpierr
integer(kind=c_int), value :: mpi_comm_world, my_prow, my_pcol
integer(kind=c_int) :: mpi_comm_rows, mpi_comm_cols
mpierr = get_elpa_row_col_comms(mpi_comm_world, my_prow, my_pcol, &
mpi_comm_rows, mpi_comm_cols)
end function
!c> #include
!c> /*! \brief C old, deprecated interface, will be deleted. Use "elpa_get_communicators"
!c> *
!c> * \param mpi_comm_word MPI global communicator (in)
!c> * \param my_prow Row coordinate of the calling process in the process grid (in)
!c> * \param my_pcol Column coordinate of the calling process in the process grid (in)
!c> * \param mpi_comm_rows Communicator for communicating within rows of processes (out)
!c> * \result int integer error value of mpi_comm_split function
!c> */
!c> int get_elpa_communicators(int mpi_comm_world, int my_prow, int my_pcol, int *mpi_comm_rows, int *mpi_comm_cols);
function get_elpa_row_col_comms_wrapper_c_name2(mpi_comm_world, my_prow, my_pcol, &
mpi_comm_rows, mpi_comm_cols) &
result(mpierr) bind(C,name="get_elpa_communicators")
use, intrinsic :: iso_c_binding
use elpa1, only : get_elpa_communicators
implicit none
integer(kind=c_int) :: mpierr
integer(kind=c_int), value :: mpi_comm_world, my_prow, my_pcol
integer(kind=c_int) :: mpi_comm_rows, mpi_comm_cols
mpierr = get_elpa_communicators(mpi_comm_world, my_prow, my_pcol, &
mpi_comm_rows, mpi_comm_cols)
end function
!c> #include
!c> /*! \brief C interface to create ELPA communicators
!c> *
!c> * \param mpi_comm_word MPI global communicator (in)
!c> * \param my_prow Row coordinate of the calling process in the process grid (in)
!c> * \param my_pcol Column coordinate of the calling process in the process grid (in)
!c> * \param mpi_comm_rows Communicator for communicating within rows of processes (out)
!c> * \result int integer error value of mpi_comm_split function
!c> */
!c> int elpa_get_communicators(int mpi_comm_world, int my_prow, int my_pcol, int *mpi_comm_rows, int *mpi_comm_cols);
function elpa_get_communicators_wrapper_c(mpi_comm_world, my_prow, my_pcol, &
mpi_comm_rows, mpi_comm_cols) &
result(mpierr) bind(C,name="elpa_get_communicators")
use, intrinsic :: iso_c_binding
use elpa1, only : elpa_get_communicators
implicit none
integer(kind=c_int) :: mpierr
integer(kind=c_int), value :: mpi_comm_world, my_prow, my_pcol
integer(kind=c_int) :: mpi_comm_rows, mpi_comm_cols
mpierr = elpa_get_communicators(mpi_comm_world, my_prow, my_pcol, &
mpi_comm_rows, mpi_comm_cols)
end function
!c> /*! \brief C interface to solve the double-precision real eigenvalue problem with 1-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c>*/
#define DOUBLE_PRECISION_REAL 1
#ifdef DOUBLE_PRECISION_REAL
!c> 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);
#else
!c> 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);
#endif
#ifdef DOUBLE_PRECISION_REAL
function solve_elpa1_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_1stage_double_precision")
#else
function solve_elpa1_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_1stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa1
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, mpi_comm_all
integer(kind=c_int), value, intent(in) :: useGPU
#ifdef DOUBLE_PRECISION_REAL
real(kind=c_double) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(lda,*), q(ldq,*)
#else
real(kind=c_double) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#else /* SINGLE_PRECISION */
real(kind=c_float) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_float) :: a(lda,*), q(ldq,*)
#else
real(kind=c_float) :: a(1:lda,1:matrixCols), ev(1:na), q(1:ldq,1:matrixCols)
#endif
#endif
logical :: successFortran
#ifdef DOUBLE_PRECISION_REAL
successFortran = elpa_solve_evp_real_1stage_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#else
successFortran = elpa_solve_evp_real_1stage_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
#undef DOUBLE_PRECISION_REAL
!c> /*! \brief C interface to solve the single-precision real eigenvalue problem with 1-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c>*/
#ifdef DOUBLE_PRECISION_REAL
!c> 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);
#else
!c> 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);
#endif
#ifdef DOUBLE_PRECISION_REAL
function solve_elpa1_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
ueGPU) &
result(success) bind(C,name="elpa_solve_evp_real_1stage_double_precision")
#else
function solve_elpa1_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_1stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa1
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, mpi_comm_all
integer(kind=c_int), value, intent(in) :: useGPU
#ifdef DOUBLE_PRECISION_REAL
real(kind=c_double) :: a(1:lda,1:matrixCols), ev(1:na), q(1:ldq,1:matrixCols)
#else
real(kind=c_float) :: a(1:lda,1:matrixCols), ev(1:na), q(1:ldq,1:matrixCols)
#endif
logical :: successFortran
#ifdef DOUBLE_PRECISION_REAL
successFortran = elpa_solve_evp_real_1stage_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#else
successFortran = elpa_solve_evp_real_1stage_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*! \brief C interface to solve the double-precision complex eigenvalue problem with 1-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
#define DOUBLE_PRECISION_COMPLEX 1
#ifdef DOUBLE_PRECISION_COMPLEX
!c> 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);
#else
!c> int elpa_solve_evp_complex_1stage_single_precision(int na, int nev, complex *a, int lda, float *ev, complex *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int useGPU);
#endif
#ifdef DOUBLE_PRECISION_COMPLEX
function solve_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_1stage_double_precision")
#else
function solve_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_1stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa1
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, mpi_comm_all
integer(kind=c_int), value, intent(in) :: useGPU
#ifdef DOUBLE_PRECISION_COMPLEX
real(kind=c_double) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
complex(kind=c_double_complex) :: a(lda,*), q(ldq,*)
#else
complex(kind=c_double_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#else /* SINGLE_PRECISION */
real(kind=c_float) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
complex(kind=c_float_complex) :: a(lda,*), q(ldq,*)
#else
complex(kind=c_float_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#endif
logical :: successFortran
#ifdef DOUBLE_PRECISION_COMPLEX
successFortran = elpa_solve_evp_complex_1stage_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#else
successFortran = elpa_solve_evp_complex_1stage_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_COMPLEX
!c> /*! \brief C interface to solve the single-precision complex eigenvalue problem with 1-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
#undef DOUBLE_PRECISION_COMPLEX
#ifdef DOUBLE_PRECISION_COMPLEX
!c> 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);
#else
!c> int elpa_solve_evp_complex_1stage_single_precision(int na, int nev, complex *a, int lda, float *ev, complex *q, int ldq, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int mpi_comm_all, int useGPU);
#endif
#ifdef DOUBLE_PRECISION_COMPLEX
function solve_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_1stage_double_precision")
#else
function solve_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_1stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa1
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, mpi_comm_all
integer(kind=c_int), value, intent(in) :: useGPU
#ifdef DOUBLE_PRECISION_COMPLEX
complex(kind=c_double_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
real(kind=c_double) :: ev(1:na)
#else
complex(kind=c_float_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
real(kind=c_float) :: ev(1:na)
#endif
logical :: successFortran
#ifdef DOUBLE_PRECISION_COMPLEX
successFortran = elpa_solve_evp_complex_1stage_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#else
successFortran = elpa_solve_evp_complex_1stage_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_COMPLEX */
!c> /*! \brief C interface to solve the double-precision real eigenvalue problem with 2-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_REAL_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useQR use QR decomposition 1 = yes, 0 = no
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
#define DOUBLE_PRECISION_REAL 1
#ifdef DOUBLE_PRECISION_REAL
!c> 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);
#else
!c> 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);
#endif
#ifdef DOUBLE_PRECISION_REAL
function solve_elpa2_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQR, useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_2stage_double_precision")
#else
function solve_elpa2_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQR, useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_2stage_double_precision")
result(success) bind(C,name="elpa_solve_evp_real_2stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa2
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_REAL_ELPA_KERNEL_API, useQR, useGPU
#ifdef DOUBLE_PRECISION_REAL
real(kind=c_double) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(lda,*), q(ldq,*)
#else
real(kind=c_double) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#else /* SINGLE_PRECISION */
real(kind=c_float) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_float) :: a(1:lda,*), q(1:ldq,*)
#else
real(kind=c_float) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#endif
logical :: successFortran, useQRFortran
if (useQR .eq. 0) then
useQRFortran =.false.
else
useQRFortran = .true.
endif
#ifdef DOUBLE_PRECISION_REAL
successFortran = elpa_solve_evp_real_2stage_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1)
#else
successFortran = elpa_solve_evp_real_2stage_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
!c> /*! \brief C interface to solve the single-precision real eigenvalue problem with 2-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_REAL_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useQR use QR decomposition 1 = yes, 0 = no
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
#undef DOUBLE_PRECISION_REAL
#ifdef DOUBLE_PRECISION_REAL
!c> 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);
#else
!c> 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);
#endif
#ifdef DOUBLE_PRECISION_REAL
function solve_elpa2_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQR, useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_2stage_double_precision")
#else
function solve_elpa2_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQR, useGPU) &
result(success) bind(C,name="elpa_solve_evp_real_2stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa2
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_REAL_ELPA_KERNEL_API, useQR, useGPU
#ifdef DOUBLE_PRECISION_REAL
real(kind=c_double) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(1:lda,*), q(1:ldq,*)
#else
real(kind=c_double) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#else /* SINGLE_PRECISION */
real(kind=c_float) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_float) :: a(1:lda,*), q(1:ldq,*)
#else
real(kind=c_float) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#endif
logical :: successFortran, useQRFortran
if (useQR .eq. 0) then
useQRFortran =.false.
else
useQRFortran = .true.
endif
#ifdef DOUBLE_PRECISION_REAL
successFortran = elpa_solve_evp_real_2stage_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1)
#else
successFortran = elpa_solve_evp_real_2stage_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*! \brief C interface to solve the double-precision complex eigenvalue problem with 2-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_COMPLEX_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
#define DOUBLE_PRECISION_COMPLEX 1
#ifdef DOUBLE_PRECISION_COMPLEX
!c> 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);
#else
!c> int elpa_solve_evp_complex_2stage_single_precision(int na, int nev, complex *a, int lda, float *ev, 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);
#endif
#ifdef DOUBLE_PRECISION_COMPLEX
function solve_elpa2_evp_complex_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_COMPLEX_ELPA_KERNEL_API, useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_2stage_double_precision")
#else
function solve_elpa2_evp_complex_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_COMPLEX_ELPA_KERNEL_API, useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_2stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa2
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_COMPLEX_ELPA_KERNEL_API, useGPU
#ifdef DOUBLE_PRECISION_COMPLEX
real(kind=c_double) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
complex(kind=c_double_complex) :: a(lda,*), q(ldq,*)
#else
complex(kind=c_double_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#else /* SINGLE_PRECISION */
real(kind=c_float) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
complex(kind=c_float_complex) :: a(lda,*), q(ldq,*)
#else
complex(kind=c_float_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
#endif
logical :: successFortran
! matrix is not banded
#ifdef DOUBLE_PRECISION_COMPLEX
successFortran = elpa_solve_evp_complex_2stage_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, &
mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1)
#else
successFortran = elpa_solve_evp_complex_2stage_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, &
mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_COMPLEX
!c> /*! \brief C interface to solve the single-precision complex eigenvalue problem with 2-stage solver
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_REAL_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
#undef DOUBLE_PRECISION_COMPLEX
#ifdef DOUBLE_PRECISION_COMPLEX
!c> 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);
#else
!c> int elpa_solve_evp_complex_2stage_single_precision(int na, int nev, complex *a, int lda, float *ev, 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);
#endif
#ifdef DOUBLE_PRECISION_COMPLEX
function solve_elpa2_evp_complex_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_COMPLEX_ELPA_KERNEL_API, useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_2stage_double_precision")
#else
function solve_elpa2_evp_complex_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_COMPLEX_ELPA_KERNEL_API, useGPU) &
result(success) bind(C,name="elpa_solve_evp_complex_2stage_single_precision")
#endif
use, intrinsic :: iso_c_binding
use elpa2
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_COMPLEX_ELPA_KERNEL_API, useGPU
#ifdef DOUBLE_PRECISION_COMPLEX
complex(kind=c_double_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
real(kind=c_double) :: ev(1:na)
#else
complex(kind=c_float_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
real(kind=c_float) :: ev(1:na)
#endif
logical :: successFortran
#ifdef DOUBLE_PRECISION_COMPLEX
successFortran = elpa_solve_evp_complex_2stage_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, &
mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1)
#else
successFortran = elpa_solve_evp_complex_2stage_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, &
mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1)
#endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_COMPLEX */
!c> /*! \brief C interface to driver function "elpa_solve_evp_real_double"
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_REAL_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useQR use QR decomposition 1 = yes, 0 = no
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> * \param method choose whether to use ELPA 1stage or 2stage solver
!c> * possible values: "1stage" => use ELPA 1stage solver
!c> * "2stage" => use ELPA 2stage solver
!c> * "auto" => (at the moment) use ELPA 2stage solver
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
!c> 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);
function elpa_solve_evp_real_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQR, useGPU, method) &
result(success) bind(C,name="elpa_solve_evp_real_double")
use, intrinsic :: iso_c_binding
use elpa, only : elpa_solve_evp_real_double
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_REAL_ELPA_KERNEL_API, useQR, useGPU
real(kind=c_double) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(lda,*), q(ldq,*)
#else
real(kind=c_double) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
logical :: successFortran, useQRFortran
character(kind=c_char,len=1), intent(in) :: method(*)
character(len=6) :: methodFortran
integer(kind=c_int) :: charCount
if (useQR .eq. 0) then
useQRFortran =.false.
else
useQRFortran = .true.
endif
charCount = 1
do
if (method(charCount) == c_null_char) exit
charCount = charCount + 1
enddo
charCount = charCount - 1
if (charCount .ge. 1) then
methodFortran(1:charCount) = transfer(method(1:charCount), methodFortran)
successFortran = elpa_solve_evp_real_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1, methodFortran)
else
successFortran = elpa_solve_evp_real_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1)
endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
!c> /*! \brief C interface to driver function "elpa_solve_evp_real_single"
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_REAL_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useQR use QR decomposition 1 = yes, 0 = no
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> * \param method choose whether to use ELPA 1stage or 2stage solver
!c> * possible values: "1stage" => use ELPA 1stage solver
!c> * "2stage" => use ELPA 2stage solver
!c> * "auto" => (at the moment) use ELPA 2stage solver
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
!c> 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);
function elpa_solve_evp_real_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQR, useGPU, method) &
result(success) bind(C,name="elpa_solve_evp_real_single")
use, intrinsic :: iso_c_binding
use elpa, only : elpa_solve_evp_real_single
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_REAL_ELPA_KERNEL_API, useQR, useGPU
real(kind=c_float) :: ev(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_float) :: a(lda,*), q(ldq,*)
#else
real(kind=c_float) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
logical :: successFortran, useQRFortran
character(kind=c_char,len=1), intent(in) :: method(*)
character(len=6) :: methodFortran
integer(kind=c_int) :: charCount
if (useQR .eq. 0) then
useQRFortran =.false.
else
useQRFortran = .true.
endif
charCount = 1
do
if (method(charCount) == c_null_char) exit
charCount = charCount + 1
enddo
charCount = charCount - 1
if (charCount .ge. 1) then
methodFortran(1:charCount) = transfer(method(1:charCount), methodFortran)
successFortran = elpa_solve_evp_real_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1, methodFortran)
else
successFortran = elpa_solve_evp_real_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, mpi_comm_all, &
THIS_REAL_ELPA_KERNEL_API, useQRFortran, useGPU == 1)
endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*! \brief C interface to driver function "elpa_solve_evp_complex_double"
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_COMPLEX_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> * \param method choose whether to use ELPA 1stage or 2stage solver
!c> * possible values: "1stage" => use ELPA 1stage solver
!c> * "2stage" => use ELPA 2stage solver
!c> * "auto" => (at the moment) use ELPA 2stage solver
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
!c> 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);
function elpa_solve_evp_complex_wrapper_double(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_COMPLEX_ELPA_KERNEL_API, useGPU, method) &
result(success) bind(C,name="elpa_solve_evp_complex_double")
use, intrinsic :: iso_c_binding
use elpa, only : elpa_solve_evp_complex_double
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_COMPLEX_ELPA_KERNEL_API, useGPU
#ifdef USE_ASSUMED_SIZE
complex(kind=c_double_complex) :: a(lda,*), q(ldq,*)
#else
complex(kind=c_double_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
real(kind=c_double) :: ev(1:na)
character(kind=c_char,len=1), intent(in) :: method(*)
character(len=6) :: methodFortran
integer(kind=c_int) :: charCount
logical :: successFortran
charCount = 1
do
if (method(charCount) == c_null_char) exit
charCount = charCount + 1
enddo
charCount = charCount - 1
if (charCount .ge. 1) then
methodFortran(1:charCount) = transfer(method(1:charCount), methodFortran)
successFortran = elpa_solve_evp_complex_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1, methodFortran)
else
successFortran = elpa_solve_evp_complex_double(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1)
endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_COMPLEX
!c> /*! \brief C interface to driver function "elpa_solve_evp_complex_single"
!c> *
!c> * \param na Order of matrix a
!c> * \param nev Number of eigenvalues needed.
!c> * The smallest nev eigenvalues/eigenvectors are calculated.
!c> * \param a Distributed matrix for which eigenvalues are to be computed.
!c> * Distribution is like in Scalapack.
!c> * The full matrix must be set (not only one half like in scalapack).
!c> * \param lda Leading dimension of a
!c> * \param ev(na) On output: eigenvalues of a, every processor gets the complete set
!c> * \param q On output: Eigenvectors of a
!c> * Distribution is like in Scalapack.
!c> * Must be always dimensioned to the full size (corresponding to (na,na))
!c> * even if only a part of the eigenvalues is needed.
!c> * \param ldq Leading dimension of q
!c> * \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> * \param matrixCols distributed number of matrix columns
!c> * \param mpi_comm_rows MPI-Communicator for rows
!c> * \param mpi_comm_cols MPI-Communicator for columns
!c> * \param mpi_coll_all MPI communicator for the total processor set
!c> * \param THIS_COMPLEX_ELPA_KERNEL_API specify used ELPA2 kernel via API
!c> * \param useGPU use GPU (1=yes, 0=No)
!c> * \param method choose whether to use ELPA 1stage or 2stage solver
!c> * possible values: "1stage" => use ELPA 1stage solver
!c> * "2stage" => use ELPA 2stage solver
!c> * "auto" => (at the moment) use ELPA 2stage solver
!c> *
!c> * \result int: 1 if error occured, otherwise 0
!c> */
!c> int elpa_solve_evp_complex_single(int na, int nev, complex *a, int lda, float *ev, 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);
function elpa_solve_evp_complex_wrapper_single(na, nev, a, lda, ev, q, ldq, nblk, &
matrixCols, mpi_comm_rows, mpi_comm_cols, mpi_comm_all, &
THIS_COMPLEX_ELPA_KERNEL_API, useGPU, method) &
result(success) bind(C,name="elpa_solve_evp_complex_single")
use, intrinsic :: iso_c_binding
use elpa, only : elpa_solve_evp_complex_single
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, lda, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows, &
mpi_comm_all
integer(kind=c_int), value, intent(in) :: THIS_COMPLEX_ELPA_KERNEL_API, useGPU
#ifdef USE_ASSUMED_SIZE
complex(kind=c_float_complex) :: a(lda,*), q(ldq,*)
#else
complex(kind=c_float_complex) :: a(1:lda,1:matrixCols), q(1:ldq,1:matrixCols)
#endif
real(kind=c_float) :: ev(1:na)
character(kind=c_char,len=1), intent(in) :: method(*)
character(len=6) :: methodFortran
integer(kind=c_int) :: charCount
logical :: successFortran
charCount = 1
do
if (method(charCount) == c_null_char) exit
charCount = charCount + 1
enddo
charCount = charCount - 1
if (charCount .ge. 1) then
methodFortran(1:charCount) = transfer(method(1:charCount), methodFortran)
successFortran = elpa_solve_evp_complex_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU == 1, methodFortran)
else
successFortran = elpa_solve_evp_complex_single(na, nev, a, lda, ev, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, &
mpi_comm_all, THIS_COMPLEX_ELPA_KERNEL_API, useGPU ==1)
endif
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_COMPLEX */
!c> /*
!c> \brief C interface to solve double-precision tridiagonal eigensystem with divide and conquer method
!c> \details
!c>
!c> *\param na Matrix dimension
!c> *\param nev number of eigenvalues/vectors to be computed
!c> *\param d array d(na) on input diagonal elements of tridiagonal matrix, on
!c> * output the eigenvalues in ascending order
!c> *\param e array e(na) on input subdiagonal elements of matrix, on exit destroyed
!c> *\param q on exit : matrix q(ldq,matrixCols) contains the eigenvectors
!c> *\param ldq leading dimension of matrix q
!c> *\param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> *\param matrixCols columns of matrix q
!c> *\param mpi_comm_rows MPI communicator for rows
!c> *\param mpi_comm_cols MPI communicator for columns
!c> *\param wantDebug give more debug information if 1, else 0
!c> *\result success int 1 on success, else 0
!c> */
!c> 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);
function elpa_solve_tridi_wrapper_double(na, nev, d, e, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug) &
result(success) bind(C,name="elpa_solve_tridi_double")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_solve_tridi_double
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows
integer(kind=c_int), value :: wantDebug
real(kind=c_double) :: d(1:na), e(1:na)
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: q(ldq,*)
#else
real(kind=c_double) :: q(1:ldq, 1:matrixCols)
#endif
logical :: successFortran, wantDebugFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_solve_tridi_double(na, nev, d, e, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, &
wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
!c> /*
!c> \brief C interface to solve single-precision tridiagonal eigensystem with divide and conquer method
!c> \details
!c>
!c> \param na Matrix dimension
!c> \param nev number of eigenvalues/vectors to be computed
!c> \param d array d(na) on input diagonal elements of tridiagonal matrix, on
!c> output the eigenvalues in ascending order
!c> \param e array e(na) on input subdiagonal elements of matrix, on exit destroyed
!c> \param q on exit : matrix q(ldq,matrixCols) contains the eigenvectors
!c> \param ldq leading dimension of matrix q
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param matrixCols columns of matrix q
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug give more debug information if 1, else 0
!c> \result success int 1 on success, else 0
!c> */
!c> 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);
function elpa_solve_tridi_wrapper_single(na, nev, d, e, q, ldq, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug) &
result(success) bind(C,name="elpa_solve_tridi_single")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_solve_tridi_single
implicit none
integer(kind=c_int) :: success
integer(kind=c_int), value, intent(in) :: na, nev, ldq, nblk, matrixCols, mpi_comm_cols, mpi_comm_rows
integer(kind=c_int), value :: wantDebug
real(kind=c_float) :: d(1:na), e(1:na), q(1:ldq, 1:matrixCols)
logical :: successFortran, wantDebugFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_solve_tridi_single(na, nev, d, e, q, ldq, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*
!c> \brief C interface for elpa_mult_at_b_real_double: Performs C : = A**T * B for double-precision matrices
!c> where A is a square matrix (na,na) which is optionally upper or lower triangular
!c> B is a (na,ncb) matrix
!c> C is a (na,ncb) matrix where optionally only the upper or lower
!c> triangle may be computed
!c> \details
!c> \param uplo_a 'U' if A is upper triangular
!c> 'L' if A is lower triangular
!c> anything else if A is a full matrix
!c> Please note: This pertains to the original A (as set in the calling program)
!c> whereas the transpose of A is used for calculations
!c> If uplo_a is 'U' or 'L', the other triangle is not used at all,
!c> i.e. it may contain arbitrary numbers
!c> \param uplo_c 'U' if only the upper diagonal part of C is needed
!c> 'L' if only the upper diagonal part of C is needed
!c> anything else if the full matrix C is needed
!c> Please note: Even when uplo_c is 'U' or 'L', the other triangle may be
!c> written to a certain extent, i.e. one shouldn't rely on the content there!
!c> \param na Number of rows/columns of A, number of rows of B and C
!c> \param ncb Number of columns of B and C
!c> \param a matrix a
!c> \param lda leading dimension of matrix a
!c> \param ldaCols columns of matrix a
!c> \param b matrix b
!c> \param ldb leading dimension of matrix b
!c> \param ldbCols columns of matrix b
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param c matrix c
!c> \param ldc leading dimension of matrix c
!c> \param ldcCols columns of matrix c
!c> \result success int report success (1) or failure (0)
!c> */
!c> 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);
function elpa_mult_at_b_real_wrapper_double(uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols) &
bind(C,name="elpa_mult_at_b_real_double") result(success)
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_mult_at_b_real_double
implicit none
character(1,C_CHAR), value :: uplo_a, uplo_c
integer(kind=c_int), value :: na, ncb, lda, ldb, nblk, mpi_comm_rows, mpi_comm_cols, ldc, &
ldaCols, ldbCols, ldcCols
integer(kind=c_int) :: success
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(lda,*), b(ldb,*), c(ldc,*)
#else
real(kind=c_double) :: a(lda,ldaCols), b(ldb,ldbCols), c(ldc,ldcCols)
#endif
logical :: successFortran
successFortran = elpa_mult_at_b_real_double(uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
!c> /*
!c> \brief C interface for elpa_mult_at_b_real_single: Performs C : = A**T * B for single-precision matrices
!c> where A is a square matrix (na,na) which is optionally upper or lower triangular
!c> B is a (na,ncb) matrix
!c> C is a (na,ncb) matrix where optionally only the upper or lower
!c> triangle may be computed
!c> \details
!c> \param uplo_a 'U' if A is upper triangular
!c> 'L' if A is lower triangular
!c> anything else if A is a full matrix
!c> Please note: This pertains to the original A (as set in the calling program)
!c> whereas the transpose of A is used for calculations
!c> If uplo_a is 'U' or 'L', the other triangle is not used at all,
!c> i.e. it may contain arbitrary numbers
!c> \param uplo_c 'U' if only the upper diagonal part of C is needed
!c> 'L' if only the upper diagonal part of C is needed
!c> anything else if the full matrix C is needed
!c> Please note: Even when uplo_c is 'U' or 'L', the other triangle may be
!c> written to a certain extent, i.e. one shouldn't rely on the content there!
!c> \param na Number of rows/columns of A, number of rows of B and C
!c> \param ncb Number of columns of B and C
!c> \param a matrix a
!c> \param lda leading dimension of matrix a
!c> \param ldaCols columns of matrix a
!c> \param b matrix b
!c> \param ldb leading dimension of matrix b
!c> \param ldbCols columns of matrix b
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param c matrix c
!c> \param ldc leading dimension of matrix c
!c> \result success int report success (1) or failure (0)
!c> */
!c> 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);
function elpa_mult_at_b_real_wrapper_float(uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols) &
bind(C,name="elpa_mult_at_b_real_float") result(success)
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_mult_at_b_real_single
implicit none
character(1,C_CHAR), value :: uplo_a, uplo_c
integer(kind=c_int), value :: na, ncb, lda, ldb, nblk, mpi_comm_rows, mpi_comm_cols, ldc
integer(kind=c_int) :: success
integer(kind=c_int), value :: ldaCols, ldbCols, ldCcols
#ifdef USE_ASSUMED_SIZE
real(kind=c_float) :: a(lda,*), b(ldb,*), c(ldc,*)
#else
real(kind=c_float) :: a(lda,ldaCols), b(ldb,ldbCols), c(ldc,ldcCols)
#endif
logical :: successFortran
successFortran = elpa_mult_at_b_real_single(uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*
!c> \brief C interface for elpa_mult_ah_b_complex_double: Performs C : = A**H * B for double-precision matrices
!c> where A is a square matrix (na,na) which is optionally upper or lower triangular
!c> B is a (na,ncb) matrix
!c> C is a (na,ncb) matrix where optionally only the upper or lower
!c> triangle may be computed
!c> \details
!c>
!c> \param uplo_a 'U' if A is upper triangular
!c> 'L' if A is lower triangular
!c> anything else if A is a full matrix
!c> Please note: This pertains to the original A (as set in the calling program)
!c> whereas the transpose of A is used for calculations
!c> If uplo_a is 'U' or 'L', the other triangle is not used at all,
!c> i.e. it may contain arbitrary numbers
!c> \param uplo_c 'U' if only the upper diagonal part of C is needed
!c> 'L' if only the upper diagonal part of C is needed
!c> anything else if the full matrix C is needed
!c> Please note: Even when uplo_c is 'U' or 'L', the other triangle may be
!c> written to a certain extent, i.e. one shouldn't rely on the content there!
!c> \param na Number of rows/columns of A, number of rows of B and C
!c> \param ncb Number of columns of B and C
!c> \param a matrix a
!c> \param lda leading dimension of matrix a
!c> \param b matrix b
!c> \param ldb leading dimension of matrix b
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param c matrix c
!c> \param ldc leading dimension of matrix c
!c> \result success int reports success (1) or failure (0)
!c> */
!c> 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);
function elpa_mult_ah_b_complex_wrapper_double( uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, &
mpi_comm_cols, c, ldc, ldcCols) result(success) &
bind(C,name="elpa_mult_ah_b_complex_double")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_mult_ah_b_complex_double
implicit none
character(1,C_CHAR), value :: uplo_a, uplo_c
integer(kind=c_int), value :: na, ncb, lda, ldb, nblk, mpi_comm_rows, mpi_comm_cols, ldc
integer(kind=c_int) :: success
integer(kind=c_int), value :: ldaCols, ldbCols, ldcCols
#ifdef USE_ASSUMED_SIZE
complex(kind=c_double_complex) :: a(lda,*), b(ldb,*), c(ldc,*)
#else
complex(kind=c_double_complex) :: a(lda,ldaCols), b(ldb,ldbCols), c(ldc,ldcCols)
#endif
logical :: successFortran
successFortran = elpa_mult_ah_b_complex_double(uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, nblk, &
mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_COMPLEX
!c> /*
!c> \brief C interface for elpa_mult_ah_b_complex_single: Performs C : = A**H * B for single-precision matrices
!c> where A is a square matrix (na,na) which is optionally upper or lower triangular
!c> B is a (na,ncb) matrix
!c> C is a (na,ncb) matrix where optionally only the upper or lower
!c> triangle may be computed
!c> \details
!c>
!c> \param uplo_a 'U' if A is upper triangular
!c> 'L' if A is lower triangular
!c> anything else if A is a full matrix
!c> Please note: This pertains to the original A (as set in the calling program)
!c> whereas the transpose of A is used for calculations
!c> If uplo_a is 'U' or 'L', the other triangle is not used at all,
!c> i.e. it may contain arbitrary numbers
!c> \param uplo_c 'U' if only the upper diagonal part of C is needed
!c> 'L' if only the upper diagonal part of C is needed
!c> anything else if the full matrix C is needed
!c> Please note: Even when uplo_c is 'U' or 'L', the other triangle may be
!c> written to a certain extent, i.e. one shouldn't rely on the content there!
!c> \param na Number of rows/columns of A, number of rows of B and C
!c> \param ncb Number of columns of B and C
!c> \param a matrix a
!c> \param lda leading dimension of matrix a
!c> \param b matrix b
!c> \param ldb leading dimension of matrix b
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param c matrix c
!c> \param ldc leading dimension of matrix c
!c> \result success int reports success (1) or failure (0)
!c> */
!c> int elpa_mult_ah_b_complex_single(char uplo_a, char uplo_c, int na, int ncb, complex *a, int lda, int ldaCols, complex *b, int ldb, int ldbCols, int nblk, int mpi_comm_rows, int mpi_comm_cols, complex *c, int ldc, int ldcCols);
function elpa_mult_ah_b_complex_wrapper_single( uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols) &
result(success) bind(C,name="elpa_mult_ah_b_complex_single")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_mult_ah_b_complex_single
implicit none
character(1,C_CHAR), value :: uplo_a, uplo_c
integer(kind=c_int), value :: na, ncb, lda, ldb, nblk, mpi_comm_rows, mpi_comm_cols, ldc
integer(kind=c_int) :: success
integer(kind=c_int), value :: ldaCols, ldbCols, ldcCols
#ifdef USE_ASSUMED_SIZE
complex(kind=c_float_complex) :: a(lda,*), b(ldb,*), c(ldc,*)
#else
complex(kind=c_float_complex) :: a(lda,ldaCols), b(ldb,ldbCols), c(ldc,ldcCols)
#endif
logical :: successFortran
successFortran = elpa_mult_ah_b_complex_single(uplo_a, uplo_c, na, ncb, a, lda, ldaCols, b, ldb, ldbCols, &
nblk, mpi_comm_rows, mpi_comm_cols, c, ldc, ldcCols)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_COMPLEX */
!c> /*
!c> \brief C interface to elpa_invert_trm_real_double: Inverts a real double-precision upper triangular matrix
!c> \details
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be inverted
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> The lower triangle is not referenced.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> 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);
function elpa_invert_trm_real_wrapper_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug) &
result(success) bind(C,name="elpa_invert_trm_real_double")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_invert_trm_real_double
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols
integer(kind=c_int), value :: wantDebug
integer(kind=c_int) :: success
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(lda,*)
#else
real(kind=c_double) :: a(lda,matrixCols)
#endif
logical :: wantDebugFortran, successFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_invert_trm_real_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
!c> /*
!c> \brief C interface to elpa_invert_trm_real_single: Inverts a real single-precision upper triangular matrix
!c> \details
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be inverted
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> The lower triangle is not referenced.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> int elpa_invert_trm_real_single(int na, double *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug);
function elpa_invert_trm_real_wrapper_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug) &
result(success) bind(C,name="elpa_invert_trm_real_single")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_invert_trm_real_single
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols
integer(kind=c_int), value :: wantDebug
integer(kind=c_int) :: success
real(kind=c_float) :: a(lda,matrixCols)
logical :: wantDebugFortran, successFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_invert_trm_real_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*
!c> \brief C interface to elpa_invert_trm_complex_double: Inverts a double-precision complex upper triangular matrix
!c> \details
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be inverted
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> The lower triangle is not referenced.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> 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);
function elpa_invert_trm_complex_wrapper_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, wantDebug) result(success) &
bind(C,name="elpa_invert_trm_complex_double")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_invert_trm_complex_double
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols
integer(kind=c_int), value :: wantDebug
integer(kind=c_int) :: success
#ifdef USE_ASSUMED_SIZE
complex(kind=c_double_complex) :: a(lda, *)
#else
complex(kind=c_double_complex) :: a(lda, matrixCols)
#endif
logical :: successFortran, wantDebugFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_invert_trm_complex_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_COMPLEX
!c> /*
!c> \brief C interface to elpa_invert_trm_complex_single: Inverts a single-precision complex upper triangular matrix
!c> \details
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be inverted
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> The lower triangle is not referenced.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> int elpa_invert_trm_complex_single(int na, complex *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug);
function elpa_invert_trm_complex_wrapper_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, wantDebug) result(success) &
bind(C,name="elpa_invert_trm_complex_single")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_invert_trm_complex_single
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols
integer(kind=c_int), value :: wantDebug
integer(kind=c_int) :: success
complex(kind=c_float_complex) :: a(lda, matrixCols)
logical :: successFortran, wantDebugFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_invert_trm_complex_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_COMPLEX */
!c> /*
!c> \brief elpa_cholesky_real_double: Cholesky factorization of a double-precision real symmetric matrix
!c> \details
!c>
!c> *\param na Order of matrix
!c> *\param a(lda,matrixCols) Distributed matrix which should be factorized.
!c> * Distribution is like in Scalapack.
!c> * Only upper triangle is needs to be set.
!c> * On return, the upper triangle contains the Cholesky factor
!c> * and the lower triangle is set to 0.
!c> *\param lda Leading dimension of a
!c> *\param matrixCols local columns of matrix a
!c> *\param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> *\param mpi_comm_rows MPI communicator for rows
!c> *\param mpi_comm_cols MPI communicator for columns
!c> *\param wantDebug int more debug information on failure if 1, else 0
!c> *\result succes int reports success (1) or failure (0)
!c> */
!c> 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);
function elpa_cholesky_real_wrapper_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug) result(success) &
bind(C,name="elpa_cholesky_real_double")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_cholesky_real_double
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug
integer(kind=c_int) :: success
#ifdef USE_ASSUMED_SIZE
real(kind=c_double) :: a(lda,*)
#else
real(kind=c_double) :: a(lda,matrixCols)
#endif
logical :: successFortran, wantDebugFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_cholesky_real_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_REAL
!c> /*
!c> \brief elpa_cholesky_real_single: Cholesky factorization of a single-precision real symmetric matrix
!c> \details
!c>
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be factorized.
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> On return, the upper triangle contains the Cholesky factor
!c> and the lower triangle is set to 0.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> 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);
function elpa_cholesky_real_wrapper_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug) result(success) &
bind(C,name="elpa_cholesky_real_single")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_cholesky_real_single
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug
integer(kind=c_int) :: success
real(kind=c_float) :: a(lda,matrixCols)
logical :: successFortran, wantDebugFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_cholesky_real_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_REAL */
!c> /*
!c> \brief C interface elpa_cholesky_complex_double: Cholesky factorization of a double-precision complex hermitian matrix
!c> \details
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be factorized.
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> On return, the upper triangle contains the Cholesky factor
!c> and the lower triangle is set to 0.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure, if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> 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);
function elpa_cholesky_complex_wrapper_double(na, a, lda, nblk, matrixCols, mpi_comm_rows, &
mpi_comm_cols, wantDebug) result(success) &
bind(C,name="elpa_cholesky_complex_double")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_cholesky_complex_double
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug
integer(kind=c_int) :: success
#ifdef USE_ASSUMED_SIZE
complex(kind=c_double_complex) :: a(lda,*)
#else
complex(kind=c_double_complex) :: a(lda,matrixCols)
#endif
logical :: wantDebugFortran, successFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_cholesky_complex_double(na, a, lda, nblk, matrixCols, &
mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#ifdef WANT_SINGLE_PRECISION_COMPLEX
!c> /*
!c> \brief C interface elpa_cholesky_complex_single: Cholesky factorization of a single-precision complex hermitian matrix
!c> \details
!c> \param na Order of matrix
!c> \param a(lda,matrixCols) Distributed matrix which should be factorized.
!c> Distribution is like in Scalapack.
!c> Only upper triangle is needs to be set.
!c> On return, the upper triangle contains the Cholesky factor
!c> and the lower triangle is set to 0.
!c> \param lda Leading dimension of a
!c> \param matrixCols local columns of matrix a
!c> \param nblk blocksize of cyclic distribution, must be the same in both directions!
!c> \param mpi_comm_rows MPI communicator for rows
!c> \param mpi_comm_cols MPI communicator for columns
!c> \param wantDebug int more debug information on failure, if 1, else 0
!c> \result succes int reports success (1) or failure (0)
!c> */
!c> int elpa_cholesky_complex_single(int na, complex *a, int lda, int nblk, int matrixCols, int mpi_comm_rows, int mpi_comm_cols, int wantDebug);
function elpa_cholesky_complex_wrapper_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, &
wantDebug) result(success) &
bind(C,name="elpa_cholesky_complex_single")
use, intrinsic :: iso_c_binding
use elpa1_auxiliary, only : elpa_cholesky_complex_single
implicit none
integer(kind=c_int), value :: na, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebug
integer(kind=c_int) :: success
complex(kind=c_float_complex) :: a(lda,matrixCols)
logical :: wantDebugFortran, successFortran
if (wantDebug .ne. 0) then
wantDebugFortran = .true.
else
wantDebugFortran = .false.
endif
successFortran = elpa_cholesky_complex_single(na, a, lda, nblk, matrixCols, mpi_comm_rows, mpi_comm_cols, wantDebugFortran)
if (successFortran) then
success = 1
else
success = 0
endif
end function
#endif /* WANT_SINGLE_PRECISION_COMPLEX */