GitLab

instead, blacs context has to be set beforehand

Added C interface for generalized eigen problem
Extended the functionality of test.c to check generalized eigenproblem,
both with and without already decomposed matrix

added possibility to re-use the already decomposed matrix B in the
generalized problem
Added respective test

* tested with elpa1 only (should be sufficient)
* not using Hermitian multiply at the moment
* requires scalapack

and some modifications in test.f90

Apparently it was not fool-proof enough, if they could be disabled that
easily :)

This test was wrong, it was computing A * A^T instead of A^T * A.
The latter is correct since our implementation of Cholesky decomposition
stores the triangular matrix in the upper triangle
The test was passing only because the Cholesky decomposition was tested
with diagonal matrix only, than this does not matter.

This should improve performance, we will see on timings
The main problem was in normalizing eigenvectors, now we
compute maximum of computed (not analytical) solution.
It was nicer to find maximum of analytical one, since it
is the reference, but the implementation was really slow

to tell what is making the test so slow

matrix was initialized outside of three diagonals

To be used like this

   class(elpa_t), pointer      :: e
   class(elpa_autotune_t), pointer :: tune_state

   e => elpa_allocate()
   call e%set(...)
   [...]
   assert_elpa_ok(e%setup())

   tune_state => e%autotune_setup(ELPA_AUTOTUNE_FAST, ELPA_AUTOTUNE_DOMAIN_REAL)

   ! Autotuning loop, continues until all combinations have been tried
   do while (e%autotune_step(tune_state))
     ! Do the steps that are representative of your calculation
     call e%eigenvectors(a, ev, z, error)
   end do

   ! Fix best parameters, and de-allocate the autotune object
   call e%autotune_set_best(tune_state)
   call elpa_autotune_deallocate(tune_state)

in Fortran test.F90