CUDA code for RMMDIIS

There seems to be a problem for the CUDA version of the rmmdiis eigensolver:

Even when forcing the same blocksizes and tightening the EigensolverTolerance to 1e-9, the CUDA version of the code does not converge.

The example I used is the testsuite/functionals/10-vdw_d3_dna.01-gs_novdw.inp

Differences to the non-CUDA code appear at the first printout of the eigenvalues:

CUDA:

Eigenvalues [H]
 #st  Spin   Eigenvalue      Occupation
#k =   1, k = (  0.000000,  0.000000,  0.000000)
   1   --    -1.027486       2.000000
   2   --    -1.019632       2.000000
   3   --    -0.978117       2.000000
   4   --    -0.968847       2.000000
   5   --    -0.953255       2.000000
   6   --    -0.940347       2.000000
   7   --    -0.932274       2.000000
   8   --    -0.926782       2.000000
   9   --    -0.912659       2.000000
  10   --    -0.891247       2.000000
  11   --    -0.889957       2.000000
  12   --    -0.885875       2.000000
  13   --    -0.871691       2.000000
  14   --    -0.863637       2.000000
  15   --    -0.851919       2.000000
  16   --    -0.830239       2.000000
  17   --    -0.815815       2.000000
  18   --    -0.793890       2.000000
  19   --    -0.773314       2.000000
  20   --    -0.771723       2.000000
  21   --    -0.690563       2.000000
  22   --    -0.683969       2.000000
  23   --    -0.673973       2.000000
  24   --    -0.667205       2.000000
  25   --    -0.660853       2.000000
 ...

non-CUDA:

Eigenvalues [H]
 #st  Spin   Eigenvalue      Occupation
#k =   1, k = (  0.000000,  0.000000,  0.000000)
   1   --    -1.027486       2.000000
   2   --    -1.019632       2.000000
   3   --    -0.978117       2.000000
   4   --    -0.968846       2.000000
   5   --    -0.953349       2.000000
   6   --    -0.940348       2.000000
   7   --    -0.932295       2.000000
   8   --    -0.929263       2.000000
   9   --    -0.912685       2.000000
  10   --    -0.893838       2.000000
  11   --    -0.890251       2.000000
  12   --    -0.885876       2.000000
  13   --    -0.871691       2.000000
  14   --    -0.863660       2.000000
  15   --    -0.852078       2.000000
  16   --    -0.837568       2.000000
  17   --    -0.816301       2.000000
  18   --    -0.798950       2.000000
  19   --    -0.773314       2.000000
  20   --    -0.771725       2.000000
  21   --    -0.692003       2.000000
  22   --    -0.686843       2.000000
  23   --    -0.673974       2.000000
  24   --    -0.667211       2.000000
  25   --    -0.660855       2.000000
 ...

An interesting thing is that some eigenvalues do agree (1-3, 13, and some more) agree, but that might be coincidence.