It is not needed, since CUSPARSE is included in all versions of CUDA
since at least 7.0.

Also note that CUSPARSE is needed only for some tests and legacy code
(tnl-benchmark-spmv and wrappers in Matrices::CSR) and experimental code
(Preconditioners::ILU0). Everything is still guarded by the
HAVE_CUSPARSE macro, so the user can pass -DHAVE_CUSPARSE -lcusparse to
the compiler to enable the features.

I don't understand how it could work on the small grids...

Why do problems have this method anyway? It was obviously never used...

Needs refactoring!

The previous version was too complicated and even wrong as it did not
allow to configure e.g. solvers with doubles and meshes with floats.

Implementation of TimeIndependentPDESolver.

- separate data types for input arrays of binary operations
  (necessary for the equality comparison of two arrays of different
  type)
- added separate template parameter for ResultType, which defaults to
  the RealType
  (the goal is to allow sum of bool vectors into int instead of bool)