This will ensure that in verbose mode, the final state of the linear
system solvers is always printed. Previously this was the case only when
refresh rate was equal to 1.

Moved tnlObject_impl.h back to tnlObject.cpp since function definitions
in header files cause duplicates when building libtnl. The constructor
of tnlObject is __cuda_callable__ so it's empty definition was moved
directly to tnlObject.h to make it visible to nvcc.

Problem with marking tnlObject's virtual destructor as __cuda_callable__
is yet to be solved...

It does not make sense to define e.g. HAVE_CUSPARSE when HAVE_CUDA is
not defined. Otherwise it would be necessary to pass the CUDA's include
path even when compiling with GCC without CUDA support.

* master:
  Name in tnlObject is deleted.
  Deleting name from tnlString.
  Deleting name from tnlObject.
  Deleting name from tnlObject.
  Deleting name from tnlObject.
  Deleting name in tnlObject.
  Adding problem dependent build config tag to tnl-quickstart.
  Fixing tnl-quickstart.

(I've actually encountered such error...)

The CXX_FLAGS variable does not exist/is unused by cmake.

Parentheses around operator& are necessary due to operator priority

The problem is that for example Arch Linux symlinks python to python3,
which has different syntax (e.g. print is a function instead of a
statement).

Used shorter __cuda_callable__ instead of __host__ __device__ and
testing if HAVE_CUDA is defined.

Conflicts:
	.cproject
	CMakeLists.txt
	install

RowLengths was renamed to CompressedRowsLengths.
OpenMP support wads added to matrix-vector multiplication and to scalar
products.
CSR format can use Cusparse for SpMV.

Adding CUDA architecure and CUDA cores to log.