...and some simplifications in tnlSolverStarter - needs more!

* origin/master:
  Fixing build script.
  Adding OpenMP to vector operations.
  Fixing a bug in host and device arrays comparison.
  Fixing the DICOM reader.
  Fixing DCMTK code to work when DICOM support is not enabled.
  Fixing #1 - tnl-dicom-reader, tnl-image-converter
  Implementing the DICOM reader.
  Implementing the DICOM reader.
  Refactoring code for the DICOM format support.
  Addign DICOM support - TNL can be succesfully build now.
  JPEG format is working.
  Implementing JPEG image write.
  Implementing JPEG image.
  Adding JPEG format support.
  Adding PNG format support.
  Adding conversion from .tnl file to image.
  Implementing image converter.
  Implementing image converter.
  Implementing the image converter.
  Adding image converter.

* master:
  Tuning Ellpack formats.
  Tuning Ellpack format.
  Fixing bug in tnlVector::operator !=.
  Optimizing CUDA L2 norm.
  Adding banchmark for CUDA lp norm.

Conflicts:
	build
	src/core/CMakeLists.txt

* master:
  Optimizing L1 and L2 norms in CUDA.

The system is actually solved for t+tau, not t.

The nextIteration() method should not be called here because it
increments the iteration counter.

* master: (34 commits)
  Fixing compilation with nvcc.
  Fixing C++11 flag in CMakeLists.
  Refactoring tnlFunction.
  Refactoring system for function types.
  Debuging mesh.
  Renaming Ellpack network to indexed multimap.
  Implementing superentity indecis storage in storage network (=indexed multimap)
  Fixing missing superentities of vertices.
  Inserting the Ellpack network to the mesh.
  Renaming Ellpack graph to Ellpack network.
  Adding sparse Ellpack graph.
  Refactoring mesh entity.
  Refactoring the mesh.
  Refactoring the mesh.
  Refactoring the mesh.
  Refactoring the mesh.
  Refactoring the mesh.
  Refactoring the mesh.
  Refactoring the mesh.
  Fixing mesh config validator. Adding mesh simplex.
  ...

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.

Conflicts:
	src/mesh/layers/tnlMeshStorageLayer.h
	src/mesh/layers/tnlMeshSubentityStorageLayer.h
	src/mesh/layers/tnlMeshSuperentityStorageLayer.h
	src/mesh/tnlMesh.h
	tests/unit-tests/mesh/tnlMeshTester.h

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.