The usage of algorithms such as MemoryOperations or Reduction is not
bound to a particular container. On the other hand, ArrayIO,
ArrayAssignment, VectorAssignment and StaticArrayAssignment are just
implementation details for the containers - moved into
TNL/Containers/detail/

Also moved ParallelFor, StaticFor, StaticVectorFor, TemplateStaticFor
into TNL/Algorithms/

This will be necessary to avoid code bloat with more than 2 devices
(execution types).

- cudaMemcpy is slower than our ParallelFor kernel for CUDA
- use std::copy and std::equal instead of memcpy and memcmp, but only as
  sequential fallbacks
- use parallel algorithms for containsValue and containsOnlyValue (again
  with sequential fallbacks)

TNL is not supposed to have any external dependencies, so an empty
config file is useless. If some marginal parts of the project (such as
code for image processing) need to depend on some non-standard library,
they should be split into a separate module/project so that the
dependencies can be properly specified.

For now, the macros are specified as compiler parameters. Client
software using the affected headers will have to do the same.

Also added missing 'const' to the getMemoryElement method for host.

Implemented Array:containsOnlyValue.
Restored implementation of ArrayOperations::memoryCompare on host.

Implemented a method Array::checkValue which returns true only if there is an element with given value in the array.