They are not suitable for more than 2 devices/execution types; their design
breaks the Open-Closed Principle. Instead, a type template "Self" was
created, which allows to change any template parameter.

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).

Moved synchronization of smart pointers from Devices::Cuda into TNL::Pointers namespace as free functions

synchronizeDevice() was renamed to synchronizeSmartPointersOnDevice()
for clarity - there are many similarly named functions in CUDA (e.g.
cudaDeviceSynchronize()).

Fixes #46

This is nicer because it more clearly separates data load, computation
and data store. Furthermore, it allows to use instances of std::plus,
std::logical_and, std::logical_or, etc. instead of custom lambda
functions.

Jakub Klinkovský authored 5 years ago and Tomáš Oberhuber committed 5 years ago

Added getView() and getConstView() methods to Array, ArrayView, Vector, VectorView, DistributedArray, DistributedArrayView, DistributedVector and DistributedVectorView

NDArray-style...

TODO: update documentation and examples