/*! 
\mainpage Trilinos/Kokkos: Shared-memory programming interface and computational kernels

\section Kokkos_Intro Introduction

The %Kokkos package has two main components.  The first, sometimes
called "%Kokkos Array" or just "%Kokkos," implements a
performance-portable shared-memory parallel programming model and data
containers.  The second, called "%Kokkos Classic," consists of
computational kernels that support the %Tpetra package.

\section Kokkos_Kokkos The %Kokkos programming model

%Kokkos implements a performance-portable shared-memory parallel
programming model and data containers.  It lets you write an algorithm
once, and just change a template parameter to get the optimal data
layout for your hardware.  %Kokkos has back-ends for the following
parallel programming models:

- Kokkos::Threads: C++11 Threads (std::thread)
- Kokkos::OpenMP: OpenMP
- Kokkos::Cuda: NVIDIA's CUDA programming model for graphics
  processing units (GPUs)
- Kokkos::Serial: No thread parallelism

%Kokkos also has optimizations for shared-memory parallel systems with
nonuniform memory access (NUMA).  Its containers can hold data of any
primitive ("plain old") data type (and some aggregate types).  %Kokkos
Array may be used as a stand-alone programming model.

%Kokkos' parallel operations include the following:

- parallel_for: a thread-parallel "for loop"
- parallel_reduce: a thread-parallel reduction
- parallel_scan: a thread-parallel prefix scan operation

as well as expert-level platform-independent interfaces to thread
"teams," per-team "shared memory," synchronization, and atomic update
operations.

%Kokkos' data containers include the following:

- Kokkos::View: A multidimensional array suitable for thread-parallel
  operations.  Its layout (e.g., row-major or column-major) is
  optimized by default for the particular thread-parallel device.
- Kokkos::Vector: A drop-in replacement for std::vector that eases
  porting from standard sequential C++ data structures to %Kokkos'
  parallel data structures.
- Kokkos::UnorderedMap: A parallel lookup table comparable in
  functionality to std::unordered_map.

%Kokkos also uses the above basic containers to implement higher-level
data structures, like sparse graphs and matrices.

A good place to start learning about %Kokkos would be <a href="http://trilinos.sandia.gov/events/trilinos_user_group_2013/presentations/2013-11-TUG-Kokkos-Tutorial.pdf">these tutorial slides</a> from the 2013 Trilinos Users' Group meeting.

\section Kokkos_Classic %Kokkos Classic

"%Kokkos Classic" consists of computational kernels that support the
%Tpetra package.  These kernels include sparse matrix-vector multiply,
sparse triangular solve, Gauss-Seidel, and dense vector operations.
They are templated on the type of objects (\c Scalar) on which they
operate.  This component was not meant to be visible to users; it is
an implementation detail of the %Tpetra distributed linear algebra
package.  

%Kokkos Classic also implements a shared-memory parallel programming
model.  This inspired and preceded the %Kokkos programming model
described in the previous section.  Users should consider the %Kokkos
Classic programming model deprecated, and prefer the new %Kokkos
programming model.
*/