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73 lines
3.2 KiB
Plaintext
73 lines
3.2 KiB
Plaintext
/*!
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\mainpage Trilinos/Kokkos: Shared-memory programming interface and computational kernels
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\section Kokkos_Intro Introduction
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The %Kokkos package has two main components. The first, sometimes
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called "%Kokkos Array" or just "%Kokkos," implements a
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performance-portable shared-memory parallel programming model and data
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containers. The second, called "%Kokkos Classic," consists of
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computational kernels that support the %Tpetra package.
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\section Kokkos_Kokkos The %Kokkos programming model
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%Kokkos implements a performance-portable shared-memory parallel
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programming model and data containers. It lets you write an algorithm
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once, and just change a template parameter to get the optimal data
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layout for your hardware. %Kokkos has back-ends for the following
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parallel programming models:
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- Kokkos::Threads: C++11 Threads (std::thread)
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- Kokkos::OpenMP: OpenMP
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- Kokkos::Cuda: NVIDIA's CUDA programming model for graphics
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processing units (GPUs)
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- Kokkos::Serial: No thread parallelism
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%Kokkos also has optimizations for shared-memory parallel systems with
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nonuniform memory access (NUMA). Its containers can hold data of any
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primitive ("plain old") data type (and some aggregate types). %Kokkos
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Array may be used as a stand-alone programming model.
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%Kokkos' parallel operations include the following:
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- parallel_for: a thread-parallel "for loop"
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- parallel_reduce: a thread-parallel reduction
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- parallel_scan: a thread-parallel prefix scan operation
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as well as expert-level platform-independent interfaces to thread
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"teams," per-team "shared memory," synchronization, and atomic update
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operations.
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%Kokkos' data containers include the following:
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- Kokkos::View: A multidimensional array suitable for thread-parallel
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operations. Its layout (e.g., row-major or column-major) is
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optimized by default for the particular thread-parallel device.
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- Kokkos::Vector: A drop-in replacement for std::vector that eases
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porting from standard sequential C++ data structures to %Kokkos'
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parallel data structures.
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- Kokkos::UnorderedMap: A parallel lookup table comparable in
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functionality to std::unordered_map.
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%Kokkos also uses the above basic containers to implement higher-level
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data structures, like sparse graphs and matrices.
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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.
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\section Kokkos_Classic %Kokkos Classic
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"%Kokkos Classic" consists of computational kernels that support the
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%Tpetra package. These kernels include sparse matrix-vector multiply,
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sparse triangular solve, Gauss-Seidel, and dense vector operations.
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They are templated on the type of objects (\c Scalar) on which they
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operate. This component was not meant to be visible to users; it is
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an implementation detail of the %Tpetra distributed linear algebra
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package.
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%Kokkos Classic also implements a shared-memory parallel programming
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model. This inspired and preceded the %Kokkos programming model
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described in the previous section. Users should consider the %Kokkos
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Classic programming model deprecated, and prefer the new %Kokkos
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programming model.
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*/
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