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47 lines
1.9 KiB
Markdown
47 lines
1.9 KiB
Markdown
# Grid
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Data parallel C++ mathematical object library
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This library provides data parallel C++ container classes with internal memory layout
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that is transformed to map efficiently to SIMD architectures. CSHIFT facilities
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are provided, similar to HPF and cmfortran, and user control is given over the mapping of
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array indices to both MPI tasks and SIMD processing elements.
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* Identically shaped arrays then be processed with perfect data parallelisation.
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* Such identically shapped arrays are called conformable arrays.
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The transformation is based on the observation that Cartesian array processing involves
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identical processing to be performed on different regions of the Cartesian array.
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The library will both geometrically decompose into MPI tasks and across SIMD lanes.
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Local vector loops are parallelised with OpenMP pragmas.
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Data parallel array operations can then be specified with a SINGLE data parallel paradigm, but
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optimally use MPI, OpenMP and SIMD parallelism under the hood. This is a significant simplification
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for most programmers.
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The layout transformations are parametrised by the SIMD vector length. This adapts according to the architecture.
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Presently SSE2 (128 bit) AVX, AVX2 (256 bit) and IMCI and AVX512 (512 bit) targets are supported.
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These are presented as
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vRealF, vRealD, vComplexF, vComplexD
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internal vector data types. These may be useful in themselves for other programmers.
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The corresponding scalar types are named
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RealF, RealD, ComplexF, ComplexD
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MPI, OpenMP, and SIMD parallelism are present in the library.
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You can give `configure' initial values for configuration parameters
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by setting variables in the command line or in the environment. Here
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are examples:
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./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx" --enable-simd=AVX1
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./configure CXX=clang++ CXXFLAGS="-std=c++11 -O3 -mavx2" --enable-simd=AVX2
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./configure CXX=icpc CXXFLAGS="-std=c++11 -O3 -mmic" --enable-simd=AVX512 --host=none
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