mirror of
https://github.com/triqs/dft_tools
synced 2024-12-25 22:03:43 +01:00
47cb8a03f7
- Simplify group_indices - Only for C ordered, remove complex compile time. - Could be generalized to non C ordered, but no need. - Fix slice for custom orders. - Generalize the group_indices for the custom order. - Add c_ordered_transposed_view (useful ?) - Improve slice, special for ellipsis (quicker). - Simplify TraversalOrder - Assignement. Specialize one case for speed. - use FORCEINLINE in foreach, according to speed test for clang - add one speed test - Modify iterators for better speed. - along the lines decided for the foreach - update doc.
171 lines
6.8 KiB
C++
171 lines
6.8 KiB
C++
/*******************************************************************************
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*
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* TRIQS: a Toolbox for Research in Interacting Quantum Systems
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*
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* Copyright (C) 2013 by O. Parcollet
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*
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* TRIQS is free software: you can redistribute it and/or modify it under the
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* terms of the GNU General Public License as published by the Free Software
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* Foundation, either version 3 of the License, or (at your option) any later
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* version.
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*
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* TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
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* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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* FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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* details.
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*
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* You should have received a copy of the GNU General Public License along with
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* TRIQS. If not, see <http://www.gnu.org/licenses/>.
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*
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******************************************************************************/
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#ifndef TRIQS_UTILITY_MPI_H
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#define TRIQS_UTILITY_MPI_H
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#include <triqs/utility/c14.hpp>
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#include <boost/mpi.hpp>
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namespace triqs { namespace mpi {
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using boost::mpi::communicator;
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using boost::mpi::environment;
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// transformation type -> mpi types
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template <class T> struct mpi_datatype { static constexpr bool ok=false;};
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#define D(T,MPI_TY) template <> struct mpi_datatype <T>{ static MPI_Datatype invoke() { return MPI_TY;}; static constexpr bool ok=true;};
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D(int,MPI_INT) D(long,MPI_LONG) D(double,MPI_DOUBLE) D(float,MPI_FLOAT) D(std::complex<double>, MPI_DOUBLE_COMPLEX);
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#undef D
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// ok that is simple ...
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inline void barrier(communicator _c) { MPI_Barrier(_c);}
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// a struct to specialize for the implementation for various types...
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template<typename T, typename Enable=void> struct mpi_impl;
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// ------------------------------
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// the final function for users
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// ------------------------------
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// reduce : first the in_place version
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template<typename T> void reduce_in_place(communicator _c, T & a, int root=0) { mpi_impl<T>::reduce_in_place(_c,a,root); }
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inline void reduce_in_place_v(communicator _c) {}
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// try a variadic one. Does not cost much more to code...
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template<typename T0, typename ... T> void reduce_in_place_v(communicator _c, T0 & a0, T& ... a) {
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reduce_in_place(_c,a0,0);
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reduce_in_place_v(_c, a...);
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}
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// reduce : the regular version in term of the in place one (accept views on the fly from b).
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template<typename T, typename U> void reduce (communicator _c, T & a, U && b, int root =0) {
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b = a; reduce_in_place(_c,b,root);
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}
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// all_reduce : first the in_place version
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template<typename T> void all_reduce_in_place(communicator _c, T & a) { mpi_impl<T>::reduce_in_place(_c,a,0); }
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// all_reduce : the regular version in term of the in place one (accept views on the fly from b).
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template<typename T, typename U> void all_reduce (communicator _c, T & a, U && b) { b = a; reduce_in_place(_c,b); }
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// BroadCast
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template<typename T> void broadcast(communicator _c, T & a, int root =0) { mpi_impl<T>::broadcast(_c,a,root); }
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// ----------------------------------------------------------------------
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// the generic implementation : using serialization for recursive action
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// ----------------------------------------------------------------------
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template<typename T, typename Enable> struct mpi_impl {
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#define MAKE_ADAPTOR_AND_FNT(FNT)\
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struct adaptor_##FNT {\
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communicator _c; int root;\
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template<typename RHS> adaptor_##FNT & operator & (RHS & rhs) { mpi_impl<RHS>::FNT(_c, rhs, root); return *this; }\
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};\
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static void FNT (communicator _c, T & a, int root) {\
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auto ad = adaptor_##FNT{_c,root};\
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serialize(ad, a);\
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}
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MAKE_ADAPTOR_AND_FNT(reduce_in_place);
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MAKE_ADAPTOR_AND_FNT(all_reduce_in_place);
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MAKE_ADAPTOR_AND_FNT(broadcast);
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#undef MAKE_ADAPTOR_AND_FNT
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};
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// ------------------------------
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// overload for basic types
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// ------------------------------
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template<typename A> struct mpi_impl<A,ENABLE_IFC(std::is_arithmetic<A>::value || triqs::is_complex<A>::value)> {
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static void reduce_in_place (communicator _c, A & a, int root) {
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MPI_Reduce ((_c.rank()==root ? MPI_IN_PLACE:&a),&a,1, mpi_datatype<A>::invoke(), MPI_SUM, root, _c);
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}
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static void all_reduce_in_place (communicator _c, A & a, int root) {
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MPI_Allreduce (&a,1, mpi_datatype<A>::invoke(), MPI_SUM, _c);
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}
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static void broadcast (communicator _c, A & a, int root) { MPI_Bcast (&a,1, mpi_datatype<A>::invoke(), root, _c); }
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};
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// ------------------------------
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// a boost::mpi implementation
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// ------------------------------
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template<typename A> struct boost_mpi_impl {
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static void reduce_in_place (communicator _c, A & a, int root) {
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boost::mpi::reduce(_c,a,a, std::c14::plus<>(), root);
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}
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static void all_reduce_in_place (communicator _c, A & a, int root) {
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boost::mpi::all_reduce(_c,a,a, std::c14::plus<>(), root);
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}
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static void broadcast (communicator _c, A & a, int root) { boost::mpi::broadcast(_c,a,root);}
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};
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// ------------------------------
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// overload for arrays
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// Stragey : if not contigous, we can i) revert to boost::mpi, ii) fail !??
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// ------------------------------
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// When value_type is a basic type, we can directly call the C API
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template<typename A> struct mpi_impl<A,ENABLE_IFC(mpi_datatype<typename A::value_type>::ok && arrays::is_amv_value_or_view_class<A>::value)> {
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typedef typename A::value_type a_t;
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static void reduce_in_place (communicator _c, A & a, int root) {
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if (!has_contiguous_data(a)) TRIQS_RUNTIME_ERROR << "Non contiguous view in mpi_reduce_in_place";
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auto p = a.data_start();
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MPI_Reduce ((_c.rank()==root ? MPI_IN_PLACE:p),p,a.domain().number_of_elements(), mpi_datatype<a_t>::invoke(), MPI_SUM, root, _c);
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}
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static void all_reduce_in_place (communicator _c, A & a, int root) {
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if (!has_contiguous_data(a)) TRIQS_RUNTIME_ERROR << "Non contiguous view in mpi_reduce_in_place";
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MPI_Allreduce (MPI_IN_PLACE, a.data_start(), a.domain().number_of_elements(), mpi_datatype<a_t>::invoke(), MPI_SUM, _c);
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}
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static void broadcast (communicator _c, A & a, int root) {
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if (!has_contiguous_data(a)) TRIQS_RUNTIME_ERROR << "Non contiguous view in mpi_reduce_in_place";
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MPI_Bcast (a.data_start(),a.domain().number_of_elements(), mpi_datatype<a_t>::invoke(), root, _c);
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}
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};
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// When value_type is NOT a basic type, we revert to boost::mpi
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template<typename A> struct mpi_impl<A,ENABLE_IFC(!mpi_datatype<typename A::value_type>::ok && arrays::is_amv_value_or_view_class<A>::value)> : boost_mpi_impl<A>{};
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// overload for views rvalues (created on the fly)
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template <typename V, int R, typename To, bool W> void reduce_in_place(communicator _c, arrays::array_view<V, R, To, W>&& a, int root = 0) {
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reduce_in_place(_c, a, root);
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}
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template <typename A, typename V, int R, typename To, bool W>
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void reduce(communicator _c, A const& a, arrays::array_view<V, R, To, W>&& b, int root = 0) {
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reduce(_c, a, b, root);
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}
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// to be implemented : scatter, gather for arrays
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}}
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#endif
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