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495 lines
16 KiB
C++
495 lines
16 KiB
C++
/*************************************************************************************
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Grid physics library, www.github.com/paboyle/Grid
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Source file: ./lib/communicator/Communicator_mpi.cc
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Copyright (C) 2015
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Author: Peter Boyle <paboyle@ph.ed.ac.uk>
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This program is free software; you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation; either version 2 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License along
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with this program; if not, write to the Free Software Foundation, Inc.,
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51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
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See the full license in the file "LICENSE" in the top level distribution directory
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*************************************************************************************/
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/* END LEGAL */
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#include <Grid/GridCore.h>
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#include <Grid/communicator/SharedMemory.h>
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namespace Grid {
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Grid_MPI_Comm CartesianCommunicator::communicator_world;
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////////////////////////////////////////////
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// First initialise of comms system
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////////////////////////////////////////////
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void CartesianCommunicator::Init(int *argc, char ***argv)
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{
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int flag;
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int provided;
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MPI_Initialized(&flag); // needed to coexist with other libs apparently
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if ( !flag ) {
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MPI_Init_thread(argc,argv,MPI_THREAD_MULTIPLE,&provided);
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assert (provided == MPI_THREAD_MULTIPLE);
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}
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Grid_quiesce_nodes();
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MPI_Comm_dup (MPI_COMM_WORLD,&communicator_world);
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GlobalSharedMemory::Init(communicator_world);
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GlobalSharedMemory::SharedMemoryAllocate(
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GlobalSharedMemory::MAX_MPI_SHM_BYTES,
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GlobalSharedMemory::Hugepages);
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}
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///////////////////////////////////////////////////////////////////////////
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// Use cartesian communicators now even in MPI3
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///////////////////////////////////////////////////////////////////////////
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void CartesianCommunicator::ShiftedRanks(int dim,int shift,int &source,int &dest)
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{
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int ierr=MPI_Cart_shift(communicator,dim,shift,&source,&dest);
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assert(ierr==0);
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}
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int CartesianCommunicator::RankFromProcessorCoor(std::vector<int> &coor)
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{
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int rank;
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int ierr=MPI_Cart_rank (communicator, &coor[0], &rank);
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assert(ierr==0);
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return rank;
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}
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void CartesianCommunicator::ProcessorCoorFromRank(int rank, std::vector<int> &coor)
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{
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coor.resize(_ndimension);
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int ierr=MPI_Cart_coords (communicator, rank, _ndimension,&coor[0]);
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assert(ierr==0);
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}
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////////////////////////////////////////////////////////////////////////////////////////////////////////
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// Initialises from communicator_world
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////////////////////////////////////////////////////////////////////////////////////////////////////////
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CartesianCommunicator::CartesianCommunicator(const std::vector<int> &processors)
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{
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MPI_Comm optimal_comm;
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GlobalSharedMemory::OptimalCommunicator (processors,optimal_comm); // Remap using the shared memory optimising routine
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InitFromMPICommunicator(processors,optimal_comm);
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SetCommunicator(optimal_comm);
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}
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//////////////////////////////////
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// Try to subdivide communicator
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//////////////////////////////////
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CartesianCommunicator::CartesianCommunicator(const std::vector<int> &processors,const CartesianCommunicator &parent,int &srank)
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{
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_ndimension = processors.size();
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int parent_ndimension = parent._ndimension; assert(_ndimension >= parent._ndimension);
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std::vector<int> parent_processor_coor(_ndimension,0);
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std::vector<int> parent_processors (_ndimension,1);
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// Can make 5d grid from 4d etc...
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int pad = _ndimension-parent_ndimension;
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for(int d=0;d<parent_ndimension;d++){
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parent_processor_coor[pad+d]=parent._processor_coor[d];
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parent_processors [pad+d]=parent._processors[d];
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}
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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// split the communicator
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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// int Nparent = parent._processors ;
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// std::cout << " splitting from communicator "<<parent.communicator <<std::endl;
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int Nparent;
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MPI_Comm_size(parent.communicator,&Nparent);
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// std::cout << " Parent size "<<Nparent <<std::endl;
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int childsize=1;
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for(int d=0;d<processors.size();d++) {
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childsize *= processors[d];
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}
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int Nchild = Nparent/childsize;
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assert (childsize * Nchild == Nparent);
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// std::cout << " child size "<<childsize <<std::endl;
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std::vector<int> ccoor(_ndimension); // coor within subcommunicator
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std::vector<int> scoor(_ndimension); // coor of split within parent
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std::vector<int> ssize(_ndimension); // coor of split within parent
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for(int d=0;d<_ndimension;d++){
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ccoor[d] = parent_processor_coor[d] % processors[d];
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scoor[d] = parent_processor_coor[d] / processors[d];
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ssize[d] = parent_processors[d] / processors[d];
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}
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// rank within subcomm ; srank is rank of subcomm within blocks of subcomms
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int crank;
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// Mpi uses the reverse Lexico convention to us; so reversed routines called
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Lexicographic::IndexFromCoorReversed(ccoor,crank,processors); // processors is the split grid dimensions
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Lexicographic::IndexFromCoorReversed(scoor,srank,ssize); // ssize is the number of split grids
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MPI_Comm comm_split;
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if ( Nchild > 1 ) {
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if(0){
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std::cout << GridLogMessage<<"Child communicator of "<< std::hex << parent.communicator << std::dec<<std::endl;
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std::cout << GridLogMessage<<" parent grid["<< parent._ndimension<<"] ";
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for(int d=0;d<parent._ndimension;d++) std::cout << parent._processors[d] << " ";
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std::cout<<std::endl;
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std::cout << GridLogMessage<<" child grid["<< _ndimension <<"] ";
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for(int d=0;d<processors.size();d++) std::cout << processors[d] << " ";
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std::cout<<std::endl;
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std::cout << GridLogMessage<<" old rank "<< parent._processor<<" coor ["<< parent._ndimension <<"] ";
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for(int d=0;d<parent._ndimension;d++) std::cout << parent._processor_coor[d] << " ";
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std::cout<<std::endl;
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std::cout << GridLogMessage<<" new split "<< srank<<" scoor ["<< _ndimension <<"] ";
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for(int d=0;d<processors.size();d++) std::cout << scoor[d] << " ";
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std::cout<<std::endl;
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std::cout << GridLogMessage<<" new rank "<< crank<<" coor ["<< _ndimension <<"] ";
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for(int d=0;d<processors.size();d++) std::cout << ccoor[d] << " ";
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std::cout<<std::endl;
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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// Declare victory
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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std::cout << GridLogMessage<<"Divided communicator "<< parent._Nprocessors<<" into "
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<< Nchild <<" communicators with " << childsize << " ranks"<<std::endl;
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std::cout << " Split communicator " <<comm_split <<std::endl;
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}
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////////////////////////////////////////////////////////////////
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// Split the communicator
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////////////////////////////////////////////////////////////////
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int ierr= MPI_Comm_split(parent.communicator,srank,crank,&comm_split);
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assert(ierr==0);
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} else {
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srank = 0;
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comm_split = parent.communicator;
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// std::cout << " Inherited communicator " <<comm_split <<std::endl;
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}
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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// Set up from the new split communicator
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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InitFromMPICommunicator(processors,comm_split);
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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// Take the right SHM buffers
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//////////////////////////////////////////////////////////////////////////////////////////////////////
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SetCommunicator(comm_split);
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if(0){
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std::cout << " ndim " <<_ndimension<<" " << parent._ndimension << std::endl;
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for(int d=0;d<processors.size();d++){
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std::cout << d<< " " << _processor_coor[d] <<" " << ccoor[d]<<std::endl;
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}
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}
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for(int d=0;d<processors.size();d++){
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assert(_processor_coor[d] == ccoor[d] );
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}
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}
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void CartesianCommunicator::InitFromMPICommunicator(const std::vector<int> &processors, MPI_Comm communicator_base)
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{
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_ndimension = processors.size();
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_processor_coor.resize(_ndimension);
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/////////////////////////////////
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// Count the requested nodes
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/////////////////////////////////
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_Nprocessors=1;
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_processors = processors;
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for(int i=0;i<_ndimension;i++){
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_Nprocessors*=_processors[i];
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}
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std::vector<int> periodic(_ndimension,1);
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MPI_Cart_create(communicator_base, _ndimension,&_processors[0],&periodic[0],0,&communicator);
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MPI_Comm_rank(communicator,&_processor);
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MPI_Cart_coords(communicator,_processor,_ndimension,&_processor_coor[0]);
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if ( 0 && (communicator_base != communicator_world) ) {
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std::cout << "InitFromMPICommunicator Cartesian communicator created with a non-world communicator"<<std::endl;
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std::cout << " new communicator rank "<<_processor<< " coor ["<<_ndimension<<"] ";
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for(int d=0;d<_processors.size();d++){
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std::cout << _processor_coor[d]<<" ";
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}
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std::cout << std::endl;
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}
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int Size;
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MPI_Comm_size(communicator,&Size);
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communicator_halo.resize (2*_ndimension);
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for(int i=0;i<_ndimension*2;i++){
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MPI_Comm_dup(communicator,&communicator_halo[i]);
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}
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assert(Size==_Nprocessors);
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}
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CartesianCommunicator::~CartesianCommunicator()
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{
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int MPI_is_finalised;
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MPI_Finalized(&MPI_is_finalised);
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if (communicator && !MPI_is_finalised) {
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MPI_Comm_free(&communicator);
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for(int i=0;i<communicator_halo.size();i++){
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MPI_Comm_free(&communicator_halo[i]);
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}
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}
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}
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void CartesianCommunicator::GlobalSum(uint32_t &u){
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int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT32_T,MPI_SUM,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalSum(uint64_t &u){
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int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT64_T,MPI_SUM,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalXOR(uint32_t &u){
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int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT32_T,MPI_BXOR,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalXOR(uint64_t &u){
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int ierr=MPI_Allreduce(MPI_IN_PLACE,&u,1,MPI_UINT64_T,MPI_BXOR,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalSum(float &f){
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int ierr=MPI_Allreduce(MPI_IN_PLACE,&f,1,MPI_FLOAT,MPI_SUM,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalSumVector(float *f,int N)
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{
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int ierr=MPI_Allreduce(MPI_IN_PLACE,f,N,MPI_FLOAT,MPI_SUM,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalSum(double &d)
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{
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int ierr = MPI_Allreduce(MPI_IN_PLACE,&d,1,MPI_DOUBLE,MPI_SUM,communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::GlobalSumVector(double *d,int N)
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{
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int ierr = MPI_Allreduce(MPI_IN_PLACE,d,N,MPI_DOUBLE,MPI_SUM,communicator);
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assert(ierr==0);
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}
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// Basic Halo comms primitive
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void CartesianCommunicator::SendToRecvFrom(void *xmit,
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int dest,
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void *recv,
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int from,
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int bytes)
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{
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std::vector<CommsRequest_t> reqs(0);
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// unsigned long xcrc = crc32(0L, Z_NULL, 0);
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// unsigned long rcrc = crc32(0L, Z_NULL, 0);
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// xcrc = crc32(xcrc,(unsigned char *)xmit,bytes);
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SendToRecvFromBegin(reqs,xmit,dest,recv,from,bytes);
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SendToRecvFromComplete(reqs);
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// rcrc = crc32(rcrc,(unsigned char *)recv,bytes);
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// printf("proc %d SendToRecvFrom %d bytes %lx %lx\n",_processor,bytes,xcrc,rcrc);
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}
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void CartesianCommunicator::SendRecvPacket(void *xmit,
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void *recv,
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int sender,
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int receiver,
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int bytes)
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{
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MPI_Status stat;
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assert(sender != receiver);
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int tag = sender;
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if ( _processor == sender ) {
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MPI_Send(xmit, bytes, MPI_CHAR,receiver,tag,communicator);
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}
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if ( _processor == receiver ) {
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MPI_Recv(recv, bytes, MPI_CHAR,sender,tag,communicator,&stat);
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}
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}
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// Basic Halo comms primitive
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void CartesianCommunicator::SendToRecvFromBegin(std::vector<CommsRequest_t> &list,
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void *xmit,
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int dest,
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void *recv,
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int from,
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int bytes)
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{
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int myrank = _processor;
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int ierr;
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if ( CommunicatorPolicy == CommunicatorPolicyConcurrent ) {
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MPI_Request xrq;
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MPI_Request rrq;
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ierr =MPI_Irecv(recv, bytes, MPI_CHAR,from,from,communicator,&rrq);
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ierr|=MPI_Isend(xmit, bytes, MPI_CHAR,dest,_processor,communicator,&xrq);
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assert(ierr==0);
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list.push_back(xrq);
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list.push_back(rrq);
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} else {
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// Give the CPU to MPI immediately; can use threads to overlap optionally
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ierr=MPI_Sendrecv(xmit,bytes,MPI_CHAR,dest,myrank,
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recv,bytes,MPI_CHAR,from, from,
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communicator,MPI_STATUS_IGNORE);
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assert(ierr==0);
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}
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}
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double CartesianCommunicator::StencilSendToRecvFrom( void *xmit,
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int dest,
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void *recv,
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int from,
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int bytes,int dir)
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{
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std::vector<CommsRequest_t> list;
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double offbytes = StencilSendToRecvFromBegin(list,xmit,dest,recv,from,bytes,dir);
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StencilSendToRecvFromComplete(list,dir);
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return offbytes;
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}
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double CartesianCommunicator::StencilSendToRecvFromBegin(std::vector<CommsRequest_t> &list,
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void *xmit,
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int dest,
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void *recv,
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int from,
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int bytes,int dir)
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{
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int ncomm =communicator_halo.size();
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int commdir=dir%ncomm;
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MPI_Request xrq;
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MPI_Request rrq;
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int ierr;
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int gdest = ShmRanks[dest];
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int gfrom = ShmRanks[from];
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int gme = ShmRanks[_processor];
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assert(dest != _processor);
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assert(from != _processor);
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assert(gme == ShmRank);
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double off_node_bytes=0.0;
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if ( gfrom ==MPI_UNDEFINED) {
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ierr=MPI_Irecv(recv, bytes, MPI_CHAR,from,from,communicator_halo[commdir],&rrq);
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assert(ierr==0);
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list.push_back(rrq);
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off_node_bytes+=bytes;
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}
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if ( gdest == MPI_UNDEFINED ) {
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ierr =MPI_Isend(xmit, bytes, MPI_CHAR,dest,_processor,communicator_halo[commdir],&xrq);
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assert(ierr==0);
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list.push_back(xrq);
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off_node_bytes+=bytes;
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}
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if ( CommunicatorPolicy == CommunicatorPolicySequential ) {
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this->StencilSendToRecvFromComplete(list,dir);
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}
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return off_node_bytes;
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}
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void CartesianCommunicator::StencilSendToRecvFromComplete(std::vector<CommsRequest_t> &waitall,int dir)
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{
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SendToRecvFromComplete(waitall);
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}
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void CartesianCommunicator::StencilBarrier(void)
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{
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MPI_Barrier (ShmComm);
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}
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void CartesianCommunicator::SendToRecvFromComplete(std::vector<CommsRequest_t> &list)
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{
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int nreq=list.size();
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if (nreq==0) return;
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std::vector<MPI_Status> status(nreq);
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int ierr = MPI_Waitall(nreq,&list[0],&status[0]);
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assert(ierr==0);
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list.resize(0);
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}
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void CartesianCommunicator::Barrier(void)
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{
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int ierr = MPI_Barrier(communicator);
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assert(ierr==0);
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}
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void CartesianCommunicator::Broadcast(int root,void* data, int bytes)
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{
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int ierr=MPI_Bcast(data,
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bytes,
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MPI_BYTE,
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root,
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communicator);
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assert(ierr==0);
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}
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int CartesianCommunicator::RankWorld(void){
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int r;
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MPI_Comm_rank(communicator_world,&r);
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return r;
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}
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void CartesianCommunicator::BroadcastWorld(int root,void* data, int bytes)
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{
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int ierr= MPI_Bcast(data,
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bytes,
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MPI_BYTE,
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root,
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communicator_world);
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assert(ierr==0);
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}
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void CartesianCommunicator::AllToAll(int dim,void *in,void *out,uint64_t words,uint64_t bytes)
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{
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std::vector<int> row(_ndimension,1);
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assert(dim>=0 && dim<_ndimension);
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// Split the communicator
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row[dim] = _processors[dim];
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int me;
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CartesianCommunicator Comm(row,*this,me);
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Comm.AllToAll(in,out,words,bytes);
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}
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void CartesianCommunicator::AllToAll(void *in,void *out,uint64_t words,uint64_t bytes)
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{
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// MPI is a pain and uses "int" arguments
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// 64*64*64*128*16 == 500Million elements of data.
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// When 24*4 bytes multiples get 50x 10^9 >>> 2x10^9 Y2K bug.
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// (Turns up on 32^3 x 64 Gparity too)
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MPI_Datatype object;
|
|
int iwords;
|
|
int ibytes;
|
|
iwords = words;
|
|
ibytes = bytes;
|
|
assert(words == iwords); // safe to cast to int ?
|
|
assert(bytes == ibytes); // safe to cast to int ?
|
|
MPI_Type_contiguous(ibytes,MPI_BYTE,&object);
|
|
MPI_Type_commit(&object);
|
|
MPI_Alltoall(in,iwords,object,out,iwords,object,communicator);
|
|
MPI_Type_free(&object);
|
|
}
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|
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|
|
|
|
|
}
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