MatrixNnzStructure.cc 12 KB
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/******************************************************************************
 *
 * AMDiS - Adaptive multidimensional simulations
 *
 * Copyright (C) 2013 Dresden University of Technology. All Rights Reserved.
 * Web: https://fusionforge.zih.tu-dresden.de/projects/amdis
 *
 * Authors: 
 * Simon Vey, Thomas Witkowski, Andreas Naumann, Simon Praetorius, et al.
 *
 * This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
 * WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
 *
 *
 * This file is part of AMDiS
 *
 * See also license.opensource.txt in the distribution.
 * 
 ******************************************************************************/
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#include <algorithm>
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#include "Global.h"
#include "DOFMatrix.h"
#include "parallel/MatrixNnzStructure.h"
#include "parallel/ParallelDofMapping.h"

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using namespace std;

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namespace AMDiS { namespace Parallel {
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  MatrixNnzStructure::~MatrixNnzStructure()
  {
    clear();
  }


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  void MatrixNnzStructure::clear()
  {
    if (dnnz) {
      delete [] dnnz;
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      dnnz = nullptr;
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    }
    
    if (onnz) {
      delete [] onnz;
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      onnz = nullptr;
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    }
  }


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  void MatrixNnzStructure::create(Matrix<DOFMatrix*> &mat,
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				  ParallelDofMapping &rowDofMap,
				  ParallelDofMapping &colDofMap,
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				  PeriodicMap *perMap,
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				  const ElementObjectDatabase& elObjDb,
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				  bool localMatrix)
  {
    FUNCNAME("MatrixNnzStructure::create()");

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    int nRankRows = rowDofMap.getRankDofs(); 		// Number of DOFs owned by rank.
    int rankStartRowIndex = rowDofMap.getStartDofs();	// Smallest global index of a DOF owned by the rank.
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    int nRankCols = colDofMap.getRankDofs();
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    int nOverallCols = colDofMap.getOverallDofs();	// Number of global DOFs (this value is thus the same on all ranks).
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    int rankStartColIndex = colDofMap.getStartDofs();

    create(nRankRows, (!localMatrix ? nRankRows : -1));

    using mtl::tag::row; using mtl::tag::nz; using mtl::begin; using mtl::end;
    namespace traits = mtl::traits;
    typedef DOFMatrix::base_matrix_type Matrix;
    typedef traits::range_generator<row, Matrix>::type cursor_type;
    typedef traits::range_generator<nz, cursor_type>::type icursor_type;

    typedef vector<pair<int, int> > MatrixNnzEntry;
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//     typedef map<int, DofContainer> RankToDofContainer;
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    // Stores to each rank a list of nnz entries (i.e. pairs of row and column
    // index) that this rank will send to. These nnz entries will be assembled
    // on this rank, but because the row DOFs are not DOFs of this rank they 
    // will be send to the owner of the row DOFs.
    map<int, MatrixNnzEntry> sendMatrixEntry;

    // Maps to each DOF that must be send to another rank the rank number of the
    // receiving rank.
    map<pair<DegreeOfFreedom, int>, int> sendDofToRank;

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    int nComponents = mat.getNumRows();
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    // First, create for all ranks, to which we send data to, MatrixNnzEntry 
    // object with 0 entries.
    for (int i = 0; i < nComponents; i++) {
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      const FiniteElemSpace* feSpace = nullptr;
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      for (int j = 0; j < nComponents; j++)
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	if (mat[i][j])
	  feSpace = mat[i][j]->getRowFeSpace();
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      TEST_EXIT_DBG(feSpace)("No FE space found!\n");

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      for (DofComm::Iterator it(rowDofMap.getDofComm().getRecvDofs(), feSpace);
	   !it.end(); it.nextRank()) {
	sendMatrixEntry[it.getRank()].resize(0);
	
	for (; !it.endDofIter(); it.nextDof())
	  sendDofToRank[make_pair(it.getDofIndex(), i)] = it.getRank();
      }
    }

    // Create list of ranks from which we receive data from.
    std::set<int> recvFromRank;
    for (int i = 0; i < nComponents; i++)  {
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      const FiniteElemSpace* feSpace = nullptr;
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      for (int j = 0; j < nComponents; j++)
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	if (mat[i][j])
	  feSpace = mat[i][j]->getRowFeSpace();
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      for (DofComm::Iterator it(rowDofMap.getDofComm().getSendDofs(), feSpace);
	   !it.end(); it.nextRank())
	recvFromRank.insert(it.getRank());
    }


    // === Traverse matrices to create nnz data. ===

    for (int rowComp = 0; rowComp < nComponents; rowComp++) {
      for (int colComp = 0; colComp < nComponents; colComp++) {
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	DOFMatrix *dofMat = mat[rowComp][colComp];
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 	if (!dofMat)
	  continue;

	const FiniteElemSpace *rowFeSpace = dofMat->getRowFeSpace();
	const FiniteElemSpace *colFeSpace = dofMat->getColFeSpace();
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	if (rowDofMap.isDefinedFor(rowComp) == false ||
	    colDofMap.isDefinedFor(colComp) == false)
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	  continue;
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	// === Prepare MTL4 iterators for the current DOF matrix. ===

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	Matrix baseMat = dofMat->getBaseMatrix(); // TBD: warum hier keine Referenz?
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	traits::col<Matrix>::type getCol(baseMat);
	traits::row<Matrix>::type getRow(baseMat);
	
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	traits::const_value<Matrix>::type value(baseMat);  
	cursor_type cursor = begin<row>(baseMat);
	cursor_type cend = end<row>(baseMat);


	// === Iterate on all DOFs of the row mapping. ===

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	DofMap::iterator rowIt = rowDofMap[rowComp].begin();
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	DofMap::iterator rowEndIt = rowDofMap[rowComp].end();
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	for (; rowIt != rowEndIt; ++rowIt) {

	  // Go to the corresponding matrix row (note, both the mapping and the
	  // matrix rows are stored in increasing order).
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	  while (cursor.value() != rowIt->first)
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	    ++cursor;
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	  size_t _row = cursor.value();
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	  // The corresponding global matrix row index of the current row DOF.
	  int petscRowIdx = 0;
	  if (localMatrix) {
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	    petscRowIdx = rowDofMap.getLocalMatIndex(rowComp, _row);
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	  } else {
	    if (rowDofMap.isMatIndexFromGlobal())
	      petscRowIdx = rowDofMap.getMatIndex(rowComp, rowIt->second.global);
	    else
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	      petscRowIdx = rowDofMap.getMatIndex(rowComp, _row);
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	  }

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	  // Set of periodic row associations (is empty, if row DOF is not 
	  // periodic.
	  std::set<int> perRowAsc;
	  if (perMap)
	    perMap->fillAssociations(rowFeSpace, rowIt->second.global, elObjDb, perRowAsc);
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	  if (localMatrix || rowDofMap[rowComp].isRankDof(_row)) {
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	    // === The current row DOF is a rank DOF, so create the       ===
	    // === corresponding nnz values directly on rank's nnz data.  ===
	    
	    // This is the local row index of the local PETSc matrix.
	    int localPetscRowIdx = petscRowIdx;

	    if (localMatrix == false)
	      localPetscRowIdx -= rankStartRowIndex;
	    
	    TEST_EXIT_DBG(localPetscRowIdx >= 0 && localPetscRowIdx < nRankRows)
	      ("Should not happen! \n Debug info: DOF = %d   globalRowIndx = %d   petscRowIdx = %d   localPetscRowIdx = %d   rStart = %d   compontens = %d from %d   nRankRows = %d\n",
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	       _row,
	       rowDofMap[rowComp][_row].global,
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	       petscRowIdx, 
	       localPetscRowIdx, 
	       rankStartRowIndex,
	       rowComp,
	       nComponents, 
	       nRankRows);
	    

	    if (localMatrix) {
	      for (icursor_type icursor = begin<nz>(cursor), 
		     icend = end<nz>(cursor); icursor != icend; ++icursor)
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		if (colDofMap[colComp].isSet(getCol(*icursor)))
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		  dnnz[localPetscRowIdx]++;	      
	    } else {
	      MultiIndex colDofIndex;

	      // Traverse all non zero entries in this row.
	      for (icursor_type icursor = begin<nz>(cursor), 
		     icend = end<nz>(cursor); icursor != icend; ++icursor) {
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		if (colDofMap[colComp].find(getCol(*icursor), colDofIndex) == false)
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		  continue;
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		// Set of periodic row associations (is empty, if row DOF is not 
		// periodic.
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		std::set<int> perColAsc = perRowAsc;
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		if (perMap)
		  perMap->fillAssociations(colFeSpace, colDofIndex.global, elObjDb, perColAsc);
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		if (perColAsc.empty()) {
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		  if (colDofMap[colComp].isRankDof(getCol(*icursor)))
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		    dnnz[localPetscRowIdx]++;
		  else
		    onnz[localPetscRowIdx]++;
		} else {
		  vector<int> newCols;
		  perMap->mapDof(colFeSpace, colDofIndex.global, perColAsc, newCols);
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		  for (size_t aa = 0; aa < newCols.size(); aa++) {
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		    int petscColIdx = colDofMap.getMatIndex(colComp, newCols[aa]);
		    
		    // The row DOF is a rank DOF, if also the column is a rank DOF, 
		    // increment the diagNnz values for this row, 
		    // otherwise the offdiagNnz value.
		    if (petscColIdx >= rankStartColIndex && 
			petscColIdx < rankStartColIndex + nRankCols)
		      dnnz[localPetscRowIdx]++;
		    else
		      onnz[localPetscRowIdx]++;
		  }
		}
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	      }
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 	      if (!perRowAsc.empty()) {
		vector<int> newRows;
		perMap->mapDof(rowFeSpace, rowIt->second.global, perRowAsc, newRows);
		
		dnnz[localPetscRowIdx] += 
		  (newRows.size() - 1) * (onnz[localPetscRowIdx] + dnnz[localPetscRowIdx]);
 	      }
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	    }
	  } else {
	    // === The current row DOF is not a rank DOF, i.e., its values   ===
	    // === are also created on this rank, but afterthere they will   ===
	    // === be send to another rank. So we need to send also the      ===
	    // === corresponding nnz structure of this row to the corres-    ===
	    // === ponding rank.                                             ===
	    
	    // Send all non zero entries to the member of the row DOF.
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	    int sendToRank = sendDofToRank[make_pair(cursor.value(), rowComp)];
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	    MultiIndex colDofIndex;

	    for (icursor_type icursor = begin<nz>(cursor), 
		   icend = end<nz>(cursor); icursor != icend; ++icursor) {
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	      if (colDofMap[colComp].find(getCol(*icursor), colDofIndex) == false)
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		continue;

	      int petscColIdx = (colDofMap.isMatIndexFromGlobal() ? 
				 colDofMap.getMatIndex(colComp, colDofIndex.global) :
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				 colDofMap.getMatIndex(colComp, getCol(*icursor)));
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	      sendMatrixEntry[sendToRank].
		push_back(make_pair(petscRowIdx, petscColIdx));
	    }
	    
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	  } // if (isRankDof[cursor.value()]) ... else ...
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	} // for each row in mat[i][j]
      } 
    }


    if (localMatrix == false) {
      // === Send and recv the nnz row structure to/from other ranks. ===
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      StdMpi<MatrixNnzEntry> stdMpi(rowDofMap.getMpiComm());
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      stdMpi.send(sendMatrixEntry);
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      for (std::set<int>::iterator it = recvFromRank.begin(); 
	   it != recvFromRank.end(); ++it)
	stdMpi.recv(*it);
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      stdMpi.startCommunication();     
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      // === Evaluate the nnz structure this rank got from other ranks and add ===
      // === it to the PETSc nnz data structure.                               ===
      
      for (map<int, MatrixNnzEntry>::iterator it = stdMpi.getRecvData().begin();
	   it != stdMpi.getRecvData().end(); ++it) {
	if (it->second.size() > 0) {
	  for (unsigned int i = 0; i < it->second.size(); i++) {
	    int r = it->second[i].first;
	    int c = it->second[i].second;
	    
	    int localRowIdx = r - rankStartRowIndex;
	    
	    TEST_EXIT_DBG(localRowIdx >= 0 && localRowIdx < nRankRows)
	      ("Got row index %d/%d (nRankRows = %d) from rank %d. Should not happen!\n",
	       r, localRowIdx, nRankRows, it->first);
	    
	    if (c < rankStartColIndex || c >= rankStartColIndex + nRankCols)
	      onnz[localRowIdx]++;
	    else
	      dnnz[localRowIdx]++;
	  }
	}
      }
    }

    // The above algorithm for calculating the number of nnz per row over-
    // approximates the value, i.e., the number is always equal or larger to 
    // the real number of nnz values in the global parallel matrix. For small
    // matrices, the problem may arise, that the result is larger than the
    // number of elements in a row. This is fixed in the following.

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    for (int i = 0; i < nRankRows; i++) {
      dnnz[i] = std::min(dnnz[i], nRankCols);
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      if (onnz)
	onnz[i] = std::min(onnz[i], nOverallCols - nRankCols);
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    }
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#if (DEBUG != 0)
    int nMax = 0; 
    int nSum = 0;
    for (int i = 0; i < nRankRows; i++) {
      nMax = std::max(nMax, dnnz[i]);
      nSum += dnnz[i];
    }

    MSG("NNZ in diag block: max = %d, avrg = %.0f\n",
	nMax, (nSum > 0 ? (static_cast<double>(nSum) / nRankRows) : 0));

    if (!localMatrix) {
      nMax = 0;
      nSum = 0;

      for (int i = 0; i < nRankRows; i++) {
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	nMax = std::max(nMax, onnz[i]);
	nSum += onnz[i];
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      }

      MSG("NNZ in offdiag block: max = %d, avrg = %.0f\n",
	  nMax, (nSum > 0 ? (static_cast<double>(nSum) / nRankRows) : 0));     
    }
#endif
  }


  void MatrixNnzStructure::create(int nRows0, int nRows1)
  {
    if (nRows0 == 0)
      return;
    
    TEST_EXIT_DBG(nRows0 > 0)("Should not happen!\n");
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    clear();
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    dnnz = new int[nRows0];
    for (int i = 0; i < nRows0; i++)
      dnnz[i] = 0;
    
    if (nRows1 > 0) {
      onnz = new int[nRows1];
      for (int i = 0; i < nRows1; i++)
	onnz[i] = 0;	
    }
  }

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} }