tapioca.cpp 15.2 KB
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#include "tapioca.hpp"
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Tapioca::Tapioca ()
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{
}


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Tapioca::~Tapioca ()
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{
}


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void Tapioca::Finalize ()
{
  this->chunksIndexMatching.clear();
  free (this->chunkCount_);
  free (this->chunkSize_);
  free (this->chunkOffset_);
  this->excludedNode.clear();
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  this->commDataSize_ = 0;

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  MPI_Win_free (&this->RMAWin1);
  MPI_Win_free (&this->RMAWin2);

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  MPI_Comm_free (&this->subComm_);

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  if ( this->amAnAggr_ ) {
    free (this->buffer1);
    free (this->buffer2);
  }
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}


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void Tapioca::GlobalFence () 
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{
  int buffer;

  buffer = this->currentRound_ % NBUFFERS;

  switch (buffer)
    {
    case 0:
      MPI_Win_fence (0, this->RMAWin1);
      break;
    case 1:
      MPI_Win_fence (0, this->RMAWin2);
      break;
    }
  
#ifdef TIMING
  this->endAggrTime = MPI_Wtime();
  
  if ( this->startAggrTime != 0 ) {
    this->totAggrTime = this->endAggrTime - this->startAggrTime;
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    fprintf (stdout, "[TIMING][AGG][AGGR] Rank %d, Rnd %d - %.2f ms\n",
     	     this->commRank_, this->currentRound_, this->totAggrTime * 1000);
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  }
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  this->startAggrTime = 0;
#endif

}


/***********************/
/*  INITIALIZATION     */
/***********************/
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void Tapioca::SetDefaultValues ()
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{
  this->rankDataSize_ = 0;
  this->strategy_ = SHORTEST_PATH;
  this->nAggr_ = 8;
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  this->bufferSize_ = 16777216;
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  this->amAnAggr_ = false;
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  this->commSplit_ = true;
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  this->currentRound_ = 0;
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  this->totalRounds_ = 0;
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  this->readRound_ = 0;
  this->firstRead_ = false;
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  this->currentDataSize_ = 0;
  this->nCommit_ = 0;
  this->writeDevNull_ = false;
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  this->pipelinedBuffers_ = true;
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  /* DEBUG */
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}


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void Tapioca::ParseEnvVariables ()
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{
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  char *envStrategy   = getenv("TAPIOCA_STRATEGY");
  char *envNAggr      = getenv("TAPIOCA_NBAGGR");
  char *envBufferSize = getenv("TAPIOCA_BUFFERSIZE");
  char *envSplit      = getenv("TAPIOCA_COMMSPLIT");
  char *envDevNull    = getenv("TAPIOCA_DEVNULL");
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  char *envPipelining = getenv("TAPIOCA_PIPELINING");
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  if (envStrategy != NULL) {
    strcmp(envStrategy, "SHORTEST_PATH")    ? 0 : this->strategy_ = SHORTEST_PATH;
    strcmp(envStrategy, "LONGEST_PATH")     ? 0 : this->strategy_ = LONGEST_PATH;
    strcmp(envStrategy, "TOPOLOGY_AWARE")   ? 0 : this->strategy_ = TOPOLOGY_AWARE;
    strcmp(envStrategy, "CONTENTION_AWARE") ? 0 : this->strategy_ = CONTENTION_AWARE;
    strcmp(envStrategy, "UNIFORM")          ? 0 : this->strategy_ = UNIFORM;
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    strcmp(envStrategy, "RANDOM")           ? 0 : this->strategy_ = RANDOM;
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  }

  if (envNAggr != NULL) {
    this->nAggr_ = atoi(envNAggr);
  }

  if (envBufferSize != NULL) {
    this->bufferSize_ = atoi(envBufferSize);
  }

  if (envSplit != NULL) {
    strcmp(envSplit, "true")  ? 0 : this->commSplit_ = true;
    strcmp(envSplit, "false") ? 0 : this->commSplit_ = false;
  }

  if (envDevNull != NULL) {
    strcmp(envDevNull, "true")  ? 0 : this->writeDevNull_ = true;
    strcmp(envDevNull, "false") ? 0 : this->writeDevNull_ = false;
  }
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  if (envPipelining != NULL) {
    strcmp(envPipelining, "true")  ? 0 : this->pipelinedBuffers_ = true;
    strcmp(envPipelining, "false") ? 0 : this->pipelinedBuffers_ = false;
  }
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}


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void Tapioca::SetCommValues ()
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{
  MPI_Comm_rank (this->subComm_, &this->commRank_);
  MPI_Comm_size (this->subComm_, &this->commSize_);
  MPI_Comm_rank (MPI_COMM_WORLD, &this->worldRank_);

  MPI_Allreduce (&this->rankDataSize_, &this->commDataSize_, 1, MPI_LONG_LONG, MPI_SUM, this->subComm_);
}


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void Tapioca::SetOffsets ()
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{
  MPI_Exscan (&this->rankDataSize_, &this->offsetInAggrData_, 1, 
	      MPI_LONG_LONG, MPI_SUM, this->subComm_);
  if (this->commRank_ == 0)
    this->offsetInAggrData_ = 0;
}


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void Tapioca::SetNodesList ()
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{
  int *coords, *myCoords, i, worldSize, dimensions;
  
  MPI_Comm_size ( MPI_COMM_WORLD, &worldSize );
  coords = (int *)malloc (worldSize * sizeof (int));

  dimensions = topology.NetworkDimensions () + 1;
  myCoords = (int *)malloc (dimensions * sizeof (int));

  topology.RankToCoordinates (this->worldRank_, myCoords);
  this->intCoords_ = this->CoordsToInt (myCoords, dimensions - 1);
  
  MPI_Allgather(&this->intCoords_, 1, MPI_INT, coords, 1, MPI_INT, MPI_COMM_WORLD);

  for ( i = 0; i < worldSize; i++ )
    this->excludedNode[coords[i]] = false;
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  this->nNodes_ = this->excludedNode.size();

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  free (coords);
  free (myCoords);
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}


/***********************/
/*    AGGREGATION      */
/***********************/
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int Tapioca::NumberOfAggregators ()
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{
  return 0;
}


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void Tapioca::IdentifyMyAggregators ()
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{
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  int i, j, c, globalRoundId, upperBound, index = 0, nAggr;
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  int64_t remainingData, offsetInAggrData;
  std::vector<Round_t> rounds;
  
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  this->totalNeededBuffers_  = ceil ( (double)this->commDataSize_ / (double)this->bufferSize_ );
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  /*
   * If we have more aggregators (and buffers) than needed, decrease the number of aggregators
   */
  nAggr = this->nAggr_;
  
  if ( nAggr > this->nNodes_ )
    nAggr = this->nNodes_;
  
  if ( nAggr > this->totalNeededBuffers_ )
    nAggr = this->totalNeededBuffers_;
  
  if ( nAggr != this->nAggr_ ) {
    if ( this->commRank_ == 0 )
      fprintf ( stdout, "[INFO] Number of aggregators decreased from %d to %d\n",
		this->nAggr_, nAggr);
    
    this->nAggr_ = nAggr;      
  }

  this->totalRounds_ = ceil ( (double)this->totalNeededBuffers_ / (double)this->nAggr_ );
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  for ( i = 0; i < this->totalNeededBuffers_; i++ ) {
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    Round_t r;
    r.aggr = i % this->nAggr_;
    r.round = i / this->nAggr_;
    rounds.push_back(r);
  }

  for ( c = 0; c < this->nChunks_; c++ ) {
    remainingData    = this->chunkCount_[c] * this->chunkSize_[c];
    offsetInAggrData = this->chunkOffset_[c] - this->offsetInFile_;
    globalRoundId = floor ( offsetInAggrData / this->bufferSize_ );
    upperBound = ( offsetInAggrData % this->bufferSize_ ) + remainingData;
    
    while ( remainingData > 0 ) {
      this->globalAggregatorsRanks.push_back ( rounds[globalRoundId].aggr );
      this->roundsIds.push_back ( rounds[globalRoundId].round );
      this->chunksIndexMatching[c].push_back ( index );
      
      if ( upperBound > this->bufferSize_) {
	remainingData = (upperBound - this->bufferSize_);
	this->dataSize.push_back ( this->chunkCount_[c] * this->chunkSize_[c] - remainingData );
      }
      else {
	this->dataSize.push_back ( remainingData );
	remainingData = 0;
      }
      
      upperBound -= this->bufferSize_;
      globalRoundId++;
      index++;
    }
  }
  
#ifdef DEBUG
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  if (this->commRank_ == 4) {
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    fprintf (stdout, "[DEBUG] Rounds distrib. on %d aggregators: AGG ", this->nAggr_);
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    for ( i = 0; i < this->totalNeededBuffers_; i++ )
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      fprintf (stdout, "%d ", rounds[i].aggr);
    fprintf (stdout, "\n                                          RND ");
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    for ( i = 0; i < this->totalNeededBuffers_; i++ )
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      fprintf (stdout, "%d ", rounds[i].round);
    fprintf (stdout, "\n                                          AGG ");
    for ( i = 0; i < this->globalAggregatorsRanks.size(); i++ )
      fprintf (stdout, "%d ", this->globalAggregatorsRanks[i]);
    fprintf (stdout, "\n                                          RID ");
    for ( i = 0; i < this->roundsIds.size(); i++ )
      fprintf (stdout, "%d ", this->roundsIds[i]);
    fprintf (stdout, "\n                                          DAS ");
    for ( i = 0; i < this->dataSize.size(); i++ )
      fprintf (stdout, "%d ", this->dataSize[i]);
    fprintf (stdout, "\n                                          CIM ");
    for ( i = 0; i < this->chunksIndexMatching.size(); i++ ) {
      fprintf (stdout, "{ ");
      for ( j = 0; j < this->chunksIndexMatching[i].size(); j++ )
	fprintf (stdout, "%d ", this->chunksIndexMatching[i][j]);
      fprintf (stdout, "}");
    }
    fprintf (stdout, "\n");
  }
#endif
}


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void Tapioca::ElectAggregators ()
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{
  int aggr, aggrRank, rankAggrComm, sizeAggrComm, aggrRankAggrComm, i, j, aggrCoords, worldSize;
  int64_t color;
  double startTime, endTime, totTime = 0.0;
  MPI_Comm aggrComm;
  MPI_Request request;
  MPI_Status status;
  /* Groups */
  MPI_Group commGroup, aggrGroup;
  int *ranks, *join, *groupRanks, groupSize, groupRank, joinGroup;

  MPI_Comm_size (MPI_COMM_WORLD, &worldSize);

  this->aggregatorsRanks.resize ( this->globalAggregatorsRanks.size() );
  
  for ( aggr = 0; aggr < this->nAggr_; aggr++ ) {
    color = this->DataSizeSentToAggr (aggr);
    
    startTime = MPI_Wtime();

    if ( this->commSplit_ )
      MPI_Comm_split (this->subComm_, color > 0, this->commRank_, &aggrComm);
    else {
      
      MPI_Comm_group (this->subComm_, &commGroup);

      if ( color > 0 ) {
	joinGroup = 1;
	MPI_Allreduce (&joinGroup, &groupSize, 1, MPI_INT, MPI_SUM, this->subComm_ );
      }
      else {
	joinGroup = 0;
	MPI_Allreduce (&joinGroup, &groupSize, 1, MPI_INT, MPI_SUM, this->subComm_ );
	groupSize = this->commSize_ - groupSize;
      }

      join = (int *)malloc (this->commSize_ * sizeof (int));
      MPI_Allgather(&joinGroup, 1, MPI_INT, join, 1, MPI_INT, this->subComm_);
      groupRanks = (int *)malloc (groupSize * sizeof (int));
      
      j = 0;
      for ( i = 0; i < this->commSize_; i++ ) {
	if (join[i] == joinGroup) {
	  groupRanks[j] = i;
	  j++;
	}
      }

      MPI_Group_incl (commGroup, groupSize, groupRanks, &aggrGroup);
      MPI_Comm_create (this->subComm_, aggrGroup, &aggrComm);
      
      free (join);
      free (groupRanks);
    }
    
    MPI_Comm_rank (aggrComm, &rankAggrComm);
    MPI_Comm_size (aggrComm, &sizeAggrComm);

    endTime = MPI_Wtime();
    totTime += ( endTime - startTime );
    
    if ( color > 0 ) {
      switch ( this->strategy_ )
	{
	case SHORTEST_PATH:
	  aggrRank = this->RankShortestPath (aggrComm, color);
	  break;
	case LONGEST_PATH:
	  aggrRank = this->RankLongestPath (aggrComm, color);
	  break;
	case TOPOLOGY_AWARE:
	  aggrRank = this->RankTopologyAware (aggrComm, color);
	  break;
	case CONTENTION_AWARE:
	  aggrRank = this->RankContentionAware (aggrComm, color);
	  break;
	case UNIFORM:
	  aggrRank = this->RankUniformDistribution (aggrComm, color);
	  break;
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	case RANDOM:
	  aggrRank = this->RankRandom (aggrComm, color);
	  break;
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	}

      if ( this->commRank_ == aggrRank ) {
	this->totalWrites_     = ceil ( (double)this->aggrDataSize_ / (double)this->bufferSize_);
	this->globalAggrRank_  = aggr;
	aggrCoords             = this->intCoords_;
	MPI_Isend ( &aggrCoords, 1, MPI_INT, 0, 0, MPI_COMM_WORLD, &request );
      }

      for ( i = 0; i < this->aggregatorsRanks.size(); i++ )
	if ( this->globalAggregatorsRanks[i] == aggr )
	  this->aggregatorsRanks[i] = aggrRank;

#ifdef DEBUG
      int coords[topology.NetworkDimensions() + 1];
      if ( this->commRank_ == aggrRank ) {
	topology.RankToCoordinates (this->worldRank_, coords);
	fprintf (stdout, "[DEBUG] AggRank %d, (", this->worldRank_);
	for ( i = 0; i < topology.NetworkDimensions() + 1; i++ )
	  fprintf (stdout, "%u ", coords[i]);
	fprintf (stdout, ") -> %d, part %d, %lld B from %d ranks, %d rounds\n",
		 this->intCoords_, topology.BridgeNodeId(), this->aggrDataSize_, sizeAggrComm, this->totalWrites_);
      }
#endif
    }

    /*
     *  TODO: Compute this... 
     *              - Vesta: 16 nodes/bridge node
     *              - Mira : 64 nodes/bridge node
     */
    for ( i = 0; i < ( (worldSize / topology.ProcessPerNode ()) / (this->commSize_ / topology.ProcessPerNode ()) ); i++ ) {
      if ( this->worldRank_ == 0 )
	MPI_Recv ( &aggrCoords, 1, MPI_INT, MPI_ANY_SOURCE, 0, MPI_COMM_WORLD, &status );
      
      MPI_Bcast ( &aggrCoords, 1, MPI_INT, 0, MPI_COMM_WORLD);
      this->excludedNode[aggrCoords] = true;
    }
  }

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#ifdef TIMING
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  this->PrintTime( 0, totTime, " |-> Create subcommunicator");
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#endif
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}


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int64_t Tapioca::DataSizeSentToAggr (int aggrId)
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{
  int i;
  int64_t dataSize = 0;

  for ( i = 0; i < this->aggregatorsRanks.size(); i++ )
    if ( this->globalAggregatorsRanks[i] == aggrId )
      dataSize += this->dataSize[i];

  return dataSize;
}


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void Tapioca::InitAggregators () 
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{
  int aggr, retval;
  
  if ( this->amAnAggr_ ) {
    this->buffer1 = malloc (this->bufferSize_);
    this->buffer2 = malloc (this->bufferSize_);

    retval = MPI_Win_create (this->buffer1, this->bufferSize_, 1, MPI_INFO_NULL, this->subComm_, &this->RMAWin1);
    this->HandleMPIError (retval);
    MPI_Win_create (this->buffer2, this->bufferSize_, 1, MPI_INFO_NULL, this->subComm_, &this->RMAWin2);
    this->HandleMPIError (retval);
  }
  else {
    retval = MPI_Win_create (NULL, 0, 1, MPI_INFO_NULL, this->subComm_, &this->RMAWin1);
    this->HandleMPIError (retval);
    retval = MPI_Win_create (NULL, 0, 1, MPI_INFO_NULL, this->subComm_, &this->RMAWin2);
    this->HandleMPIError (retval);
  }

  retval = MPI_Win_fence (0, this->RMAWin1);
  this->HandleMPIError (retval);
  retval = MPI_Win_fence (0, this->RMAWin2);
  this->HandleMPIError (retval);

#ifdef DEBUG
  if (this->commRank_ == MASTER) {
    fprintf (stdout, "[DEBUG] %d RMA windows created (%d aggr., %d buffers)\n", 
	     NBUFFERS, this->nAggr_, NBUFFERS);
  }
#endif
}


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int Tapioca::CoordsToInt (int *coords, int dim)
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{
  int i, res = 0;

  for ( i = 0; i < dim; i++ )
    res += coords[i] * pow (10.0, (double)i);

  return res;
}

/***********************/
/*        MISC.        */
/***********************/
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const char* Tapioca::getStrategyName ()
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{
  switch (this->strategy_)
    {
    case SHORTEST_PATH:    return "Shortest path";
    case LONGEST_PATH:     return "Longest path";
    case TOPOLOGY_AWARE:   return "Topology-aware placement";
    case CONTENTION_AWARE: return "Contention-aware placement";
    case UNIFORM:          return "Uniform placement";
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    case RANDOM :          return "Random placement";
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    default:               return "No placement strategy defined!";
    }
}


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void Tapioca::HandleMPIError (int retval) 
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{
#ifdef DEBUG
  char msg[MPI_MAX_ERROR_STRING];
  int resultlen;
  if (retval != MPI_SUCCESS) {
    MPI_Error_string(retval, msg, &resultlen);
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    fprintf(stderr, "[ERR] %s\n", msg);
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  }
#endif

  return;
}


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void Tapioca::PrintTime ( double startTime, double endTime, char* func )
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{
  double totTime, avgTime, minTime, maxTime;
  int commSize, commRank;
  
  MPI_Comm_rank(MPI_COMM_WORLD, &commRank);
  MPI_Comm_size(MPI_COMM_WORLD, &commSize);
  
  totTime = endTime - startTime;
  totTime = totTime * 1000;
  MPI_Reduce(&totTime, &avgTime, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);
  MPI_Reduce(&totTime, &maxTime, 1, MPI_DOUBLE, MPI_MAX, 0, MPI_COMM_WORLD);
  MPI_Reduce(&totTime, &minTime, 1, MPI_DOUBLE, MPI_MIN, 0, MPI_COMM_WORLD);
  if (commRank == 0) {
    avgTime = avgTime / commSize;
    fprintf (stdout, "[TIMING][AGG] %s: %.2f ms [%.2f ; %.2f]\n",
             func, avgTime, minTime, maxTime);
  }
}


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void Tapioca::MPIIOInfo ( MPI_File fileHandle )
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{
  MPI_Info info;
  int flag;
  char value[1024];

  if ( this->worldRank_ == 0 ) {
    MPI_File_get_info ( fileHandle, &info );
    
    fprintf ( stdout, "[INFO] MPI Two-phases I/O\n");
    
    MPI_Info_get ( info, "cb_buffer_size", 1024, value, &flag );
    fprintf ( stdout, "[INFO] cb_buffer_size = %s\n", value );
    
    MPI_Info_get ( info, "cb_nodes", 1024, value, &flag );
    fprintf ( stdout, "[INFO] cb_nodes = %s\n", value );

    MPI_Info_get ( info, "romio_cb_read", 1024, value, &flag );
    fprintf ( stdout, "[INFO] romio_cb_read = %s\n", value );
    
    MPI_Info_get ( info, "romio_cb_write", 1024, value, &flag );
    fprintf ( stdout, "[INFO] romio_cb_write = %s\n", value );
    
    MPI_Info_get ( info, "romio_no_indep_rw", 1024, value, &flag );
    fprintf ( stdout, "[INFO] romio_no_indep_rw = %s\n", value );
  }
}