bool comm_mesh_verify_parallel_consistency(
  BulkData & M , std::ostream & error_log )
{
  int result = 1 ;

  // Verify consistency of parallel attributes

  result = verify_parallel_attributes( M , error_log );

  if (M.parallel_size() > 1) {
    all_reduce( M.parallel() , ReduceMin<1>( & result ) );
  }

  // Verify entities against owner.

  if ( result ) {
    CommAll all( M.parallel() );

    pack_owned_verify( all , M );

    all.allocate_buffers( all.parallel_size() / 4 );

    pack_owned_verify( all , M );

    all.communicate();

    result = unpack_not_owned_verify( all , M , error_log );

    if (M.parallel_size() > 1) {
      all_reduce( M.parallel() , ReduceMin<1>( & result ) );
    }
  }

  return result == 1 ;
}
Beispiel #2
0
void verify_parallel_consistency( const MetaData & s , ParallelMachine pm )
{
  const unsigned p_rank = parallel_machine_rank( pm );

  const bool is_root = 0 == p_rank ;

  CommBroadcast comm( pm , 0 );

  if ( is_root ) {
    pack( comm.send_buffer() , s.get_parts() );
    pack( comm.send_buffer() , s.get_fields() );
  }

  comm.allocate_buffer();

  if ( is_root ) {
    pack( comm.send_buffer() , s.get_parts() );
    pack( comm.send_buffer() , s.get_fields() );
  }

  comm.communicate();

  int ok[ 2 ];

  ok[0] = unpack_verify( comm.recv_buffer() , s.get_parts() );
  ok[1] = unpack_verify( comm.recv_buffer() , s.get_fields() );

  all_reduce( pm , ReduceMin<2>( ok ) );

  ThrowRequireMsg(ok[0], "P" << p_rank << ": FAILED for Parts");
  ThrowRequireMsg(ok[1], "P" << p_rank << ": FAILED for Fields");
}
Beispiel #3
0
 inline T
 all_reduce(ProcessGroup pg, const T& value, BinaryOperation bin_op)
 {
   T result;
   all_reduce(pg,
              const_cast<T*>(&value), const_cast<T*>(&value+1),
              &result, bin_op);
   return result;
 }
Beispiel #4
0
void CowichanMPI::life(BoolMatrix matrixIn, BoolMatrix matrixOut)
{
  int i;                   // iteration index
  index_t r;               // row index
  int alive;               // number alive
  index_t lo, hi;          // work controls
  index_t rlo, rhi;        // for broadcast
  bool work;               // useful work to do?
  int is_alive = 1;        // some cells still alive?
  BoolMatrix m_tmp;        // tmp pointer

  // work
  work = get_block (world, 0, nr, &lo, &hi);
  for (i = 0; (i < lifeIterations) && (is_alive > 0); i++) {
  
    // reset alive neighbour count
    alive = 0;

    // count neighbours and fill new matrix
    if (work) {
      for (r = lo; r < hi; r++) {
        for (index_t c = 0; c < nc; ++c) {
          index_t count = sumNeighbours(matrixIn, r, c, nr, nc);
          if (count == 3 || ((count == 2) && MATRIX_RECT(matrixIn, r, c))) {
          MATRIX_RECT(matrixOut, r, c) = true;
          ++alive;
        } else {
          MATRIX_RECT(matrixOut, r, c) = false;
        }
        }
      }
    }
    
    // broadcast matrix
    for (r = 0; r < world.size (); r++) {
      if (get_block (world, 0, nr, &rlo, &rhi, r)) {
        broadcast (world, &MATRIX_RECT(matrixOut, rlo, 0),
            (int)((rhi - rlo) * nc), (int)r);
      }
    }
    
    // is_alive is maximum of local alive's
    all_reduce (world, alive, is_alive, mpi::maximum<int>());

  // swap matrices (ping-pong)
    m_tmp = matrixIn;
    matrixIn = matrixOut;
    matrixOut = m_tmp;
    
  }
}
Beispiel #5
0
void communicate_field_data_verify_read( CommAll & sparse )
{
  std::ostringstream msg ;
  int error = 0 ;
  for ( unsigned p = 0 ; p < sparse.parallel_size() ; ++p ) {
    if ( sparse.recv_buffer( p ).remaining() ) {
      msg << "P" << sparse.parallel_rank()
          << " Unread data from P" << p << std::endl ;
      error = 1 ;
    }
  }
  all_reduce( sparse.parallel() , ReduceSum<1>( & error ) );
  ThrowErrorMsgIf( error, msg.str() );
}
Beispiel #6
0
void communicate_field_data_verify_read( CommAll & sparse )
{
  std::ostringstream msg ;
  int flag = 0 ;
  for ( unsigned p = 0 ; p < sparse.parallel_size() ; ++p ) {
    if ( sparse.recv_buffer( p ).remaining() ) {
      msg << "P" << sparse.parallel_rank()
          << " Unread data from P" << p << std::endl ;
      flag = 1 ;
    }
  }
  all_reduce( sparse.parallel() , ReduceSum<1>( & flag ) );
  if ( flag ) {
    throw std::runtime_error( msg.str() );
  }
}
int main(int argc, char* argv[])
{
  mpi::environment env(argc, argv);
  mpi::communicator world;

  std::srand(world.rank());
  int my_number = std::rand();

  all_reduce(world, my_number, mpi::minimum<int>());

  if (world.rank() == 0) {
    std::cout << "The minimum value is " << my_number << std::endl;
  }

  return 0;
}
Beispiel #8
0
void verify_parallel_consistency( const MetaData & s , ParallelMachine pm )
{
  static const char method[] = "phdmesh::verify_parallel_consistency(MetaData)" ;

  const unsigned p_rank = parallel_machine_rank( pm );

  const bool is_root = 0 == p_rank ;

  CommBroadcast comm( pm , 0 );

  if ( is_root ) {
    pack( comm.send_buffer() , s.get_parts() );
    pack( comm.send_buffer() , s.get_fields() );
  }

  comm.allocate_buffer();

  if ( is_root ) {
    pack( comm.send_buffer() , s.get_parts() );
    pack( comm.send_buffer() , s.get_fields() );
  }

  comm.communicate();

  int ok[ 2 ];

  ok[0] = unpack_verify( comm.recv_buffer() , s.get_parts() );
  ok[1] = unpack_verify( comm.recv_buffer() , s.get_fields() );

  all_reduce( pm , Min<2>( ok ) );

  if ( ! ok[0] || ! ok[1] ) {
    std::ostringstream msg ;
    msg << "P" << p_rank ;
    msg << ": " << method ;
    msg << " : FAILED for:" ;
    if ( ! ok[0] ) { msg << " Parts" ; }
    if ( ! ok[1] ) { msg << " Fields" ; }
    throw std::logic_error( msg.str() );
  }
}
Beispiel #9
0
void
AllReduce(
  MPI_Comm		comm,
  const ReduceSet &	reduce_set)
{
  size_t size = reduce_set.size();

  if (size) {
    char *input_buffer  = new char[size];
    char *output_buffer = new char[size];
    void *inbuf = (void *) input_buffer;
    void *outbuf = (void *) output_buffer;

    s_currentReduceSet = &reduce_set;

    ParallelReduceOp f = reinterpret_cast<ParallelReduceOp>(& ReduceSet::void_op);

    reduce_set.copyin(inbuf);
    all_reduce(comm, f, inbuf, outbuf, size);
    reduce_set.copyout(outbuf);
    delete [] output_buffer;
    delete [] input_buffer;
  }
}
Beispiel #10
0
    /** Evaluate the function at this input point (or points) returning value(s) in output_field_values
     *
     *   In the following, the arrays are dimensioned using the notation (from Intrepid's doc):
     *
     *   [C]         - num. integration domains (cells/elements)
     *   [F]         - num. Intrepid "fields" (number of bases within an element == num. nodes typically)
     *   [P]         - num. integration (or interpolation) points within the element
     *   [D]         - spatial dimension
     *   [D1], [D2]  - spatial dimension
     *
     *   Locally, we introduce this notation:
     *
     *   [DOF]       - number of degrees-of-freedom per node of the interpolated stk Field.  For example, a vector field in 3D has [DOF] = 3
     *
     *  Dimensions of input_phy_points are required to be either ([D]) or ([P],[D])
     *  Dimensions of output_field_values are required to be ([DOF]) or ([P],[DOF]) respectively
     *
     *  [R] is used for the rank of MDArray's
     */
    void FieldFunction::operator()(MDArray& input_phy_points, MDArray& output_field_values, double time)
    {
      EXCEPTWATCH;
      argsAreValid(input_phy_points, output_field_values);

      m_found_on_local_owned_part = false;

      //// single point only (for now)
      unsigned found_it = 0;

      int D_ = last_dimension(input_phy_points);
      MDArray found_parametric_coordinates_one(1, D_);
      setup_searcher(D_);

      MDArray output_field_values_local = output_field_values;
      int R_output = output_field_values.rank();

      int R_input = input_phy_points.rank();
      int P_ = (R_input == 1 ? 1 : input_phy_points.dimension(R_input-2));

      // FIXME for tensor valued fields
      int DOF_ = last_dimension(output_field_values_local);

      MDArray input_phy_points_one(1,D_);
      MDArray output_field_values_one(1,DOF_);

      int C_ = 1;
      if (R_input == 3)
        {
          C_ = input_phy_points.dimension(0);
        }
      for (int iC = 0; iC < C_; iC++)
        {
          for (int iP = 0; iP < P_; iP++)
            {
              for (int iD = 0; iD < D_; iD++)
                {
                  switch(R_input)
                    {
                    case 1: input_phy_points_one(0, iD) = input_phy_points(iD); break;
                    case 2: input_phy_points_one(0, iD) = input_phy_points(iP, iD); break;
                    case 3: input_phy_points_one(0, iD) = input_phy_points(iC, iP, iD); break;
                    default: VERIFY_1("bad rank");
                    }
                }

              const stk_classic::mesh::Entity *found_element = 0;
              {
                EXCEPTWATCH;
                //if (m_searchType==STK_SEARCH) std::cout << "find" << std::endl;
                found_element = m_searcher->findElement(input_phy_points_one, found_parametric_coordinates_one, found_it, m_cachedElement);
                //if (m_searchType==STK_SEARCH)                std::cout << "find..done found_it=" << found_it << std::endl;
              }

              // if found element on the local owned part, evaluate
              if (found_it)
                {
                  m_found_on_local_owned_part = true;
                  if (( EXTRA_PRINT) && m_searchType==STK_SEARCH)
                    std::cout << "FieldFunction::operator() found element # = " << found_element->identifier() << std::endl;

                  (*this)(input_phy_points_one, output_field_values_one, *found_element, found_parametric_coordinates_one);

                  for (int iDOF = 0; iDOF < DOF_; iDOF++)
                    {
                      switch (R_output)
                        {
                        case 1: output_field_values_local( iDOF)        = output_field_values_one(0, iDOF); break;
                        case 2: output_field_values_local(iP, iDOF)     = output_field_values_one(0, iDOF); break;
                        case 3: output_field_values_local(iC, iP, iDOF) = output_field_values_one(0, iDOF); break;
                        default: VERIFY_1("bad rank");
                        }
                    }
                }
              else
                {
                  if (!m_parallelEval)
                    {
                      std::cout << "P[" << Util::get_rank() << "] FieldFunction::operator() found_it = " << found_it << " points= "
                                << input_phy_points_one
                                << std::endl;

                      throw std::runtime_error("FieldFunction::operator() in local eval mode and didn't find element - logic error");
                    }
                  double max_val = std::numeric_limits<double>::max();
                  output_field_values_local.initialize(max_val);
                }

              // make sure it is found somewhere
              if (m_parallelEval)
                {
                  all_reduce( m_bulkData->parallel() , ReduceMax<1>( & found_it ) );
                }

              if (EXTRA_PRINT) std::cout << "FieldFunction::operator() global found_it = " << found_it << std::endl;

              if (!found_it)
                {
                  throw std::runtime_error("FieldFunction::operator() couldn't find element");
                }

              if (m_parallelEval)
                {
                  stk_percept_global_lex_min( m_bulkData->parallel(), output_field_values.size(), &output_field_values_local[0], &output_field_values[0]);
                }
              else
                {
                  output_field_values = output_field_values_local;
                }
              m_cachedElement = found_element;
            }
        }

    }
Beispiel #11
0
int main(int argc, char **argv){//MAIN MAIN MAIN
mpi::environment env(argc, argv);
mpi::communicator world;
std::srand(135+world.rank()); 

int nodecount, max_i, max_j, max_k;
if(world.rank()==0) {
  std::cout << "usage:  ./population_test.exe testfilename\n";
  FILE* nodefile = fopen(argv[1], "r"); 
  if (nodefile==NULL) {
    std::cout << "error opening file "<<argv[1] << "\n"; 
    return 1; 
  }

  char oneline[100];
  int line_count=0;
  while( fgets(oneline,100,nodefile)!=NULL){
    if(oneline[0]=='#' || oneline[0]=='\n'){
      std::cout << oneline; 
      continue;
    }else{
      line_count+=1;
      if(line_count==1){ 
        sscanf(oneline,"%d%d%d%d",&nodecount,&max_i,&max_j,&max_k); 
      }else{
        gampi_nodelist.push_back((nodeid) atoi(oneline));
      } 
    }
  } 
}

broadcast(world, max_i, 0);
broadcast(world, max_j, 0);
broadcast(world, max_k, 0);
broadcast(world, gampi_nodelist, 0);

gampi_domain=Domain(max_i, max_j, max_k); 

if(world.rank()==0){
  Individual a;
  a.show((char*)"Ideal soln"); 
}

Individual v(true);
Population a(v, 1); //ancestor population
Population e(v, 1); //store the elites

time_t start=time(NULL); 
time_t lastprint=time(NULL);
float currbest=v.get_fitness(); 
std::pair<float,int> fitrank, bestfitrank; 
int elapsed=0; 

const int pop_size=100000; 
const int subset_percent=5; //percentage of population that makes the subset for next gen
const float maxruntime=300.0; // seconds
const float maxgentime=maxruntime/30.0; // seconds, max time for creating one generation

do {
  float lastbest=currbest;

  Population p(a, pop_size, maxgentime); //population expanded from ancestors

  //Select a subset to be used for creating next generation
  e=p.elitist_selection(std::max(1, p.get_size()*subset_percent/100/10)); 
  currbest=e.get_best_fitness(); 

  if(currbest>lastbest*0.99) {
    a=p.rank_selection   (std::max(1, p.get_size()*subset_percent/100)); 
  } else {
    a=p.elitist_selection(std::max(1, p.get_size()*subset_percent/100)); 
  }

  //Add someone else's elites to mine
  if(world.size()>1){
    int comm_offset;
    if(world.rank()==0) comm_offset=1+(rand()%(world.size()-1)); // goes from 1 to N-1
    broadcast(world, comm_offset, 0); 
    int src_rank=(world.size()+world.rank()+comm_offset)%world.size(); // I receive from
    int dst_rank=(world.size()+world.rank()-comm_offset)%world.size(); // I send to 

    mpi::request reqs[2];
    Population r(v, 1);
    reqs[0]=world.isend(dst_rank, 307, e); 
    reqs[1]=world.irecv(src_rank, 307, r); 
    mpi::wait_all(reqs, reqs+2);  
    a+=r; 
  }

  time_t current=time(NULL); 
  elapsed=difftime(current, start); 
  broadcast(world, elapsed, 0); //So they all stop at the same iteration

  fitrank=std::make_pair(currbest, world.rank()); 
  all_reduce(world, fitrank, bestfitrank, mpi::minimum<std::pair<float,int> >()); 

  if (world.rank()==0 && difftime(current, lastprint)>=1) {
      printf("%3d (secs): %8.5f\n", elapsed, bestfitrank.first);
      lastprint=time(NULL); 
  }
} while(elapsed<maxruntime); 

Individual best; 
if(bestfitrank.second==0 && world.rank()==0) {
  best=e.get_individual(0); 
  best.show((char*) "Best soln"); 
} else if(world.rank()==bestfitrank.second) {
  best=e.get_individual(0); 
  world.send(0, 816, best); 
} else if (world.rank()==0) {
  world.recv(bestfitrank.second, 816, best); 
  best.show((char*) "Best soln"); 
}

} // end MAIN MAIN MAIN
Beispiel #12
0
inline void
all_reduce(const communicator& comm, inplace_t<T*> inout_values, int n, Op op)
{
  all_reduce(comm, static_cast<const T*>(MPI_IN_PLACE), n, inout_values.buffer, op);
}
Beispiel #13
0
void BulkData::change_entity_owner( const std::vector<EntityProc> & arg_change )
{
  static const char method[] = "stk::mesh::BulkData::change_entity_owner" ;

  const MetaData  & meta = m_mesh_meta_data ;
  const unsigned  p_rank = m_parallel_rank ;
  const unsigned  p_size = m_parallel_size ;
  ParallelMachine p_comm = m_parallel_machine ;

  //------------------------------
  // Verify the input changes, generate a clean local change list, and
  // generate the remote change list so that all processes know about
  // pending changes.

  std::vector<EntityProc> local_change( arg_change );

  // Parallel synchronous clean up and verify the requested changes:
  clean_and_verify_parallel_change( method , *this , local_change );

  //----------------------------------------
  // Parallel synchronous determination of changing
  // shared and ghosted.

  std::vector<EntityProc> ghosted_change ;
  std::vector<EntityProc> shared_change ;

  generate_parallel_change( *this , local_change ,
                            shared_change , ghosted_change );

  //------------------------------
  // Have enough information to delete all effected ghosts.
  // If the closure of a ghost contains a changing entity
  // then that ghost must be deleted.
  // Request that all ghost entities in the closure of the ghost be deleted.

  typedef std::set<EntityProc,EntityLess> EntityProcSet;
  typedef std::set<Entity*,EntityLess> EntitySet;

  // Closure of the owner change for impacted ghost entities.

  EntityProcSet send_closure ;

  for ( std::vector<EntityProc>::iterator
        i = local_change.begin() ; i != local_change.end() ; ++i ) {
    insert_closure_send( *i , send_closure );
  }

  {
    EntitySet work ;

    for ( std::vector<EntityProc>::const_iterator
          i = ghosted_change.begin() ; i != ghosted_change.end() ; ++i ) {
      insert_transitive_ghost( i->first , m_parallel_rank , work );
    }

    for ( std::vector<EntityProc>::const_iterator
          i = shared_change.begin() ; i != shared_change.end() ; ++i ) {
      insert_transitive_ghost( i->first , m_parallel_rank , work );
    }

    for ( EntityProcSet::iterator
          i = send_closure.begin() ; i != send_closure.end() ; ++i ) {
      insert_transitive_ghost( i->first , m_parallel_rank , work );
    }

    // The ghosted change list will become invalid
    ghosted_change.clear();

    std::vector<EntityProc> empty ;
    std::vector<Entity*> effected_ghosts( work.begin() , work.end() );

    // Skip 'm_ghosting[0]' which is the shared subset.
    for ( std::vector<Ghosting*>::iterator
          ig = m_ghosting.begin() + 1 ; ig != m_ghosting.end() ; ++ig ) {
      // parallel synchronous:
      internal_change_ghosting( **ig , empty , effected_ghosts );
    }
  }

  //------------------------------
  // Consistently change the owner on all processes.
  // 1) The local_change list is giving away ownership.
  // 2) The shared_change may or may not be receiving ownership

  {
    PartVector owned( 1 );
    owned[0] = & meta.locally_owned_part();

    for ( std::vector<EntityProc>::iterator
          i = local_change.begin() ; i != local_change.end() ; ++i ) {
      // Giving ownership, change the parts first and then
      // the owner rank to pass the ownership test.
      change_entity_parts( * i->first , PartVector() , owned );

      m_entity_repo.set_entity_owner_rank( *(i->first), i->second);
    }

    for ( std::vector<EntityProc>::iterator
          i = shared_change.begin() ; i != shared_change.end() ; ++i ) {
      m_entity_repo.set_entity_owner_rank( *(i->first), i->second);
      if ( p_rank == i->second ) { // I receive ownership
        change_entity_parts( * i->first , owned , PartVector() );
      }
    }
  }

  //------------------------------
  // Send entities, along with their closure, to the new owner processes
  {
    std::ostringstream error_msg ;
    int error_count = 0 ;

    CommAll comm( p_comm );

    for ( std::set<EntityProc,EntityLess>::iterator
          i = send_closure.begin() ; i != send_closure.end() ; ++i ) {
      CommBuffer & buffer = comm.send_buffer( i->second );
      Entity     & entity = * i->first ;
      pack_entity_info( buffer , entity );
      pack_field_values( buffer , entity );
    }

    comm.allocate_buffers( p_size / 4 );

    for ( std::set<EntityProc,EntityLess>::iterator
          i = send_closure.begin() ; i != send_closure.end() ; ++i ) {
      CommBuffer & buffer = comm.send_buffer( i->second );
      Entity     & entity = * i->first ;
      pack_entity_info( buffer , entity );
      pack_field_values( buffer , entity );
    }

    comm.communicate();

    for ( unsigned p = 0 ; p < p_size ; ++p ) {
      CommBuffer & buf = comm.recv_buffer(p);
      while ( buf.remaining() ) {
        PartVector parts ;
        std::vector<Relation> relations ;
        EntityKey key ;
        unsigned  owner = ~0u ;

        unpack_entity_info( buf, *this, key, owner, parts, relations );

        // Received entity information will be correct,
        // modulo the owned and shared parts

        remove( parts , meta.globally_shared_part() );

        if ( owner == p_rank ) {
          // Must have the locally_owned_part
          insert( parts , meta.locally_owned_part() );
        }
        else {
          // Must not have the locally_owned_part
          remove( parts , meta.locally_owned_part() );
        }

        std::pair<Entity*,bool> result =
          m_entity_repo.internal_create_entity( key );

        m_entity_repo.log_created_parallel_copy( *(result.first) );

        // The entity was copied and not created.

        m_entity_repo.set_entity_owner_rank( *(result.first), owner);

        internal_change_entity_parts( *result.first , parts , PartVector() );

        declare_relation( *result.first , relations );

        if ( ! unpack_field_values( buf , * result.first , error_msg ) ) {
          ++error_count ;
        }
      }
    }

    all_reduce( p_comm , ReduceSum<1>( & error_count ) );

    if ( error_count ) { throw std::runtime_error( error_msg.str() ); }

    // Any entity that I sent and is not in an owned closure is deleted.
    // The owned closure will be effected by received entities, so can
    // only clean up after the newly owned entities have been received.
    // Destroy backwards so as not to invalidate closures in the process.

    {
      Entity * entity = NULL ;

      for ( std::set<EntityProc,EntityLess>::iterator
            i = send_closure.end() ; i != send_closure.begin() ; ) {

        Entity * e = (--i)->first ;

        // The same entity may be sent to more than one process.
        // Only evaluate it once.

        if ( entity != e ) {
          entity = e ;
          if ( ! member_of_owned_closure( *e , p_rank ) ) {
            if ( ! destroy_entity( e ) ) {
              throw std::logic_error(std::string("BulkData::destroy_entity FAILED"));
            }
          }
        }
      }
    }

    send_closure.clear(); // Has been invalidated
  }
}
Beispiel #14
0
void
outer_mpi(mpi::communicator world,
  pt1D*		ptVec,			/* vector of points */
  real2D*	matrix,			/* matrix to fill */
  real1D*	realVec,		/* vector to fill */
  int		n			/* size */
){
  int		lo, hi;		/* work controls */
  int		r, c;			/* loop indices */
  real		d;			/* distance */
  real d_max_local = -1.0; // maximum distance
  real d_max; // maximum distance
  bool		work;			/* do useful work? */
  int i, j;

  /* all elements except matrix diagonal */
  work = get_block_rows_mpi (world, 0, n, &lo, &hi);
  if (work) {
    for (r = lo; r < hi; r++) {
      realVec[r] = ptMag(&(ptVec[r]));
      for (c = 0; c < r; c++) {
        d = ptDist (&(ptVec[r]), &(ptVec[c]));
        if (d > d_max_local) {
          d_max_local = d;
        }
        // fill columns 0 to r only
        matrix[r][c] = d;
      }
    }
  }

  // reduce to maximum d's
  all_reduce (world, d_max_local, d_max, mpi::maximum<real>());
  
  /* matrix diagonal */
  d = d_max * n;
  if (work) {
    for (r = lo; r < hi; r++) {
      matrix[r][r] = d;
    }
  }

  // broadcast matrix, realVec
  for (i = 0; i < world.size (); i++) {
    if (get_block_rows_mpi (world, 0, n, &lo, &hi, i)) {
      broadcast (world, &realVec[lo], hi - lo, i);
      // broadcast row by row since n may be smaller than MAXEXT
      for (j = lo; j < hi; j++) {
        broadcast (world, matrix[j], n, i);
      }
    }
  }

  // fill in the rest to make symmetric matrix
  for (r = 0; r < n; r++) {
    for (c = 0; c < r; c++) {
      matrix[c][r] = matrix[r][c];
    }
  }

  /* return */
}
Beispiel #15
0
    // Initialize for edge generation
    scalable_rmat_iterator(ProcessGroup pg, Distribution distrib,
                           RandomGenerator& gen, vertices_size_type n,
                           edges_size_type m, double a, double b, double c,
                           double d, bool permute_vertices = true)
        : gen(), done(false)
    {
        BOOST_ASSERT(a + b + c + d == 1);
        int id = process_id(pg);

        this->gen.reset(new uniform_01<RandomGenerator>(gen));

        std::vector<vertices_size_type> vertexPermutation;
        if (permute_vertices)
            generate_permutation_vector(gen, vertexPermutation, n);

        int SCALE = int(floor(log(double(n))/log(2.)));
        boost::uniform_01<RandomGenerator> prob(gen);

        std::map<value_type, bool> edge_map;

        edges_size_type generated = 0, local_edges = 0;
        do {
            edges_size_type tossed = 0;
            do {
                vertices_size_type u, v;
                boost::tie(u, v) = generate_edge(this->gen, n, SCALE, a, b, c, d);

                if (permute_vertices) {
                    u = vertexPermutation[u];
                    v = vertexPermutation[v];
                }

                // Lowest vertex number always comes first (this
                // means we don't have to worry about i->j and j->i
                // being in the edge list)
                if (u > v && is_same<directed_category, undirected_tag>::value)
                    std::swap(u, v);

                if (distrib(u) == id || distrib(v) == id) {
                    if (edge_map.find(std::make_pair(u, v)) == edge_map.end()) {
                        edge_map[std::make_pair(u, v)] = true;
                        local_edges++;
                    } else {
                        tossed++;

                        // special case - if both u and v are on same
                        // proc, ++ twice, since we divide by two (to
                        // cover the two process case)
                        if (distrib(u) == id && distrib(v) == id)
                            tossed++;
                    }
                }
                generated++;

            } while (generated < m);
            tossed = all_reduce(pg, tossed, boost::parallel::sum<vertices_size_type>());
            generated -= (tossed / 2);
        } while (generated < m);
        // NGE - Asking for more than n^2 edges will result in an infinite loop here
        //       Asking for a value too close to n^2 edges may as well

        values.reserve(local_edges);
        typename std::map<value_type, bool>::reverse_iterator em_end = edge_map.rend();
        for (typename std::map<value_type, bool>::reverse_iterator em_i = edge_map.rbegin();
                em_i != em_end ;
                ++em_i) {
            values.push_back(em_i->first);
        }

        current = values.back();
        values.pop_back();
    }