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Zoltan2_AlgBlock.hpp
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45 #ifndef _ZOLTAN2_ALGBLOCK_HPP_
46 #define _ZOLTAN2_ALGBLOCK_HPP_
47 
48 #include <Zoltan2_Algorithm.hpp>
51 
52 #include <bitset>
53 #include <sstream>
54 #include <string>
55 
60 namespace Zoltan2{
61 
71 };
72 
90 template <typename Adapter>
91 class AlgBlock : public Algorithm<Adapter>
92 {
93 
94 private:
95  const RCP<const Environment> env;
96  const RCP<const Comm<int> > problemComm;
97  const RCP<const IdentifierModel<typename Adapter::base_adapter_t> > ids;
98 
99 public:
100  typedef typename Adapter::lno_t lno_t; // local ids
101  typedef typename Adapter::gno_t gno_t; // global ids
102  typedef typename Adapter::scalar_t scalar_t; // scalars
103  typedef typename Adapter::part_t part_t; // part numbers
104 
105  // Constructor
107  const RCP<const Environment> &env_,
108  const RCP<const Comm<int> > &problemComm_,
110  ) :
111  env(env_), problemComm(problemComm_), ids(ids_)
112  {}
113 
114  // Partitioning method
115  void partition(const RCP<PartitioningSolution<Adapter> > &solution)
116  {
117  env->debug(DETAILED_STATUS, std::string("Entering AlgBlock"));
118 
119  int rank = env->myRank_;
120  int nprocs = env->numProcs_;
121 
123  // From the IdentifierModel we need:
124  // the number of gnos
125  // number of weights per gno
126  // the weights
127 
128  size_t numGnos = ids->getLocalNumIdentifiers();
129 
130  ArrayView<const gno_t> idList;
131  typedef StridedData<lno_t, scalar_t> input_t;
132  ArrayView<input_t> wgtList;
133 
134  ids->getIdentifierList(idList, wgtList);
135 
136  // If user supplied no weights, we use uniform weights.
137  bool uniformWeights = (wgtList.size() == 0);
138 
140  // Partitioning problem parameters of interest:
141  // objective
142  // imbalance_tolerance
143 
144  const Teuchos::ParameterList &pl = env->getParameters();
145  const Teuchos::ParameterEntry *pe;
146 
147  pe = pl.getEntryPtr("partitioning_objective");
148  if (pe) {
149  std::string po = pe->getValue<std::string>(&po);
150  if (po == std::string("balance_object_count"))
151  uniformWeights = true; // User requests that we ignore weights
152  }
153 
154  double imbalanceTolerance=1.1;
155  pe = pl.getEntryPtr("imbalance_tolerance");
156  if (pe) imbalanceTolerance = pe->getValue<double>(&imbalanceTolerance);
157 
159  // From the Solution we get part information:
160  // number of parts and part sizes
161 
162  size_t numGlobalParts = solution->getTargetGlobalNumberOfParts();
163 
164  Array<scalar_t> part_sizes(numGlobalParts);
165 
166  if (solution->criteriaHasUniformPartSizes(0))
167  for (unsigned int i=0; i<numGlobalParts; i++)
168  part_sizes[i] = 1.0 / numGlobalParts;
169  else
170  for (unsigned int i=0; i<numGlobalParts; i++)
171  part_sizes[i] = solution->getCriteriaPartSize(0, i);
172 
173  for (unsigned int i=1; i<numGlobalParts; i++)
174  part_sizes[i] += part_sizes[i-1];
175 
176  // TODO assertion that last part sizes is about equal to 1.0
177 
178 
180  // The algorithm
181  //
182  // Block partitioning algorithm lifted from zoltan/src/simple/block.c
183  // The solution is:
184  // a list of part numbers in gno order
185  // an imbalance for each weight
186 
187  scalar_t wtsum(0);
188 
189  if (!uniformWeights) {
190  for (size_t i=0; i<numGnos; i++)
191  wtsum += wgtList[0][i]; // [] operator knows stride
192  }
193  else
194  wtsum = static_cast<scalar_t>(numGnos);
195 
196  Array<scalar_t> scansum(nprocs+1, 0);
197 
198  Teuchos::gatherAll<int, scalar_t>(*problemComm, 1, &wtsum, nprocs,
199  scansum.getRawPtr()+1);
200 
201  /* scansum = sum of weights on lower processors, excluding self. */
202 
203  for (int i=2; i<=nprocs; i++)
204  scansum[i] += scansum[i-1];
205 
206  scalar_t globalTotalWeight = scansum[nprocs];
207 
208  if (env->getDebugLevel() >= VERBOSE_DETAILED_STATUS) {
209  std::ostringstream oss("Part sizes: ");
210  for (unsigned int i=0; i < numGlobalParts; i++)
211  oss << part_sizes[i] << " ";
212  oss << std::endl << std::endl << "Weights : ";
213  for (int i=0; i <= nprocs; i++)
214  oss << scansum[i] << " ";
215  oss << std::endl;
216  env->debug(VERBOSE_DETAILED_STATUS, oss.str());
217  }
218 
219  /* Loop over objects and assign part. */
220  part_t part = 0;
221  wtsum = scansum[rank];
222  Array<scalar_t> partTotal(numGlobalParts, 0);
223  ArrayRCP<part_t> gnoPart= arcp(new part_t[numGnos], 0, numGnos);
224 
225  env->memory("Block algorithm memory");
226 
227  for (size_t i=0; i<numGnos; i++){
228  scalar_t gnoWeight = (uniformWeights ? 1.0 : wgtList[0][i]);
229  /* wtsum is now sum of all lower-ordered object */
230  /* determine new part number for this object,
231  using the "center of gravity" */
232  while (unsigned(part)<numGlobalParts-1 &&
233  (wtsum+0.5*gnoWeight) > part_sizes[part]*globalTotalWeight)
234  part++;
235  gnoPart[i] = part;
236  partTotal[part] += gnoWeight;
237  wtsum += gnoWeight;
238  }
239 
241  // Done
242 
243  solution->setParts(gnoPart);
244 
245  env->debug(DETAILED_STATUS, std::string("Exiting AlgBlock"));
246  }
247 };
248 
249 } // namespace Zoltan2
250 
251 #endif
Adapter::lno_t lno_t
AlgBlock(const RCP< const Environment > &env_, const RCP< const Comm< int > > &problemComm_, const RCP< const IdentifierModel< typename Adapter::base_adapter_t > > &ids_)
Adapter::part_t part_t
Defines the PartitioningSolution class.
sub-steps, each method&#39;s entry and exit
SparseMatrixAdapter_t::part_t part_t
list idList
Match up parameters to validators.
Defines the IdentifierModel interface.
A PartitioningSolution is a solution to a partitioning problem.
Adapter::scalar_t scalar_t
The StridedData class manages lists of weights or coordinates.
Algorithm defines the base class for all algorithms.
Adapter::gno_t gno_t
void partition(const RCP< PartitioningSolution< Adapter > > &solution)
Partitioning method.
IdentifierModel defines the interface for all identifier models.
include more detail about sub-steps
blockParams
The boolean parameters of interest to the Block algorithm.