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Zoltan2_MatrixPartitioningSolution.hpp
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1// @HEADER
2// *****************************************************************************
3// Zoltan2: A package of combinatorial algorithms for scientific computing
4//
5// Copyright 2012 NTESS and the Zoltan2 contributors.
6// SPDX-License-Identifier: BSD-3-Clause
7// *****************************************************************************
8// @HEADER
9
14#ifndef _ZOLTAN2_MATRIXPARTITIONINGSOLUTION_HPP_
15#define _ZOLTAN2_MATRIXPARTITIONINGSOLUTION_HPP_
16
17// namespace Zoltan2 {
18// template <typename Adapter>
19// class PartitioningSolution;
20// }
21
22// #include <Zoltan2_Environment.hpp>
23// #include <Zoltan2_Solution.hpp>
24// #include <Zoltan2_GreedyMWM.hpp>
25// #include <Zoltan2_Algorithm.hpp>
26// #include <Zoltan2_CoordinatePartitioningGraph.hpp>
27// #include <cmath>
28// #include <algorithm>
29// #include <vector>
30// #include <limits>
31
32
33namespace Zoltan2 {
34
49template <typename Adapter>
51{
52public:
53
54#ifndef DOXYGEN_SHOULD_SKIP_THIS
55 typedef typename Adapter::gno_t gno_t;
56 typedef typename Adapter::scalar_t scalar_t;
57 typedef typename Adapter::lno_t lno_t;
58 typedef typename Adapter::part_t part_t;
59 typedef typename Adapter::user_t user_t;
60#endif
61
77 MatrixPartitioningSolution( const RCP<const Environment> &env,
78 const RCP<const Comm<int> > &comm,
79 const RCP<Algorithm<Adapter> > &algorithm = Teuchos::null);
80
81
83 // Information that the algorithm may wish to query.
84
86 // Method used by the algorithm to set results.
87
102 void setIDLists(ArrayRCP<part_t> &rowIDs,ArrayRCP<part_t> &colIDs,
103 ArrayRCP<part_t> &domainIDs, ArrayRCP<part_t> &rangeIDs);
104
106
107 // TODO: Figure out if I want to do this
108 //
109 // /*! \brief Remap a new partition for maximum overlap with an input partition.
110 // *
111 // * Assumptions for this version:
112 // * input part assignment == processor rank for every local object.
113 // * assuming nGlobalParts <= num ranks
114 // * TODO: Write a version that takes the input part number as input;
115 // * this change requires input parts in adapters to be provided in
116 // * the Adapter.
117 // * TODO: For repartitioning, compare to old remapping results; see Zoltan1.
118 // */
119
120 // void RemapParts();
121
122 // ////////////////////////////////////////////////////////////////////
123 // /* Return the weight of objects staying with a given remap.
124 // * If remap is NULL, compute weight of objects staying with given partition
125 // */
126 // long measure_stays(part_t *remap, int *idx, part_t *adj, long *wgt,
127 // part_t nrhs, part_t nlhs)
128 // {
129 // long staying = 0;
130 // for (part_t i = 0; i < nrhs; i++) {
131 // part_t k = (remap ? remap[i] : i);
132 // for (part_t j = idx[k]; j < idx[k+1]; j++) {
133 // if (i == (adj[j]-nlhs)) {
134 // staying += wgt[j];
135 // break;
136 // }
137 // }
138 // }
139 // return staying;
140 // }
141
143 // Results that may be queried by the user, by migration methods,
144 // or by metric calculation methods.
145 // We return raw pointers so users don't have to learn about our
146 // pointer wrappers.
147
150 inline const RCP<const Comm<int> > &getCommunicator() const { return comm_;}
151
154 inline const RCP<const Environment> &getEnvironment() const { return env_;}
155
156
159 const gno_t *getRowIdsView() const
160 {
161 if (rowIDs_.size() > 0)
162 return rowIDs_.getRawPtr();
163 else
164 return NULL;
165 }
166
167
170 const gno_t *getColIdsView() const
171 {
172 if (colIDs_.size() > 0)
173 return colIDs_.getRawPtr();
174 else
175 return NULL;
176 }
177
178
179 // /*! \brief Returns the process list corresponding to the global ID list.
180 // \return The return value is a NULL pointer if part IDs are
181 // synonomous with process IDs.
182 // */
183 // const int *getProcListView() const {
184 // if (procs_.size() > 0) return procs_.getRawPtr();
185 // else return NULL;
186 // }
187
188
189 // /*! \brief Get the processes containing a part.
190 // * \param partId a part number from 0 to one less than the global number
191 // * of parts.
192 // * \param procMin on return will be set to minimum proc number
193 // * \param procMax on return will be set to maximum proc number
194 // *
195 // * Normally \c procMin and \c procMax are the same value and a part
196 // * is assigned to one process. But if there are more processes than
197 // * parts, it's possible that a part will be divided across more than
198 // * one process.
199 // */
200 // void getProcsForPart(part_t partId, part_t &procMin, part_t &procMax) const
201 // {
202 // env_->localInputAssertion(__FILE__, __LINE__, "invalid part id",
203 // partId >= 0 && partId < nGlobalParts_, BASIC_ASSERTION);
204
205 // partToProcsMap(partId, procMin, procMax);
206 // }
207
208private:
209
210
211 // void setPartDistribution();
212
213 // void setPartSizes(ArrayView<ArrayRCP<part_t> > reqPartIds,
214 // ArrayView<ArrayRCP<scalar_t> > reqPartSizes);
215
216 // void computePartSizes(int widx, ArrayView<part_t> ids,
217 // ArrayView<scalar_t> sizes);
218
219 // void broadcastPartSizes(int widx);
220
221
222 RCP<const Environment> env_; // has application communicator
223 const RCP<const Comm<int> > comm_; // the problem communicator
224
225 // part_t nGlobalParts_;// target global number of parts
226
228 // The algorithm sets these values upon completion.
229
230
231 // There is a decision to made to decide what to store in the solution.
232 // 1. One possibility is to store part numbers for each local id. This
233 // is what was implemented for PartitioninSolution and this was advantageous
234 // for this case since (unlike 2) an extra communication was not needed
235 // after each process assigned its localids a part.
236 // 2. Alternatively, each process can store the set of ids that it owns. For 1D
237 // this would require an additional communication step to place the ids to the
238 // correct processor. This would also complicated the case where number of
239 // parts != number of processes. This is similar to what is needed to build
240 // row or column epetra/tpetra maps.
241 //
242 // However, things are more complicated for 2D Cartesian partitioning (maybe all
243 // of partitioning). In this case, we need to assign matrix nonzeros to both
244 // a process row and a process column. This means that extra communication will
245 // be needed for option #1 in order to determine both of these, which are needed
246 // to determine a part assignment for a given nonzero (or alternatively both the
247 // process rows and column assignments for a 2D block of matrix rows and columns,
248 // although this may complicated part assignment).
249 // This eliminates one of the advantages of method 1 vs. method 2.
250
251 // For method 2 and 2D, each process would store the set of rowIDs and columnIDs
252 // for which it owns the nonzeros. Method 2 still
253 // has the disadvantage that it becomes more complicated for #parts != #procs.
254 // However, it would have what is needed to build both the row and column ids.
255 // For now, we are going with Method #2.
256
257 // Need a plan to handle #parts != #procs
258
259 ArrayRCP<gno_t> rowIDs_; // Row Ids assigned to this process
260 ArrayRCP<gno_t> colIDs_; // Col Ids assigned to this process
261
262 ArrayRCP<gno_t> domainIDs_; // Domain vector Ids assigned to this process
263 ArrayRCP<gno_t> rangeIDs_; // Range vector Ids assigned to this process
264
265
266 bool haveSolution_;
267
268
270 // Algorithm used to compute the solution;
271 // Not sure if this is necessary
272 const RCP<Algorithm<Adapter> > algorithm_;
273};
274
277template <typename Adapter>
279 const RCP<const Comm<int> > &comm, const RCP<Algorithm<Adapter> > &algorithm)
280 : env_(env), comm_(comm), rowIDs_(), colIDs_(), haveSolution_(false),
281 algorithm_(algorithm)
282{
283 env_->memory("After construction of solution");
284}
286
289template <typename Adapter>
290void MatrixPartitioningSolution<Adapter>::setIDLists(ArrayRCP<part_t> &rowIDs,ArrayRCP<part_t> &colIDs,
291 ArrayRCP<part_t> &domainIDs, ArrayRCP<part_t> &rangeIDs)
292{
293 env_->debug(DETAILED_STATUS, "Entering setParts");
294
295 rowIDs_=rowIDs;
296 colIDs_=colIDs;
297 domainIDs_=domainIDs;
298 rangeIDs_=rangeIDs;
299
300 haveSolution_ = true;
301
302 env_->memory("After Solution has processed algorithm's answer");
303 env_->debug(DETAILED_STATUS, "Exiting setParts");
304}
306
307
308
309
310} // namespace Zoltan2
311
312#endif
Zoltan2::BasicUserTypes< zscalar_t, zlno_t, zgno_t > user_t
Definition Metric.cpp:39
Algorithm defines the base class for all algorithms.
A PartitioningSolution is a solution to a partitioning problem.
const RCP< const Comm< int > > & getCommunicator() const
Remap a new partition for maximum overlap with an input partition.
void setIDLists(ArrayRCP< part_t > &rowIDs, ArrayRCP< part_t > &colIDs, ArrayRCP< part_t > &domainIDs, ArrayRCP< part_t > &rangeIDs)
The algorithm uses setIDLists to set the solution.
const RCP< const Environment > & getEnvironment() const
Return the environment associated with the solution.
const gno_t * getRowIdsView() const
Returns list of global row IDs of the nonzeros owned by this process.
MatrixPartitioningSolution(const RCP< const Environment > &env, const RCP< const Comm< int > > &comm, const RCP< Algorithm< Adapter > > &algorithm=Teuchos::null)
Constructor when part sizes are not supplied.
const gno_t * getColIdsView() const
Returns list of global column IDs of the nonzeros owned by this process.
Just a placeholder for now.
map_t::local_ordinal_type lno_t
map_t::global_ordinal_type gno_t
Created by mbenlioglu on Aug 31, 2020.
@ DETAILED_STATUS
sub-steps, each method's entry and exit
SparseMatrixAdapter_t::part_t part_t