Actual source code: matcoloring.c

petsc-3.9.2 2018-05-20
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  1:  #include <petsc/private/matimpl.h>

  3: PetscFunctionList MatColoringList              = 0;
  4: PetscBool         MatColoringRegisterAllCalled = PETSC_FALSE;
  5: const char *const MatColoringWeightTypes[] = {"RANDOM","LEXICAL","LF","SL","MatColoringWeightType","MAT_COLORING_WEIGHT_",0};

  7: /*@C
  8:    MatColoringRegister - Adds a new sparse matrix coloring to the  matrix package.

 10:    Not Collective

 12:    Input Parameters:
 13: +  sname - name of Coloring (for example MATCOLORINGSL)
 14: -  function - function pointer that creates the coloring

 16:    Level: developer

 18:    Sample usage:
 19: .vb
 20:    MatColoringRegister("my_color",MyColor);
 21: .ve

 23:    Then, your partitioner can be chosen with the procedural interface via
 24: $     MatColoringSetType(part,"my_color")
 25:    or at runtime via the option
 26: $     -mat_coloring_type my_color

 28: .keywords: matrix, Coloring, register

 30: .seealso: MatColoringRegisterDestroy(), MatColoringRegisterAll()
 31: @*/
 32: PetscErrorCode  MatColoringRegister(const char sname[],PetscErrorCode (*function)(MatColoring))
 33: {

 37:   PetscFunctionListAdd(&MatColoringList,sname,function);
 38:   return(0);
 39: }

 41: /*@
 42:    MatColoringCreate - Creates a matrix coloring context.

 44:    Collective on MatColoring

 46:    Input Parameters:
 47: .  comm - MPI communicator

 49:    Output Parameter:
 50: .  mcptr - the new MatColoring context

 52:    Options Database Keys:
 53: +   -mat_coloring_type - the type of coloring algorithm used
 54: .   -mat_coloring_maxcolors - the maximum number of relevant colors, all nodes not in a color are in maxcolors+1
 55: .   -mat_coloring_distance - compute a distance 1,2,... coloring.
 56: .   -mat_coloring_view - print information about the coloring and the produced index sets
 57: .   -mat_coloring_test - debugging option that prints all coloring incompatibilities
 58: -   -mat_is_coloring_test - debugging option that throws an error if MatColoringApply() generates an incorrect iscoloring

 60:    Level: beginner

 62:    Notes: A distance one coloring is useful, for example, multi-color SOR. A distance two coloring is for the finite difference computation of Jacobians 
 63:           (see MatFDColoringCreate()).

 65:           Some coloring types only support distance two colorings

 67: .keywords: Coloring, Matrix

 69: .seealso: MatColoring, MatColoringApply(), MatFDColoringCreate()
 70: @*/
 71: PetscErrorCode MatColoringCreate(Mat m,MatColoring *mcptr)
 72: {
 73:   MatColoring    mc;

 79:   *mcptr = NULL;

 81: #if !defined(PETSC_USE_DYNAMIC_LIBRARIES)
 82:   MatInitializePackage();
 83: #endif
 84:   PetscHeaderCreate(mc, MAT_COLORING_CLASSID,"MatColoring","Matrix coloring", "MatColoring",PetscObjectComm((PetscObject)m),MatColoringDestroy, MatColoringView);
 85:   PetscObjectReference((PetscObject)m);
 86:   mc->mat       = m;
 87:   mc->dist      = 2; /* default to Jacobian computation case */
 88:   mc->maxcolors = IS_COLORING_MAX;
 89:   *mcptr        = mc;
 90:   mc->valid     = PETSC_FALSE;
 91:   mc->weight_type = MAT_COLORING_WEIGHT_RANDOM;
 92:   mc->user_weights = NULL;
 93:   mc->user_lperm = NULL;
 94:   return(0);
 95: }


 98: /*@
 99:    MatColoringDestroy - Destroys the matrix coloring context

101:    Collective on MatColoring

103:    Input Parameter:
104: .  mc - the MatColoring context

106:    Level: beginner

108: .keywords: Coloring, destroy

110: .seealso: MatColoringCreate(), MatColoringApply()
111: @*/
112: PetscErrorCode MatColoringDestroy(MatColoring *mc)
113: {

117:   if (--((PetscObject)(*mc))->refct > 0) {*mc = 0; return(0);}
118:   MatDestroy(&(*mc)->mat);
119:   if ((*mc)->ops->destroy) {(*((*mc)->ops->destroy))(*mc);}
120:   if ((*mc)->user_weights) {PetscFree((*mc)->user_weights);}
121:   if ((*mc)->user_lperm) {PetscFree((*mc)->user_lperm);}
122:   PetscHeaderDestroy(mc);
123:   return(0);
124: }

126: /*@C
127:    MatColoringSetType - Sets the type of coloring algorithm used

129:    Collective on MatColoring

131:    Input Parameter:
132: +  mc - the MatColoring context
133: -  type - the type of coloring

135:    Level: beginner

137:    Notes:  Possible types include the sequential types MATCOLORINGLF,
138:    MATCOLORINGSL, and MATCOLORINGID from the MINPACK package as well
139:    as a parallel MATCOLORINGMIS algorithm.

141: .keywords: Coloring, type

143: .seealso: MatColoringCreate(), MatColoringApply()
144: @*/
145: PetscErrorCode MatColoringSetType(MatColoring mc,MatColoringType type)
146: {
147:   PetscBool      match;
148:   PetscErrorCode ierr,(*r)(MatColoring);

153:   PetscObjectTypeCompare((PetscObject)mc,type,&match);
154:   if (match) return(0);
155:    PetscFunctionListFind(MatColoringList,type,&r);
156:   if (!r) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_UNKNOWN_TYPE,"Unable to find requested MatColoring type %s",type);
157:   if (mc->ops->destroy) {
158:     (*(mc)->ops->destroy)(mc);
159:     mc->ops->destroy = NULL;
160:   }
161:   mc->ops->apply            = 0;
162:   mc->ops->view             = 0;
163:   mc->ops->setfromoptions   = 0;
164:   mc->ops->destroy          = 0;

166:   PetscObjectChangeTypeName((PetscObject)mc,type);
167:   (*r)(mc);
168:   return(0);
169: }

171: /*@
172:    MatColoringSetFromOptions - Sets MatColoring options from user parameters

174:    Collective on MatColoring

176:    Input Parameters:
177: .  mc - MatColoring context

179:    Options Database Keys:
180: +   -mat_coloring_type - the type of coloring algorithm used
181: .   -mat_coloring_maxcolors - the maximum number of relevant colors, all nodes not in a color are in maxcolors+1
182: .   -mat_coloring_distance - compute a distance 1,2,... coloring.
183: .   -mat_coloring_view - print information about the coloring and the produced index sets

185:    Level: beginner

187: .keywords: Coloring, Matrix

189: .seealso: MatColoring, MatColoringApply()
190: @*/
191: PetscErrorCode MatColoringSetFromOptions(MatColoring mc)
192: {
193:   PetscBool      flg;
194:   MatColoringType deft = MATCOLORINGSL;
195:   char           type[256];
197:   PetscInt       dist,maxcolors;

201:   MatColoringGetDistance(mc,&dist);
202:   if (dist == 2) deft = MATCOLORINGSL;
203:   else           deft = MATCOLORINGGREEDY;
204:   MatColoringGetMaxColors(mc,&maxcolors);
205:   MatColoringRegisterAll();
206:   PetscObjectOptionsBegin((PetscObject)mc);
207:   if (((PetscObject)mc)->type_name) deft = ((PetscObject)mc)->type_name;
208:   PetscOptionsFList("-mat_coloring_type","The coloring method used","MatColoringSetType",MatColoringList,deft,type,256,&flg);
209:   if (flg) {
210:     MatColoringSetType(mc,type);
211:   } else if (!((PetscObject)mc)->type_name) {
212:     MatColoringSetType(mc,deft);
213:   }
214:   PetscOptionsInt("-mat_coloring_distance","Distance of the coloring","MatColoringSetDistance",dist,&dist,&flg);
215:   if (flg) {MatColoringSetDistance(mc,dist);}
216:   PetscOptionsInt("-mat_coloring_maxcolors","Maximum colors returned at the end. 1 returns an independent set","MatColoringSetMaxColors",maxcolors,&maxcolors,&flg);
217:   if (flg) {MatColoringSetMaxColors(mc,maxcolors);}
218:   if (mc->ops->setfromoptions) {
219:     (*mc->ops->setfromoptions)(PetscOptionsObject,mc);
220:   }
221:   PetscOptionsBool("-mat_coloring_test","Check that a valid coloring has been produced","",mc->valid,&mc->valid,NULL);
222:   PetscOptionsBool("-mat_is_coloring_test","Check that a valid iscoloring has been produced","",mc->valid_iscoloring,&mc->valid_iscoloring,NULL);
223:   PetscOptionsEnum("-mat_coloring_weight_type","Sets the type of vertex weighting used","MatColoringSetWeightType",MatColoringWeightTypes,(PetscEnum)mc->weight_type,(PetscEnum*)&mc->weight_type,NULL);
224:   PetscObjectProcessOptionsHandlers(PetscOptionsObject,(PetscObject)mc);
225:   PetscOptionsEnd();
226:   return(0);
227: }

229: /*@
230:    MatColoringSetDistance - Sets the distance of the coloring

232:    Logically Collective on MatColoring

234:    Input Parameter:
235: .  mc - the MatColoring context
236: .  dist - the distance the coloring should compute

238:    Level: beginner

240:    Notes: The distance of the coloring denotes the minimum number
241:    of edges in the graph induced by the matrix any two vertices
242:    of the same color are.  Distance-1 colorings are the classical
243:    coloring, where no two vertices of the same color are adjacent.
244:    distance-2 colorings are useful for the computation of Jacobians.

246: .keywords: Coloring, distance, Jacobian

248: .seealso: MatColoringGetDistance(), MatColoringApply()
249: @*/
250: PetscErrorCode MatColoringSetDistance(MatColoring mc,PetscInt dist)
251: {
254:   mc->dist = dist;
255:   return(0);
256: }

258: /*@
259:    MatColoringGetDistance - Gets the distance of the coloring

261:    Logically Collective on MatColoring

263:    Input Parameter:
264: .  mc - the MatColoring context

266:    Output Paramter:
267: .  dist - the current distance being used for the coloring.

269:    Level: beginner

271: .keywords: Coloring, distance

273: .seealso: MatColoringSetDistance(), MatColoringApply()
274: @*/
275: PetscErrorCode MatColoringGetDistance(MatColoring mc,PetscInt *dist)
276: {
279:   if (dist) *dist = mc->dist;
280:   return(0);
281: }

283: /*@
284:    MatColoringSetMaxColors - Sets the maximum number of colors

286:    Logically Collective on MatColoring

288:    Input Parameter:
289: +  mc - the MatColoring context
290: -  maxcolors - the maximum number of colors to produce

292:    Level: beginner

294:    Notes:  This may be used to compute a certain number of
295:    independent sets from the graph.  For instance, while using
296:    MATCOLORINGMIS and maxcolors = 1, one gets out an MIS.  Vertices
297:    not in a color are set to have color maxcolors+1, which is not
298:    a valid color as they may be adjacent.

300: .keywords: Coloring

302: .seealso: MatColoringGetMaxColors(), MatColoringApply()
303: @*/
304: PetscErrorCode MatColoringSetMaxColors(MatColoring mc,PetscInt maxcolors)
305: {
308:   mc->maxcolors = maxcolors;
309:   return(0);
310: }

312: /*@
313:    MatColoringGetMaxColors - Gets the maximum number of colors

315:    Logically Collective on MatColoring

317:    Input Parameter:
318: .  mc - the MatColoring context

320:    Output Paramter:
321: .  maxcolors - the current maximum number of colors to produce

323:    Level: beginner

325: .keywords: Coloring

327: .seealso: MatColoringSetMaxColors(), MatColoringApply()
328: @*/
329: PetscErrorCode MatColoringGetMaxColors(MatColoring mc,PetscInt *maxcolors)
330: {
333:   if (maxcolors) *maxcolors = mc->maxcolors;
334:   return(0);
335: }

337: /*@
338:    MatColoringApply - Apply the coloring to the matrix, producing index
339:    sets corresponding to a number of independent sets in the induced
340:    graph.

342:    Collective on MatColoring

344:    Input Parameters:
345: .  mc - the MatColoring context

347:    Output Parameter:
348: .  coloring - the ISColoring instance containing the coloring

350:    Level: beginner

352: .keywords: Coloring, Apply

354: .seealso: MatColoring, MatColoringCreate()
355: @*/
356: PetscErrorCode MatColoringApply(MatColoring mc,ISColoring *coloring)
357: {
358:   PetscErrorCode    ierr;
359:   PetscBool         flg;
360:   PetscViewerFormat format;
361:   PetscViewer       viewer;
362:   PetscInt          nc,ncolors;

366:   PetscLogEventBegin(MATCOLORING_Apply,mc,0,0,0);
367:   (*mc->ops->apply)(mc,coloring);
368:   PetscLogEventEnd(MATCOLORING_Apply,mc,0,0,0);

370:   /* valid */
371:   if (mc->valid) {
372:     MatColoringTest(mc,*coloring);
373:   }
374:   if (mc->valid_iscoloring) {
375:     MatISColoringTest(mc->mat,*coloring);
376:   }

378:   /* view */
379:   PetscOptionsGetViewer(PetscObjectComm((PetscObject)mc),((PetscObject)mc)->prefix,"-mat_coloring_view",&viewer,&format,&flg);
380:   if (flg && !PetscPreLoadingOn) {
381:     PetscViewerPushFormat(viewer,format);
382:     MatColoringView(mc,viewer);
383:     MatGetSize(mc->mat,NULL,&nc);
384:     ISColoringGetIS(*coloring,&ncolors,NULL);
385:     PetscViewerASCIIPrintf(viewer,"  Number of colors %d\n",ncolors);
386:     PetscViewerASCIIPrintf(viewer,"  Number of total columns %d\n",nc);
387:     if (nc <= 1000) {ISColoringView(*coloring,viewer);}
388:     PetscViewerPopFormat(viewer);
389:     PetscViewerDestroy(&viewer);
390:   }
391:   return(0);
392: }

394: /*@
395:    MatColoringView - Output details about the MatColoring.

397:    Collective on MatColoring

399:    Input Parameters:
400: -  mc - the MatColoring context
401: +  viewer - the Viewer context

403:    Level: beginner

405: .keywords: Coloring, view

407: .seealso: MatColoring, MatColoringApply()
408: @*/
409: PetscErrorCode MatColoringView(MatColoring mc,PetscViewer viewer)
410: {
412:   PetscBool      iascii;

416:   if (!viewer) {
417:     PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)mc),&viewer);
418:   }

422:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
423:   if (iascii) {
424:     PetscObjectPrintClassNamePrefixType((PetscObject)mc,viewer);
425:     PetscViewerASCIIPrintf(viewer,"  Weight type: %s\n",MatColoringWeightTypes[mc->weight_type]);
426:     if (mc->maxcolors > 0) {
427:       PetscViewerASCIIPrintf(viewer,"  Distance %D, Max. Colors %D\n",mc->dist,mc->maxcolors);
428:     } else {
429:       PetscViewerASCIIPrintf(viewer,"  Distance %d\n",mc->dist);
430:     }
431:   }
432:   return(0);
433: }

435: /*@
436:    MatColoringSetWeightType - Set the type of weight computation used.

438:    Logically collective on MatColoring

440:    Input Parameters:
441: -  mc - the MatColoring context
442: +  wt - the weight type

444:    Level: beginner

446: .keywords: Coloring, view

448: .seealso: MatColoring, MatColoringWeightType
449: @*/
450: PetscErrorCode MatColoringSetWeightType(MatColoring mc,MatColoringWeightType wt)
451: {
453:   mc->weight_type = wt;
454:   return(0);

456: }