Actual source code: partition.c
petsc-3.10.0 2018-09-12
2: #include <petsc/private/matimpl.h>
4: /* Logging support */
5: PetscClassId MAT_PARTITIONING_CLASSID;
7: /*
8: Simplest partitioning, keeps the current partitioning.
9: */
10: static PetscErrorCode MatPartitioningApply_Current(MatPartitioning part,IS *partitioning)
11: {
13: PetscInt m;
14: PetscMPIInt rank,size;
17: MPI_Comm_size(PetscObjectComm((PetscObject)part),&size);
18: if (part->n != size) {
19: const char *prefix;
20: PetscObjectGetOptionsPrefix((PetscObject)part,&prefix);
21: SETERRQ1(PetscObjectComm((PetscObject)part),PETSC_ERR_SUP,"This is the DEFAULT NO-OP partitioner, it currently only supports one domain per processor\nuse -%smat_partitioning_type parmetis or chaco or ptscotch for more than one subdomain per processor",prefix ? prefix : "");
22: }
23: MPI_Comm_rank(PetscObjectComm((PetscObject)part),&rank);
25: MatGetLocalSize(part->adj,&m,NULL);
26: ISCreateStride(PetscObjectComm((PetscObject)part),m,rank,0,partitioning);
27: return(0);
28: }
30: /*
31: partition an index to rebalance the computation
32: */
33: static PetscErrorCode MatPartitioningApply_Average(MatPartitioning part,IS *partitioning)
34: {
36: PetscInt m,M,nparts,*indices,r,d,*parts,i,start,end,loc;
39: MatGetSize(part->adj,&M,NULL);
40: MatGetLocalSize(part->adj,&m,NULL);
41: nparts = part->n;
42: PetscCalloc1(nparts,&parts);
43: d = M/nparts;
44: for (i=0; i<nparts; i++) parts[i] = d;
45: r = M%nparts;
46: for (i=0; i<r; i++) parts[i] += 1;
47: for (i=1; i<nparts; i++) parts[i] += parts[i-1];
48: PetscCalloc1(m,&indices);
49: MatGetOwnershipRange(part->adj,&start,&end);
50: for (i=start; i<end; i++) {
51: PetscFindInt(i,nparts,parts,&loc);
52: if (loc<0) loc = -(loc+1);
53: else loc = loc+1;
54: indices[i-start] = loc;
55: }
56: PetscFree(parts);
57: ISCreateGeneral(PetscObjectComm((PetscObject)part),m,indices,PETSC_OWN_POINTER,partitioning);
58: return(0);
59: }
61: static PetscErrorCode MatPartitioningApply_Square(MatPartitioning part,IS *partitioning)
62: {
64: PetscInt cell,n,N,p,rstart,rend,*color;
65: PetscMPIInt size;
68: MPI_Comm_size(PetscObjectComm((PetscObject)part),&size);
69: if (part->n != size) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_SUP,"Currently only supports one domain per processor");
70: p = (PetscInt)PetscSqrtReal((PetscReal)part->n);
71: if (p*p != part->n) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_SUP,"Square partitioning requires \"perfect square\" number of domains");
73: MatGetSize(part->adj,&N,NULL);
74: n = (PetscInt)PetscSqrtReal((PetscReal)N);
75: if (n*n != N) SETERRQ(PetscObjectComm((PetscObject)part),PETSC_ERR_SUP,"Square partitioning requires square domain");
76: if (n%p != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Square partitioning requires p to divide n");
77: MatGetOwnershipRange(part->adj,&rstart,&rend);
78: PetscMalloc1(rend-rstart,&color);
79: /* for (int cell=rstart; cell<rend; cell++) { color[cell-rstart] = ((cell%n) < (n/2)) + 2 * ((cell/n) < (n/2)); } */
80: for (cell=rstart; cell<rend; cell++) {
81: color[cell-rstart] = ((cell%n) / (n/p)) + p * ((cell/n) / (n/p));
82: }
83: ISCreateGeneral(PetscObjectComm((PetscObject)part),rend-rstart,color,PETSC_OWN_POINTER,partitioning);
84: return(0);
85: }
87: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Current(MatPartitioning part)
88: {
90: part->ops->apply = MatPartitioningApply_Current;
91: part->ops->view = 0;
92: part->ops->destroy = 0;
93: return(0);
94: }
96: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Average(MatPartitioning part)
97: {
99: part->ops->apply = MatPartitioningApply_Average;
100: part->ops->view = 0;
101: part->ops->destroy = 0;
102: return(0);
103: }
105: PETSC_EXTERN PetscErrorCode MatPartitioningCreate_Square(MatPartitioning part)
106: {
108: part->ops->apply = MatPartitioningApply_Square;
109: part->ops->view = 0;
110: part->ops->destroy = 0;
111: return(0);
112: }
115: /* gets as input the "sizes" array computed by ParMetis_*_NodeND and returns
116: seps[ 0 : 2*p) : the start and end node of each subdomain
117: seps[2*p : 2*p+2*(p-1)) : the start and end node of each separator
118: levels[ 0 : p-1) : level in the tree for each separator (-1 root, -2 and -3 first level and so on)
119: The arrays must be large enough
120: */
121: PETSC_INTERN PetscErrorCode MatPartitioningSizesToSep_Private(PetscInt p, PetscInt sizes[], PetscInt seps[], PetscInt level[])
122: {
123: PetscInt l2p,i,pTree,pStartTree;
127: l2p = PetscLog2Real(p);
128: if (l2p - (PetscInt)PetscLog2Real(p)) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"%D is not a power of 2",p);
129: if (!p) return(0);
130: PetscMemzero(seps,(2*p-2)*sizeof(PetscInt));
131: PetscMemzero(level,(p-1)*sizeof(PetscInt));
132: seps[2*p-2] = sizes[2*p-2];
133: pTree = p;
134: pStartTree = 0;
135: while (pTree != 1) {
136: for (i = pStartTree; i < pStartTree + pTree; i++) {
137: seps[i] += sizes[i];
138: seps[pStartTree + pTree + (i-pStartTree)/2] += seps[i];
139: }
140: pStartTree += pTree;
141: pTree = pTree/2;
142: }
143: seps[2*p-2] -= sizes[2*p-2];
145: pStartTree = 2*p-2;
146: pTree = 1;
147: while (pStartTree > 0) {
148: for (i = pStartTree; i < pStartTree + pTree; i++) {
149: PetscInt k = 2*i - (pStartTree +2*pTree);
150: PetscInt n = seps[k+1];
152: seps[k+1] = seps[i] - sizes[k+1];
153: seps[k] = seps[k+1] + sizes[k+1] - n - sizes[k];
154: level[i-p] = -pTree - i + pStartTree;
155: }
156: pTree *= 2;
157: pStartTree -= pTree;
158: }
159: /* I know there should be a formula */
160: PetscSortIntWithArrayPair(p-1,seps+p,sizes+p,level);
161: for (i=2*p-2;i>=0;i--) { seps[2*i] = seps[i]; seps[2*i+1] = seps[i] + sizes[i] - 1; }
162: return(0);
163: }
165: /* ===========================================================================================*/
167: PetscFunctionList MatPartitioningList = 0;
168: PetscBool MatPartitioningRegisterAllCalled = PETSC_FALSE;
171: /*@C
172: MatPartitioningRegister - Adds a new sparse matrix partitioning to the matrix package.
174: Not Collective
176: Input Parameters:
177: + sname - name of partitioning (for example MATPARTITIONINGCURRENT) or parmetis
178: - function - function pointer that creates the partitioning type
180: Level: developer
182: Sample usage:
183: .vb
184: MatPartitioningRegister("my_part",MyPartCreate);
185: .ve
187: Then, your partitioner can be chosen with the procedural interface via
188: $ MatPartitioningSetType(part,"my_part")
189: or at runtime via the option
190: $ -mat_partitioning_type my_part
192: .keywords: matrix, partitioning, register
194: .seealso: MatPartitioningRegisterDestroy(), MatPartitioningRegisterAll()
195: @*/
196: PetscErrorCode MatPartitioningRegister(const char sname[],PetscErrorCode (*function)(MatPartitioning))
197: {
201: PetscFunctionListAdd(&MatPartitioningList,sname,function);
202: return(0);
203: }
205: /*@C
206: MatPartitioningGetType - Gets the Partitioning method type and name (as a string)
207: from the partitioning context.
209: Not collective
211: Input Parameter:
212: . partitioning - the partitioning context
214: Output Parameter:
215: . type - partitioner type
217: Level: intermediate
219: Not Collective
221: .keywords: Partitioning, get, method, name, type
222: @*/
223: PetscErrorCode MatPartitioningGetType(MatPartitioning partitioning,MatPartitioningType *type)
224: {
228: *type = ((PetscObject)partitioning)->type_name;
229: return(0);
230: }
232: /*@C
233: MatPartitioningSetNParts - Set how many partitions need to be created;
234: by default this is one per processor. Certain partitioning schemes may
235: in fact only support that option.
237: Not collective
239: Input Parameter:
240: . partitioning - the partitioning context
241: . n - the number of partitions
243: Level: intermediate
245: Not Collective
247: .keywords: Partitioning, set
249: .seealso: MatPartitioningCreate(), MatPartitioningApply()
250: @*/
251: PetscErrorCode MatPartitioningSetNParts(MatPartitioning part,PetscInt n)
252: {
254: part->n = n;
255: return(0);
256: }
258: /*@
259: MatPartitioningApplyND - Gets a nested dissection partitioning for a matrix.
261: Collective on Mat
263: Input Parameters:
264: . matp - the matrix partitioning object
266: Output Parameters:
267: . partitioning - the partitioning. For each local node, a positive value indicates the processor
268: number the node has been assigned to. Negative x values indicate the separator level -(x+1).
270: Level: beginner
272: The user can define additional partitionings; see MatPartitioningRegister().
274: .keywords: matrix, get, partitioning
276: .seealso: MatPartitioningRegister(), MatPartitioningCreate(),
277: MatPartitioningDestroy(), MatPartitioningSetAdjacency(), ISPartitioningToNumbering(),
278: ISPartitioningCount()
279: @*/
280: PetscErrorCode MatPartitioningApplyND(MatPartitioning matp,IS *partitioning)
281: {
287: if (!matp->adj->assembled) SETERRQ(PetscObjectComm((PetscObject)matp),PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix");
288: if (matp->adj->factortype) SETERRQ(PetscObjectComm((PetscObject)matp),PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
289: if (!matp->ops->applynd) SETERRQ1(PetscObjectComm((PetscObject)matp),PETSC_ERR_SUP,"Nested dissection not provided by MatPartitioningType %s",((PetscObject)matp)->type_name);
290: PetscLogEventBegin(MAT_PartitioningND,matp,0,0,0);
291: (*matp->ops->applynd)(matp,partitioning);
292: PetscLogEventEnd(MAT_PartitioningND,matp,0,0,0);
294: MatPartitioningViewFromOptions(matp,NULL,"-mat_partitioning_view");
295: ISViewFromOptions(*partitioning,NULL,"-mat_partitioning_view");
296: return(0);
297: }
299: /*@
300: MatPartitioningApply - Gets a partitioning for a matrix.
302: Collective on Mat
304: Input Parameters:
305: . matp - the matrix partitioning object
307: Output Parameters:
308: . partitioning - the partitioning. For each local node this tells the processor
309: number that that node is assigned to.
311: Options Database Keys:
312: To specify the partitioning through the options database, use one of
313: the following
314: $ -mat_partitioning_type parmetis, -mat_partitioning current
315: To see the partitioning result
316: $ -mat_partitioning_view
318: Level: beginner
320: The user can define additional partitionings; see MatPartitioningRegister().
322: .keywords: matrix, get, partitioning
324: .seealso: MatPartitioningRegister(), MatPartitioningCreate(),
325: MatPartitioningDestroy(), MatPartitioningSetAdjacency(), ISPartitioningToNumbering(),
326: ISPartitioningCount()
327: @*/
328: PetscErrorCode MatPartitioningApply(MatPartitioning matp,IS *partitioning)
329: {
335: if (!matp->adj->assembled) SETERRQ(PetscObjectComm((PetscObject)matp),PETSC_ERR_ARG_WRONGSTATE,"Not for unassembled matrix");
336: if (matp->adj->factortype) SETERRQ(PetscObjectComm((PetscObject)matp),PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
337: if (!matp->ops->apply) SETERRQ(PetscObjectComm((PetscObject)matp),PETSC_ERR_ARG_WRONGSTATE,"Must set type with MatPartitioningSetFromOptions() or MatPartitioningSetType()");
338: PetscLogEventBegin(MAT_Partitioning,matp,0,0,0);
339: (*matp->ops->apply)(matp,partitioning);
340: PetscLogEventEnd(MAT_Partitioning,matp,0,0,0);
342: MatPartitioningViewFromOptions(matp,NULL,"-mat_partitioning_view");
343: ISViewFromOptions(*partitioning,NULL,"-mat_partitioning_view");
344: return(0);
345: }
347: /*@
348: MatPartitioningSetAdjacency - Sets the adjacency graph (matrix) of the thing to be
349: partitioned.
351: Collective on MatPartitioning and Mat
353: Input Parameters:
354: + part - the partitioning context
355: - adj - the adjacency matrix
357: Level: beginner
359: .keywords: Partitioning, adjacency
361: .seealso: MatPartitioningCreate()
362: @*/
363: PetscErrorCode MatPartitioningSetAdjacency(MatPartitioning part,Mat adj)
364: {
368: part->adj = adj;
369: return(0);
370: }
372: /*@
373: MatPartitioningDestroy - Destroys the partitioning context.
375: Collective on Partitioning
377: Input Parameters:
378: . part - the partitioning context
380: Level: beginner
382: .keywords: Partitioning, destroy, context
384: .seealso: MatPartitioningCreate()
385: @*/
386: PetscErrorCode MatPartitioningDestroy(MatPartitioning *part)
387: {
391: if (!*part) return(0);
393: if (--((PetscObject)(*part))->refct > 0) {*part = 0; return(0);}
395: if ((*part)->ops->destroy) {
396: (*(*part)->ops->destroy)((*part));
397: }
398: PetscFree((*part)->vertex_weights);
399: PetscFree((*part)->part_weights);
400: PetscHeaderDestroy(part);
401: return(0);
402: }
404: /*@C
405: MatPartitioningSetVertexWeights - Sets the weights for vertices for a partitioning.
407: Logically Collective on Partitioning
409: Input Parameters:
410: + part - the partitioning context
411: - weights - the weights, on each process this array must have the same size as the number of local rows
413: Level: beginner
415: Notes:
416: The array weights is freed by PETSc so the user should not free the array. In C/C++
417: the array must be obtained with a call to PetscMalloc(), not malloc().
419: .keywords: Partitioning, destroy, context
421: .seealso: MatPartitioningCreate(), MatPartitioningSetType(), MatPartitioningSetPartitionWeights()
422: @*/
423: PetscErrorCode MatPartitioningSetVertexWeights(MatPartitioning part,const PetscInt weights[])
424: {
430: PetscFree(part->vertex_weights);
432: part->vertex_weights = (PetscInt*)weights;
433: return(0);
434: }
436: /*@C
437: MatPartitioningSetPartitionWeights - Sets the weights for each partition.
439: Logically Collective on Partitioning
441: Input Parameters:
442: + part - the partitioning context
443: - weights - An array of size nparts that is used to specify the fraction of
444: vertex weight that should be distributed to each sub-domain for
445: the balance constraint. If all of the sub-domains are to be of
446: the same size, then each of the nparts elements should be set
447: to a value of 1/nparts. Note that the sum of all of the weights
448: should be one.
450: Level: beginner
452: Notes:
453: The array weights is freed by PETSc so the user should not free the array. In C/C++
454: the array must be obtained with a call to PetscMalloc(), not malloc().
456: .keywords: Partitioning, destroy, context
458: .seealso: MatPartitioningCreate(), MatPartitioningSetType(), MatPartitioningSetVertexWeights()
459: @*/
460: PetscErrorCode MatPartitioningSetPartitionWeights(MatPartitioning part,const PetscReal weights[])
461: {
467: PetscFree(part->part_weights);
469: part->part_weights = (PetscReal*)weights;
470: return(0);
471: }
473: /*@
474: MatPartitioningCreate - Creates a partitioning context.
476: Collective on MPI_Comm
478: Input Parameter:
479: . comm - MPI communicator
481: Output Parameter:
482: . newp - location to put the context
484: Level: beginner
486: .keywords: Partitioning, create, context
488: .seealso: MatPartitioningSetType(), MatPartitioningApply(), MatPartitioningDestroy(),
489: MatPartitioningSetAdjacency()
491: @*/
492: PetscErrorCode MatPartitioningCreate(MPI_Comm comm,MatPartitioning *newp)
493: {
494: MatPartitioning part;
495: PetscErrorCode ierr;
496: PetscMPIInt size;
499: *newp = 0;
501: MatInitializePackage();
502: PetscHeaderCreate(part,MAT_PARTITIONING_CLASSID,"MatPartitioning","Matrix/graph partitioning","MatOrderings",comm,MatPartitioningDestroy,MatPartitioningView);
503: part->vertex_weights = NULL;
504: part->part_weights = NULL;
506: MPI_Comm_size(comm,&size);
507: part->n = (PetscInt)size;
509: *newp = part;
510: return(0);
511: }
513: /*@C
514: MatPartitioningView - Prints the partitioning data structure.
516: Collective on MatPartitioning
518: Input Parameters:
519: . part - the partitioning context
520: . viewer - optional visualization context
522: Level: intermediate
524: Note:
525: The available visualization contexts include
526: + PETSC_VIEWER_STDOUT_SELF - standard output (default)
527: - PETSC_VIEWER_STDOUT_WORLD - synchronized standard
528: output where only the first processor opens
529: the file. All other processors send their
530: data to the first processor to print.
532: The user can open alternative visualization contexts with
533: . PetscViewerASCIIOpen() - output to a specified file
535: .keywords: Partitioning, view
537: .seealso: PetscViewerASCIIOpen()
538: @*/
539: PetscErrorCode MatPartitioningView(MatPartitioning part,PetscViewer viewer)
540: {
542: PetscBool iascii;
546: if (!viewer) {
547: PetscViewerASCIIGetStdout(PetscObjectComm((PetscObject)part),&viewer);
548: }
552: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
553: if (iascii) {
554: PetscObjectPrintClassNamePrefixType((PetscObject)part,viewer);
555: if (part->vertex_weights) {
556: PetscViewerASCIIPrintf(viewer," Using vertex weights\n");
557: }
558: }
559: if (part->ops->view) {
560: PetscViewerASCIIPushTab(viewer);
561: (*part->ops->view)(part,viewer);
562: PetscViewerASCIIPopTab(viewer);
563: }
564: return(0);
565: }
567: /*@C
568: MatPartitioningSetType - Sets the type of partitioner to use
570: Collective on MatPartitioning
572: Input Parameter:
573: . part - the partitioning context.
574: . type - a known method
576: Options Database Command:
577: $ -mat_partitioning_type <type>
578: $ Use -help for a list of available methods
579: $ (for instance, parmetis)
581: Level: intermediate
583: .keywords: partitioning, set, method, type
585: .seealso: MatPartitioningCreate(), MatPartitioningApply(), MatPartitioningType
587: @*/
588: PetscErrorCode MatPartitioningSetType(MatPartitioning part,MatPartitioningType type)
589: {
590: PetscErrorCode ierr,(*r)(MatPartitioning);
591: PetscBool match;
597: PetscObjectTypeCompare((PetscObject)part,type,&match);
598: if (match) return(0);
600: if (part->ops->destroy) {
601: (*part->ops->destroy)(part);
603: part->ops->destroy = NULL;
604: part->data = 0;
605: part->setupcalled = 0;
606: }
608: PetscFunctionListFind(MatPartitioningList,type,&r);
609: if (!r) SETERRQ1(PetscObjectComm((PetscObject)part),PETSC_ERR_ARG_UNKNOWN_TYPE,"Unknown partitioning type %s",type);
611: part->ops->destroy = (PetscErrorCode (*)(MatPartitioning)) 0;
612: part->ops->view = (PetscErrorCode (*)(MatPartitioning,PetscViewer)) 0;
614: (*r)(part);
616: PetscFree(((PetscObject)part)->type_name);
617: PetscStrallocpy(type,&((PetscObject)part)->type_name);
618: return(0);
619: }
621: /*@
622: MatPartitioningSetFromOptions - Sets various partitioning options from the
623: options database.
625: Collective on MatPartitioning
627: Input Parameter:
628: . part - the partitioning context.
630: Options Database Command:
631: $ -mat_partitioning_type <type>
632: $ Use -help for a list of available methods
633: $ (for instance, parmetis)
636: Notes:
637: If the partitioner has not been set by the user it uses one of the installed partitioner such as ParMetis. If there are
638: no installed partitioners it uses current which means no repartioning.
640: Level: beginner
642: .keywords: partitioning, set, method, type
643: @*/
644: PetscErrorCode MatPartitioningSetFromOptions(MatPartitioning part)
645: {
647: PetscBool flag;
648: char type[256];
649: const char *def;
652: PetscObjectOptionsBegin((PetscObject)part);
653: if (!((PetscObject)part)->type_name) {
654: #if defined(PETSC_HAVE_PARMETIS)
655: def = MATPARTITIONINGPARMETIS;
656: #elif defined(PETSC_HAVE_CHACO)
657: def = MATPARTITIONINGCHACO;
658: #elif defined(PETSC_HAVE_PARTY)
659: def = MATPARTITIONINGPARTY;
660: #elif defined(PETSC_HAVE_PTSCOTCH)
661: def = MATPARTITIONINGPTSCOTCH;
662: #else
663: def = MATPARTITIONINGCURRENT;
664: #endif
665: } else {
666: def = ((PetscObject)part)->type_name;
667: }
668: PetscOptionsFList("-mat_partitioning_type","Type of partitioner","MatPartitioningSetType",MatPartitioningList,def,type,256,&flag);
669: if (flag) {
670: MatPartitioningSetType(part,type);
671: }
672: /*
673: Set the type if it was never set.
674: */
675: if (!((PetscObject)part)->type_name) {
676: MatPartitioningSetType(part,def);
677: }
679: if (part->ops->setfromoptions) {
680: (*part->ops->setfromoptions)(PetscOptionsObject,part);
681: }
682: PetscOptionsEnd();
683: return(0);
684: }