Actual source code: ex2.c
1: /*$Id: ex2.c,v 1.40 2001/04/10 19:37:19 bsmith Exp $*/
3: static char help[] = "Reads a a simple unstructured grid from a file. Partitions it,n
4: and distributes the grid data accordinglynn";
6: /*T
7: Concepts: Mat^partitioning a matrix;
8: Processors: n
9: T*/
11: /*
12: Updates of this example MAY be found at
13: http://www.mcs.anl.gov/petsc/src/dm/ao/examples/tutorials/ex2.c
15: This is a very basic, even crude, example of managing an unstructured
16: grid in parallel.
18: This particular code is for a Galerkin-style finite element method.
20: After the calls below, each processor will have
21: 1) a list of elements it "owns"; for each "owned" element it will have the global
22: numbering of the three vertices; stored in gdata->ele;
23: 2) a list of vertices it "owns". For each owned it will have the x and y
24: coordinates; stored in gdata->vert
26: It will not have
27: 1) list of ghost elements (since they are not needed for traditional
28: Galerkin style finite element methods). For various finite volume methods
29: you may need the ghost element lists, these may be generated using the
30: element neighbor information given in the file database.
32: To compute the local element stiffness matrix and load vector, each processor
33: will need the vertex coordinates for all of the vertices on the locally
34: "owned" elements. This data could be obtained by doing the appropriate vector
35: scatter on the data stored in gdata->vert; we haven't had time to demonstrate this.
37: Clearly writing a complete parallel unstructured grid code with PETSc is still
38: a good deal of work and requires a lot of application level coding. BUT, at least
39: PETSc can manage all of the nonlinear and linear solvers (including matrix assembly
40: etc.), which allows the programmer to concentrate his or her efforts on managing
41: the unstructured grid. The PETSc team is developing additional library objects
42: to help manage parallel unstructured grid computations. Unfortunately we have
43: not had time to complete these yet, so the application programmer still must
44: manage much of the parallel grid manipulation as indicated below.
46: */
48: /*
49: Include "petscmat.h" so that we can use matrices.
50: automatically includes:
51: petsc.h - base PETSc routines petscvec.h - vectors
52: petscsys.h - system routines petscmat.h - matrices
53: petscis.h - index sets petscviewer.h - viewers
55: Include "petscao.h" allows use of the AO (application ordering) commands,
56: used below for renumbering the vertex numbers after the partitioning.
58: Include "petscbt.h" for managing logical bit arrays that are used to
59: conserve space. Note that the code does use order N bit arrays on each
60: processor so is theoretically not scalable, but even with 64 million
61: vertices it will only need temporarily 8 megabytes of memory for the
62: bit array so one can still do very large problems with this approach,
63: since the bit arrays are freed before the vectors and matrices are
64: created.
65: */
66: #include "petscmat.h"
67: #include "petscao.h"
68: #include "petscbt.h"
70: /*
71: This is the user-defined grid data context
72: */
73: typedef struct {
74: int n_vert,n_ele;
75: int mlocal_vert,mlocal_ele;
76: int *ele;
77: Scalar *vert;
78: int *ia,*ja;
79: IS isnewproc;
80: int *localvert,nlocal; /* used to stash temporarily old global vertex number of new vertex */
81: } GridData;
83: /*
84: Variables on all processors:
85: n_vert - total number of vertices
86: mlocal_vert - number of vertices on this processor
87: vert - x,y coordinates of local vertices
89: n_ele - total number of elements
90: mlocal_ele - number of elements on this processor
91: ele - vertices of elements on this processor
93: ia, ja - adjacency graph of elements (for partitioning)
94:
95: Variables on processor 0 during data reading from file:
96: mmlocal_vert[i] - number of vertices on each processor
97: tmpvert - x,y coordinates of vertices on any processor (as read in)
99: mmlocal_ele[i] - number of elements on each processor
101: tmpia, tmpja - adjacency graph of elements for other processors
103: Notes:
104: The code below has a great deal of IO (print statements). This is to allow one to track
105: the renumbering and movement of data among processors. In an actual
106: production run, IO of this type would be deactivated.
108: To use the ParMETIS partitioner run with the option -mat_partitioning_type parmetis
109: otherwise it defaults to the initial element partitioning induced when the data
110: is read in.
112: To understand the parallel performance of this type of code, it is important
113: to profile the time spent in various events in the code; running with the
114: option -log_summary will indicate how much time is spent in the routines
115: below. Of course, for very small problems, such as the sample grid used here,
116: the profiling results are meaningless.
117: */
119: extern int DataRead(GridData *);
120: extern int DataPartitionElements(GridData *);
121: extern int DataMoveElements(GridData *);
122: extern int DataPartitionVertices(GridData *);
123: extern int DataMoveVertices(GridData *);
124: extern int DataDestroy(GridData *);
126: int main(int argc,char **args)
127: {
128: int ierr;
129: int READ_EVENT,PARTITION_ELEMENT_EVENT,MOVE_ELEMENT_EVENT;
130: int PARTITION_VERTEX_EVENT,MOVE_VERTEX_EVENT;
131: GridData gdata;
133: PetscInitialize(&argc,&args,(char *)0,help);
135: PetscLogEventRegister(&READ_EVENT, "Read Data","red");
136: PetscLogEventRegister(&PARTITION_ELEMENT_EVENT,"Partition elemen","blue");
137: PetscLogEventRegister(&MOVE_ELEMENT_EVENT, "Move elements","green");
138: PetscLogEventRegister(&PARTITION_VERTEX_EVENT, "Partition vertic","orange");
139: PetscLogEventRegister(&MOVE_VERTEX_EVENT, "Move vertices","yellow");
141: PetscLogEventBegin(READ_EVENT,0,0,0,0);
142: DataRead(&gdata);
143: PetscLogEventEnd(READ_EVENT,0,0,0,0);
144: PetscLogEventBegin(PARTITION_ELEMENT_EVENT,0,0,0,0);
145: DataPartitionElements(&gdata);
146: PetscLogEventEnd(PARTITION_ELEMENT_EVENT,0,0,0,0);
147: PetscLogEventBegin(MOVE_ELEMENT_EVENT,0,0,0,0);
148: DataMoveElements(&gdata);
149: PetscLogEventEnd(MOVE_ELEMENT_EVENT,0,0,0,0);
150: PetscLogEventBegin(PARTITION_VERTEX_EVENT,0,0,0,0);
151: DataPartitionVertices(&gdata);
152: PetscLogEventEnd(PARTITION_VERTEX_EVENT,0,0,0,0);
153: PetscLogEventBegin(MOVE_VERTEX_EVENT,0,0,0,0);
154: DataMoveVertices(&gdata);
155: PetscLogEventEnd(MOVE_VERTEX_EVENT,0,0,0,0);
156: DataDestroy(&gdata);
158: PetscFinalize();
159: return 0;
160: }
163: /*
164: Reads in the grid data from a file; each processor is naively
165: assigned a continuous chunk of vertex and element data. Later the data
166: will be partitioned and moved to the appropriate processor.
167: */
168: int DataRead(GridData *gdata)
169: {
170: int rank,size,n_vert,*mmlocal_vert,mlocal_vert,i,*ia,*ja,cnt,j;
171: int mlocal_ele,*mmlocal_ele,*ele,*tmpele,n_ele,net,a1,a2,a3;
172: int *iatmp,*jatmp,ierr;
173: char msg[128];
174: Scalar *vert,*tmpvert;
175: MPI_Status status;
178: /*
179: Processor 0 opens the file, reads in chunks of data and sends a portion off to
180: each other processor.
182: Note: For a truely scalable IO portion of the code, one would store
183: the grid data in a binary file and use MPI-IO commands to have each
184: processor read in the parts that it needs. However in most circumstances
185: involving up to a say a million nodes and 100 processors this approach
186: here is fine.
187: */
188: MPI_Comm_size(PETSC_COMM_WORLD,&size);
189: MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
191: if (!rank) {
192: FILE *fd;
193: fd = fopen("usgdata","r"); if (!fd) SETERRQ(1,"Cannot open grid file");
195: /* read in number of vertices */
196: fgets(msg,128,fd);
197: printf("File msg:%s",msg);
198: fscanf(fd,"Number Vertices = %dn",&n_vert);
199: printf("Number of grid vertices %dn",n_vert);
201: /* broadcast number of vertices to all processors */
202: MPI_Bcast(&n_vert,1,MPI_INT,0,PETSC_COMM_WORLD);
203: mlocal_vert = n_vert/size + ((n_vert % size) > 0);
205: /*
206: allocate enough room for the first processor to keep track of how many
207: vertices are assigned to each processor. Splitting vertices equally amoung
208: all processors.
209: */
210: PetscMalloc(size*sizeof(int),&mmlocal_vert);
211: for (i=0; i<size; i++) {
212: mmlocal_vert[i] = n_vert/size + ((n_vert % size) > i);
213: printf("Processor %d assigned %d verticesn",i,mmlocal_vert[i]);
214: }
216: /*
217: Read in vertices assigned to first processor
218: */
219: PetscMalloc(2*mmlocal_vert[0]*sizeof(double),&vert);
220: printf("Vertices assigned to processor 0n");
221: for (i=0; i<mlocal_vert; i++) {
222: fscanf(fd,"%d %lf %lfn",&cnt,vert+2*i,vert+2*i+1);
223: printf("%d %g %gn",cnt,vert[2*i],vert[2*i+1]);
224: }
226: /*
227: Read in vertices for all the other processors
228: */
229: PetscMalloc(2*mmlocal_vert[0]*sizeof(double),&tmpvert);
230: for (j=1; j<size; j++) {
231: printf("Vertices assigned to processor %dn",j);
232: for (i=0; i<mmlocal_vert[j]; i++) {
233: fscanf(fd,"%d %lf %lfn",&cnt,tmpvert+2*i,tmpvert+2*i+1);
234: printf("%d %g %gn",cnt,tmpvert[2*i],tmpvert[2*i+1]);
235: }
236: MPI_Send(tmpvert,2*mmlocal_vert[j],MPI_DOUBLE,j,0,PETSC_COMM_WORLD);
237: }
238: PetscFree(tmpvert);
239: PetscFree(mmlocal_vert);
241: fscanf(fd,"Number Elements = %dn",&n_ele);
242: printf("Number of grid elements %dn",n_ele);
244: /*
245: Broadcast number of elements to all processors
246: */
247: MPI_Bcast(&n_ele,1,MPI_INT,0,PETSC_COMM_WORLD);
248: mlocal_ele = n_ele/size + ((n_ele % size) > 0);
250: /*
251: Allocate enough room for the first processor to keep track of how many
252: elements are assigned to each processor.
253: */
254: PetscMalloc(size*sizeof(int),&mmlocal_ele);
255: for (i=0; i<size; i++) {
256: mmlocal_ele[i] = n_ele/size + ((n_ele % size) > i);
257: printf("Processor %d assigned %d elementsn",i,mmlocal_ele[i]);
258: }
259:
260: /*
261: read in element information for the first processor
262: */
263: PetscMalloc(3*mmlocal_ele[0]*sizeof(int),&ele);
264: printf("Elements assigned to processor 0n");
265: for (i=0; i<mlocal_ele; i++) {
266: fscanf(fd,"%d %d %d %dn",&cnt,ele+3*i,ele+3*i+1,ele+3*i+2);
267: printf("%d %d %d %dn",cnt,ele[3*i],ele[3*i+1],ele[3*i+2]);
268: }
270: /*
271: Read in elements for all the other processors
272: */
273: PetscMalloc(3*mmlocal_ele[0]*sizeof(int),&tmpele);
274: for (j=1; j<size; j++) {
275: printf("Elements assigned to processor %dn",j);
276: for (i=0; i<mmlocal_ele[j]; i++) {
277: fscanf(fd,"%d %d %d %dn",&cnt,tmpele+3*i,tmpele+3*i+1,tmpele+3*i+2);
278: printf("%d %d %d %dn",cnt,tmpele[3*i],tmpele[3*i+1],tmpele[3*i+2]);
279: }
280: MPI_Send(tmpele,3*mmlocal_ele[j],MPI_INT,j,0,PETSC_COMM_WORLD);
281: }
282: PetscFree(tmpele);
284: /*
285: Read in element neighbors for processor 0
286: We don't know how many spaces in ja[] to allocate so we allocate
287: 3*the number of local elements, this is the maximum it could be
288: */
289: PetscMalloc((mlocal_ele+1)*sizeof(int),&ia);
290: PetscMalloc((3*mlocal_ele+1)*sizeof(int),&ja);
291: net = 0;
292: ia[0] = 0;
293: printf("Element neighbors on processor 0n");
294: fgets(msg,128,fd);
295: for (i=0; i<mlocal_ele; i++) {
296: fscanf(fd,"%d %d %d %dn",&cnt,&a1,&a2,&a3);
297: printf("%d %d %d %dn",cnt,a1,a2,a3);
298: if (a1 >= 0) {ja[net++] = a1;}
299: if (a2 >= 0) {ja[net++] = a2;}
300: if (a3 >= 0) {ja[net++] = a3;}
301: ia[i+1] = net;
302: }
304: printf("ia values for processor 0n");
305: for (i=0; i<mlocal_ele+1; i++) {
306: printf("%d ",ia[i]);
307: }
308: printf("n");
309: printf("ja values for processor 0n");
310: for (i=0; i<ia[mlocal_ele]; i++) {
311: printf("%d ",ja[i]);
312: }
313: printf("n");
315: /*
316: Read in element neighbor information for all other processors
317: */
318: PetscMalloc((mlocal_ele+1)*sizeof(int),&iatmp);
319: PetscMalloc((3*mlocal_ele+1)*sizeof(int),&jatmp);
320: for (j=1; j<size; j++) {
321: net = 0;
322: iatmp[0] = 0;
323: printf("Element neighbors on processor %dn",j);
324: for (i=0; i<mmlocal_ele[j]; i++) {
325: fscanf(fd,"%d %d %d %dn",&cnt,&a1,&a2,&a3);
326: printf("%d %d %d %dn",cnt,a1,a2,a3);
327: if (a1 >= 0) {jatmp[net++] = a1;}
328: if (a2 >= 0) {jatmp[net++] = a2;}
329: if (a3 >= 0) {jatmp[net++] = a3;}
330: iatmp[i+1] = net;
331: }
333: printf("ia values for processor %dn",j);
334: for (i=0; i<mmlocal_ele[j]+1; i++) {
335: printf("%d ",iatmp[i]);
336: }
337: printf("n");
338: printf("ja values for processor %dn",j);
339: for (i=0; i<iatmp[mmlocal_ele[j]]; i++) {
340: printf("%d ",jatmp[i]);
341: }
342: printf("n");
344: /* send graph off to appropriate processor */
345: MPI_Send(iatmp,mmlocal_ele[j]+1,MPI_INT,j,0,PETSC_COMM_WORLD);
346: MPI_Send(jatmp,iatmp[mmlocal_ele[j]],MPI_INT,j,0,PETSC_COMM_WORLD);
347: }
348: PetscFree(iatmp);
349: PetscFree(jatmp);
350: PetscFree(mmlocal_ele);
352: fclose(fd);
353: } else {
354: /*
355: We are not the zeroth processor so we do not open the file
356: rather we wait for processor 0 to send us our data.
357: */
359: /* receive total number of vertices */
360: MPI_Bcast(&n_vert,1,MPI_INT,0,PETSC_COMM_WORLD);
361: mlocal_vert = n_vert/size + ((n_vert % size) > rank);
363: /* receive vertices */
364: PetscMalloc(2*(mlocal_vert+1)*sizeof(double),&vert);
365: MPI_Recv(vert,2*mlocal_vert,MPI_DOUBLE,0,0,PETSC_COMM_WORLD,&status);
367: /* receive total number of elements */
368: MPI_Bcast(&n_ele,1,MPI_INT,0,PETSC_COMM_WORLD);
369: mlocal_ele = n_ele/size + ((n_ele % size) > rank);
371: /* receive elements */
372: PetscMalloc(3*(mlocal_ele+1)*sizeof(int),&ele);
373: MPI_Recv(ele,3*mlocal_ele,MPI_INT,0,0,PETSC_COMM_WORLD,&status);
375: /* receive element adjacency graph */
376: PetscMalloc((mlocal_ele+1)*sizeof(int),&ia);
377: MPI_Recv(ia,mlocal_ele+1,MPI_INT,0,0,PETSC_COMM_WORLD,&status);
379: PetscMalloc((ia[mlocal_ele]+1)*sizeof(int),&ja);
380: MPI_Recv(ja,ia[mlocal_ele],MPI_INT,0,0,PETSC_COMM_WORLD,&status);
381: }
383: gdata->n_vert = n_vert;
384: gdata->n_ele = n_ele;
385: gdata->mlocal_vert = mlocal_vert;
386: gdata->mlocal_ele = mlocal_ele;
387: gdata->ele = ele;
388: gdata->vert = vert;
390: gdata->ia = ia;
391: gdata->ja = ja;
393: return(0);
394: }
397: /*
398: Given the grid data spread across the processors, determines a
399: new partitioning of the CELLS (elements) to reduce the number of cut edges between
400: cells (elements).
401: */
402: int DataPartitionElements(GridData *gdata)
403: {
404: Mat Adj; /* adjacency matrix */
405: int *ia,*ja;
406: int mlocal_ele,n_ele,ierr;
407: MatPartitioning part;
408: IS isnewproc;
411: n_ele = gdata->n_ele;
412: mlocal_ele = gdata->mlocal_ele;
414: ia = gdata->ia;
415: ja = gdata->ja;
417: /*
418: Create the adjacency graph matrix
419: */
420: MatCreateMPIAdj(PETSC_COMM_WORLD,mlocal_ele,n_ele,ia,ja,PETSC_NULL,&Adj);
422: /*
423: Create the partioning object
424: */
425: MatPartitioningCreate(PETSC_COMM_WORLD,&part);
426: MatPartitioningSetAdjacency(part,Adj);
427: MatPartitioningSetFromOptions(part);
428: MatPartitioningApply(part,&isnewproc);
429: MatPartitioningDestroy(part);
431: /*
432: isnewproc - indicates for each local element the new processor it is assigned to
433: */
434: PetscPrintf(PETSC_COMM_WORLD,"New processor assignment for each elementn");
435: ISView(isnewproc,PETSC_VIEWER_STDOUT_WORLD);
436: gdata->isnewproc = isnewproc;
438: /*
439: Free the adjacency graph data structures
440: */
441: MatDestroy(Adj);
444: return(0);
445: }
447: /*
448: Moves the grid element data to be on the correct processor for the new
449: element partitioning.
450: */
451: int DataMoveElements(GridData *gdata)
452: {
453: int ierr,*counts,rank,size,i,*idx;
454: Vec vele,veleold;
455: Scalar *array;
456: IS isscat,isnum;
457: VecScatter vecscat;
461: MPI_Comm_size(PETSC_COMM_WORLD,&size);
462: MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
464: /*
465: Determine how many elements are assigned to each processor
466: */
467: PetscMalloc(size*sizeof(int),&counts);
468: ierr = ISPartitioningCount(gdata->isnewproc,counts);
470: /*
471: Create a vector to contain the newly ordered element information
473: Note: we use vectors to communicate this data since we can use the powerful
474: VecScatter routines to get the data to the correct location. This is a little
475: wasteful since the vectors hold double precision numbers instead of integers,
476: but since this is just a setup phase in the entire numerical computation that
477: is only called once it is not a measureable performance bottleneck.
478: */
479: VecCreateMPI(PETSC_COMM_WORLD,3*counts[rank],PETSC_DECIDE,&vele);
481: /*
482: Create an index set from the isnewproc index set to indicate the mapping TO
483: */
484: ISPartitioningToNumbering(gdata->isnewproc,&isnum);
485: ISDestroy(gdata->isnewproc);
486: /*
487: There are three data items per cell (element), the integer vertex numbers of its three
488: coordinates (we convert to double to use the scatter) (one can think
489: of the vectors of having a block size of 3 and there is one index in idx[] for each block)
490: */
491: ISGetIndices(isnum,&idx);
492: for (i=0; i<gdata->mlocal_ele; i++) {
493: idx[i] *= 3;
494: }
495: ISCreateBlock(PETSC_COMM_WORLD,3,gdata->mlocal_ele,idx,&isscat);
496: ISRestoreIndices(isnum,&idx);
497: ISDestroy(isnum);
499: /*
500: Create a vector to contain the old ordered element information
501: */
502: VecCreateSeq(PETSC_COMM_SELF,3*gdata->mlocal_ele,&veleold);
503: VecGetArray(veleold,&array);
504: for (i=0; i<3*gdata->mlocal_ele; i++) {
505: array[i] = gdata->ele[i];
506: }
507: VecRestoreArray(veleold,&array);
508:
509: /*
510: Scatter the element vertex information to the correct processor
511: */
512: VecScatterCreate(veleold,PETSC_NULL,vele,isscat,&vecscat);
513: ISDestroy(isscat);
514: VecScatterBegin(veleold,vele,INSERT_VALUES,SCATTER_FORWARD,vecscat);
515: VecScatterEnd(veleold,vele,INSERT_VALUES,SCATTER_FORWARD,vecscat);
516: VecScatterDestroy(vecscat);
517: VecDestroy(veleold);
519: /*
520: Put the element vertex data into a new allocation of the gdata->ele
521: */
522: PetscFree(gdata->ele);
523: gdata->mlocal_ele = counts[rank];
524: PetscFree(counts);
525: PetscMalloc(3*gdata->mlocal_ele*sizeof(int),&gdata->ele);
526: VecGetArray(vele,&array);
527: for (i=0; i<3*gdata->mlocal_ele; i++) {
528: gdata->ele[i] = (int)PetscRealPart(array[i]);
529: }
530: VecRestoreArray(vele,&array);
531: VecDestroy(vele);
533: PetscPrintf(PETSC_COMM_WORLD,"Old vertex numbering in new element orderingn");
534: PetscSynchronizedPrintf(PETSC_COMM_WORLD,"Processor %dn",rank);
535: for (i=0; i<gdata->mlocal_ele; i++) {
536: PetscSynchronizedPrintf(PETSC_COMM_WORLD,"%d %d %d %dn",i,gdata->ele[3*i],gdata->ele[3*i+1],
537: gdata->ele[3*i+2]);
538: }
539: PetscSynchronizedFlush(PETSC_COMM_WORLD);
541: return(0);
542: }
544: /*
545: Given the newly partitioned cells (elements), this routine partitions the
546: vertices.
548: The code is not completely scalable since it requires
549: 1) O(n_vert) bits per processor memory
550: 2) uses O(size) stages of communication; each of size O(n_vert) bits
551: 3) it is sequential (each processor marks it vertices ONLY after all processors
552: to the left have marked theirs.
553: 4) the amount of work on the last processor is O(n_vert)
555: The algorithm also does not take advantage of vertices that are "interior" to a
556: processors elements (that is; is not contained in any element on another processor).
557: A better algorithm would first have all processors determine "interior" vertices and
558: make sure they are retained on that processor before listing "boundary" vertices.
560: The algorithm is:
561: a) each processor waits for a message from the left containing mask of all marked vertices
562: b) it loops over all local elements, generating a list of vertices it will
563: claim (not claiming ones that have already been marked in the bit-array)
564: it claims at most n_vert/size vertices
565: c) it sends to the right the mask
567: This is a quick-and-dirty implementation; it should work fine for many problems,
568: but will need to be replaced once profiling shows that it takes a large amount of
569: time. An advantage is it requires no searching or sorting.
570:
571: */
572: int DataPartitionVertices(GridData *gdata)
573: {
574: int n_vert = gdata->n_vert,ierr,*localvert;
575: int rank,size,mlocal_ele = gdata->mlocal_ele,*ele = gdata->ele,i,j,nlocal = 0,nmax;
576: PetscBT mask;
577: MPI_Status status;
580: MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
581: MPI_Comm_size(PETSC_COMM_WORLD,&size);
583: /*
584: Allocated space to store bit-array indicting vertices marked
585: */
586: PetscBTCreate(n_vert,mask);
588: /*
589: All processors except last can have a maximum of n_vert/size vertices assigned
590: (because last processor needs to handle any leftovers)
591: */
592: nmax = n_vert/size;
593: if (rank == size-1) {
594: nmax = n_vert;
595: }
597: /*
598: Receive list of marked vertices from left
599: */
600: if (rank) {
601: MPI_Recv(mask,PetscBTLength(n_vert),MPI_CHAR,rank-1,0,PETSC_COMM_WORLD,&status);
602: }
604: if (rank == size-1) {
605: /* last processor gets all the rest */
606: for (i=0; i<n_vert; i++) {
607: if (!PetscBTLookup(mask,i)) {
608: nlocal++;
609: }
610: }
611: nmax = nlocal;
612: }
614: /*
615: Now we know how many are local, allocated enough space for them and mark them
616: */
617: PetscMalloc((nmax+1)*sizeof(int),&localvert);
619: /* generate local list and fill in mask */
620: nlocal = 0;
621: if (rank < size-1) {
622: /* count my vertices */
623: for (i=0; i<mlocal_ele; i++) {
624: for (j=0; j<3; j++) {
625: if (!PetscBTLookupSet(mask,ele[3*i+j])) {
626: localvert[nlocal++] = ele[3*i+j];
627: if (nlocal >= nmax) goto foundenough2;
628: }
629: }
630: }
631: foundenough2:;
632: } else {
633: /* last processor gets all the rest */
634: for (i=0; i<n_vert; i++) {
635: if (!PetscBTLookup(mask,i)) {
636: localvert[nlocal++] = i;
637: }
638: }
639: }
640: /*
641: Send bit mask on to next processor
642: */
643: if (rank < size-1) {
644: MPI_Send(mask,PetscBTLength(n_vert),MPI_CHAR,rank+1,0,PETSC_COMM_WORLD);
645: }
646: PetscBTDestroy(mask);
648: gdata->localvert = localvert;
649: gdata->nlocal = nlocal;
651: /* print lists of owned vertices */
652: PetscSynchronizedPrintf(PETSC_COMM_WORLD,"[%d] Number vertices assigned %dn",rank,nlocal);
653: PetscSynchronizedFlush(PETSC_COMM_WORLD);
654: PetscIntView(nlocal,localvert,PETSC_VIEWER_STDOUT_WORLD);
656: return(0);
657: }
659: /*
660: Given the partitioning of the vertices; renumbers the element vertex lists for the
661: new vertex numbering and moves the vertex coordinate values to the correct processor
662: */
663: int DataMoveVertices(GridData *gdata)
664: {
665: AO ao;
666: int ierr,rank,i;
667: Vec vert,overt;
668: VecScatter vecscat;
669: IS isscat;
670: Scalar *avert;
674: MPI_Comm_rank(PETSC_COMM_WORLD,&rank);
676: /* ---------------------------------------------------------------------
677: Create a global reodering of the vertex numbers
678: */
679: AOCreateBasic(PETSC_COMM_WORLD,gdata->nlocal,gdata->localvert,PETSC_NULL,&ao);
681: /*
682: Change the element vertex information to the new vertex numbering
683: */
684: AOApplicationToPetsc(ao,3*gdata->mlocal_ele,gdata->ele);
685: PetscPrintf(PETSC_COMM_WORLD,"New vertex numbering in new element orderingn");
686: PetscSynchronizedPrintf(PETSC_COMM_WORLD,"Processor %dn",rank);
687: for (i=0; i<gdata->mlocal_ele; i++) {
688: PetscSynchronizedPrintf(PETSC_COMM_WORLD,"%d %d %d %dn",i,gdata->ele[3*i],gdata->ele[3*i+1],
689: gdata->ele[3*i+2]);
690: }
691: PetscSynchronizedFlush(PETSC_COMM_WORLD);
693: /*
694: Destroy the AO that is no longer needed
695: */
696: AODestroy(ao);
698: /* --------------------------------------------------------------------
699: Finally ship the vertex coordinate information to its owning process
700: note, we do this in a way very similar to what was done for the element info
701: */
702: /* create a vector to contain the newly ordered vertex information */
703: VecCreateSeq(PETSC_COMM_SELF,2*gdata->nlocal,&vert);
705: /* create a vector to contain the old ordered vertex information */
706: VecCreateMPIWithArray(PETSC_COMM_WORLD,2*gdata->mlocal_vert,PETSC_DECIDE,gdata->vert,
707: &overt);
709: /*
710: There are two data items per vertex, the x and y coordinates (i.e. one can think
711: of the vectors of having a block size of 2 and there is one index in localvert[] for each block)
712: */
713: for (i=0; i<gdata->nlocal; i++) gdata->localvert[i] *= 2;
714: ISCreateBlock(PETSC_COMM_WORLD,2,gdata->nlocal,gdata->localvert,&isscat);
715: PetscFree(gdata->localvert);
717: /*
718: Scatter the element vertex information to the correct processor
719: */
720: VecScatterCreate(overt,isscat,vert,PETSC_NULL,&vecscat);
721: ISDestroy(isscat);
722: VecScatterBegin(overt,vert,INSERT_VALUES,SCATTER_FORWARD,vecscat);
723: VecScatterEnd(overt,vert,INSERT_VALUES,SCATTER_FORWARD,vecscat);
724: VecScatterDestroy(vecscat);
726: VecDestroy(overt);
727: PetscFree(gdata->vert);
728:
729: /*
730: Put resulting vertex information into gdata->vert array
731: */
732: PetscMalloc(2*gdata->nlocal*sizeof(double),&gdata->vert);
733: VecGetArray(vert,&avert);
734: PetscMemcpy(gdata->vert,avert,2*gdata->nlocal*sizeof(double));
735: VecRestoreArray(vert,&avert);
736: gdata->mlocal_vert = gdata->nlocal;
737: VecDestroy(vert);
739: PetscPrintf(PETSC_COMM_WORLD,"Vertex coordinates in new numberingn");
740: for (i=0; i<2*gdata->mlocal_vert; i++) {
741: PetscSynchronizedPrintf(PETSC_COMM_WORLD,"%gn",gdata->vert[i]);
742: }
743: PetscSynchronizedFlush(PETSC_COMM_WORLD);
745: return(0);
746: }
749: int DataDestroy(GridData *gdata)
750: {
754: PetscFree(gdata->ele);
755: PetscFree(gdata->vert);
756: return(0);
757: }