xref: /petsc/src/mat/impls/aij/mpi/mpiaij.c (revision fa9ec3f1eecbb61c035ea6bc76a75ea235ea3ac3)
1 #ifndef lint
2 static char vcid[] = "$Id: mpiaij.c,v 1.20 1995/03/27 22:58:06 bsmith Exp curfman $";
3 #endif
4 
5 #include "mpiaij.h"
6 #include "vec/vecimpl.h"
7 #include "inline/spops.h"
8 
9 #define CHUNCKSIZE   100
10 /*
11    This is a simple minded stash. Do a linear search to determine if
12  in stash, if not add to end.
13 */
14 static int StashValues(Stash *stash,int row,int n, int *idxn,
15                        Scalar *values,InsertMode addv)
16 {
17   int    i,j,N = stash->n,found,*n_idx, *n_idy;
18   Scalar val,*n_array;
19 
20   for ( i=0; i<n; i++ ) {
21     found = 0;
22     val = *values++;
23     for ( j=0; j<N; j++ ) {
24       if ( stash->idx[j] == row && stash->idy[j] == idxn[i]) {
25         /* found a match */
26         if (addv == AddValues) stash->array[j] += val;
27         else stash->array[j] = val;
28         found = 1;
29         break;
30       }
31     }
32     if (!found) { /* not found so add to end */
33       if ( stash->n == stash->nmax ) {
34         /* allocate a larger stash */
35         n_array = (Scalar *) MALLOC( (stash->nmax + CHUNCKSIZE)*(
36                                      2*sizeof(int) + sizeof(Scalar)));
37         CHKPTR(n_array);
38         n_idx = (int *) (n_array + stash->nmax + CHUNCKSIZE);
39         n_idy = (int *) (n_idx + stash->nmax + CHUNCKSIZE);
40         MEMCPY(n_array,stash->array,stash->nmax*sizeof(Scalar));
41         MEMCPY(n_idx,stash->idx,stash->nmax*sizeof(int));
42         MEMCPY(n_idy,stash->idy,stash->nmax*sizeof(int));
43         if (stash->array) FREE(stash->array);
44         stash->array = n_array; stash->idx = n_idx; stash->idy = n_idy;
45         stash->nmax += CHUNCKSIZE;
46       }
47       stash->array[stash->n]   = val;
48       stash->idx[stash->n]     = row;
49       stash->idy[stash->n++]   = idxn[i];
50     }
51   }
52   return 0;
53 }
54 
55 /* local utility routine that creates a mapping from the global column
56 number to the local number in the off-diagonal part of the local
57 storage of the matrix.  This is done in a non scable way since the
58 length of colmap equals the global matrix length.
59 */
60 static int CreateColmap(Mat mat)
61 {
62   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data;
63   Mat_AIJ    *B = (Mat_AIJ*) aij->B->data;
64   int        n = B->n,i;
65   aij->colmap = (int *) MALLOC( aij->N*sizeof(int) ); CHKPTR(aij->colmap);
66   MEMSET(aij->colmap,0,aij->N*sizeof(int));
67   for ( i=0; i<n; i++ ) aij->colmap[aij->garray[i]] = i+1;
68   return 0;
69 }
70 
71 static int MatInsertValues_MPIAIJ(Mat mat,int m,int *idxm,int n,
72                             int *idxn,Scalar *v,InsertMode addv)
73 {
74   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data;
75   int        ierr,i,j, rstart = aij->rstart, rend = aij->rend;
76   int        cstart = aij->cstart, cend = aij->cend,row,col;
77 
78   if (aij->insertmode != NotSetValues && aij->insertmode != addv) {
79     SETERR(1,"You cannot mix inserts and adds");
80   }
81   aij->insertmode = addv;
82   for ( i=0; i<m; i++ ) {
83     if (idxm[i] < 0) SETERR(1,"Negative row index");
84     if (idxm[i] >= aij->M) SETERR(1,"Row index too large");
85     if (idxm[i] >= rstart && idxm[i] < rend) {
86       row = idxm[i] - rstart;
87       for ( j=0; j<n; j++ ) {
88         if (idxn[j] < 0) SETERR(1,"Negative column index");
89         if (idxn[j] >= aij->N) SETERR(1,"Column index too large");
90         if (idxn[j] >= cstart && idxn[j] < cend){
91           col = idxn[j] - cstart;
92           ierr = MatSetValues(aij->A,1,&row,1,&col,v+i*n+j,addv);CHKERR(ierr);
93         }
94         else {
95           if (aij->assembled) {
96             if (!aij->colmap) {ierr = CreateColmap(mat); CHKERR(ierr);}
97             col = aij->colmap[idxn[j]] - 1;
98             if (col < 0) {
99               SETERR(1,"Cannot insert new off diagonal block nonzero in\
100                      already\
101                      assembled matrix. Contact petsc-maint@mcs.anl.gov\
102                      if your need this feature");
103             }
104           }
105           else col = idxn[j];
106           ierr = MatSetValues(aij->B,1,&row,1,&col,v+i*n+j,addv);CHKERR(ierr);
107         }
108       }
109     }
110     else {
111       ierr = StashValues(&aij->stash,idxm[i],n,idxn,v+i*n,addv);CHKERR(ierr);
112     }
113   }
114   return 0;
115 }
116 
117 /*
118     the assembly code is alot like the code for vectors, we should
119     sometime derive a single assembly code that can be used for
120     either case.
121 */
122 
123 static int MatBeginAssemble_MPIAIJ(Mat mat)
124 {
125   Mat_MPIAIJ  *aij = (Mat_MPIAIJ *) mat->data;
126   MPI_Comm    comm = mat->comm;
127   int         numtids = aij->numtids, *owners = aij->rowners;
128   int         mytid = aij->mytid;
129   MPI_Request *send_waits,*recv_waits;
130   int         *nprocs,i,j,idx,*procs,nsends,nreceives,nmax,*work;
131   int         tag = 50, *owner,*starts,count;
132   InsertMode  addv;
133   Scalar      *rvalues,*svalues;
134 
135   /* make sure all processors are either in INSERTMODE or ADDMODE */
136   MPI_Allreduce((void *) &aij->insertmode,(void *) &addv,1,MPI_INT,
137                 MPI_BOR,comm);
138   if (addv == (AddValues|InsertValues)) {
139     SETERR(1,"Some processors have inserted while others have added");
140   }
141   aij->insertmode = addv; /* in case this processor had no cache */
142 
143   /*  first count number of contributors to each processor */
144   nprocs = (int *) MALLOC( 2*numtids*sizeof(int) ); CHKPTR(nprocs);
145   MEMSET(nprocs,0,2*numtids*sizeof(int)); procs = nprocs + numtids;
146   owner = (int *) MALLOC( (aij->stash.n+1)*sizeof(int) ); CHKPTR(owner);
147   for ( i=0; i<aij->stash.n; i++ ) {
148     idx = aij->stash.idx[i];
149     for ( j=0; j<numtids; j++ ) {
150       if (idx >= owners[j] && idx < owners[j+1]) {
151         nprocs[j]++; procs[j] = 1; owner[i] = j; break;
152       }
153     }
154   }
155   nsends = 0;  for ( i=0; i<numtids; i++ ) { nsends += procs[i];}
156 
157   /* inform other processors of number of messages and max length*/
158   work = (int *) MALLOC( numtids*sizeof(int) ); CHKPTR(work);
159   MPI_Allreduce((void *) procs,(void *) work,numtids,MPI_INT,MPI_SUM,comm);
160   nreceives = work[mytid];
161   MPI_Allreduce((void *) nprocs,(void *) work,numtids,MPI_INT,MPI_MAX,comm);
162   nmax = work[mytid];
163   FREE(work);
164 
165   /* post receives:
166        1) each message will consist of ordered pairs
167      (global index,value) we store the global index as a double
168      to simplify the message passing.
169        2) since we don't know how long each individual message is we
170      allocate the largest needed buffer for each receive. Potentially
171      this is a lot of wasted space.
172 
173 
174        This could be done better.
175   */
176   rvalues = (Scalar *) MALLOC(3*(nreceives+1)*(nmax+1)*sizeof(Scalar));
177   CHKPTR(rvalues);
178   recv_waits = (MPI_Request *) MALLOC((nreceives+1)*sizeof(MPI_Request));
179   CHKPTR(recv_waits);
180   for ( i=0; i<nreceives; i++ ) {
181     MPI_Irecv((void *)(rvalues+3*nmax*i),3*nmax,MPI_SCALAR,MPI_ANY_SOURCE,tag,
182               comm,recv_waits+i);
183   }
184 
185   /* do sends:
186       1) starts[i] gives the starting index in svalues for stuff going to
187          the ith processor
188   */
189   svalues = (Scalar *) MALLOC( 3*(aij->stash.n+1)*sizeof(Scalar) );
190   CHKPTR(svalues);
191   send_waits = (MPI_Request *) MALLOC( (nsends+1)*sizeof(MPI_Request));
192   CHKPTR(send_waits);
193   starts = (int *) MALLOC( numtids*sizeof(int) ); CHKPTR(starts);
194   starts[0] = 0;
195   for ( i=1; i<numtids; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
196   for ( i=0; i<aij->stash.n; i++ ) {
197     svalues[3*starts[owner[i]]]       = (Scalar)  aij->stash.idx[i];
198     svalues[3*starts[owner[i]]+1]     = (Scalar)  aij->stash.idy[i];
199     svalues[3*(starts[owner[i]]++)+2] =  aij->stash.array[i];
200   }
201   FREE(owner);
202   starts[0] = 0;
203   for ( i=1; i<numtids; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
204   count = 0;
205   for ( i=0; i<numtids; i++ ) {
206     if (procs[i]) {
207       MPI_Isend((void*)(svalues+3*starts[i]),3*nprocs[i],MPI_SCALAR,i,tag,
208                 comm,send_waits+count++);
209     }
210   }
211   FREE(starts); FREE(nprocs);
212 
213   /* Free cache space */
214   aij->stash.nmax = aij->stash.n = 0;
215   if (aij->stash.array){ FREE(aij->stash.array); aij->stash.array = 0;}
216 
217   aij->svalues    = svalues;       aij->rvalues = rvalues;
218   aij->nsends     = nsends;         aij->nrecvs = nreceives;
219   aij->send_waits = send_waits; aij->recv_waits = recv_waits;
220   aij->rmax       = nmax;
221 
222   return 0;
223 }
224 extern int MatSetUpMultiply_MPIAIJ(Mat);
225 
226 static int MatEndAssemble_MPIAIJ(Mat mat)
227 {
228   int        ierr;
229   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data;
230 
231   MPI_Status  *send_status,recv_status;
232   int         imdex,nrecvs = aij->nrecvs, count = nrecvs, i, n;
233   int         row,col;
234   Scalar      *values,val;
235   InsertMode  addv = aij->insertmode;
236 
237   /*  wait on receives */
238   while (count) {
239     MPI_Waitany(nrecvs,aij->recv_waits,&imdex,&recv_status);
240     /* unpack receives into our local space */
241     values = aij->rvalues + 3*imdex*aij->rmax;
242     MPI_Get_count(&recv_status,MPI_SCALAR,&n);
243     n = n/3;
244     for ( i=0; i<n; i++ ) {
245       row = (int) PETSCREAL(values[3*i]) - aij->rstart;
246       col = (int) PETSCREAL(values[3*i+1]);
247       val = values[3*i+2];
248       if (col >= aij->cstart && col < aij->cend) {
249           col -= aij->cstart;
250         MatSetValues(aij->A,1,&row,1,&col,&val,addv);
251       }
252       else {
253         if (aij->assembled) {
254           if (!aij->colmap) {ierr = CreateColmap(mat); CHKERR(ierr);}
255           col = aij->colmap[col] - 1;
256           if (col < 0) {
257             SETERR(1,"Cannot insert new off diagonal block nonzero in\
258                      already\
259                      assembled matrix. Contact petsc-maint@mcs.anl.gov\
260                      if your need this feature");
261           }
262         }
263         MatSetValues(aij->B,1,&row,1,&col,&val,addv);
264       }
265     }
266     count--;
267   }
268   FREE(aij->recv_waits); FREE(aij->rvalues);
269 
270   /* wait on sends */
271   if (aij->nsends) {
272     send_status = (MPI_Status *) MALLOC( aij->nsends*sizeof(MPI_Status) );
273     CHKPTR(send_status);
274     MPI_Waitall(aij->nsends,aij->send_waits,send_status);
275     FREE(send_status);
276   }
277   FREE(aij->send_waits); FREE(aij->svalues);
278 
279   aij->insertmode = NotSetValues;
280   ierr = MatBeginAssembly(aij->A); CHKERR(ierr);
281   ierr = MatEndAssembly(aij->A); CHKERR(ierr);
282 
283   if (!aij->assembled) {
284     ierr = MatSetUpMultiply_MPIAIJ(mat); CHKERR(ierr);
285   }
286   ierr = MatBeginAssembly(aij->B); CHKERR(ierr);
287   ierr = MatEndAssembly(aij->B); CHKERR(ierr);
288 
289   aij->assembled = 1;
290   return 0;
291 }
292 
293 static int MatZero_MPIAIJ(Mat A)
294 {
295   Mat_MPIAIJ *l = (Mat_MPIAIJ *) A->data;
296 
297   MatZeroEntries(l->A); MatZeroEntries(l->B);
298   return 0;
299 }
300 
301 /* again this uses the same basic stratagy as in the assembly and
302    scatter create routines, we should try to do it systemamatically
303    if we can figure out the proper level of generality. */
304 
305 /* the code does not do the diagonal entries correctly unless the
306    matrix is square and the column and row owerships are identical.
307    This is a BUG. The only way to fix it seems to be to access
308    aij->A and aij->B directly and not through the MatZeroRows()
309    routine.
310 */
311 static int MatZeroRows_MPIAIJ(Mat A,IS is,Scalar *diag)
312 {
313   Mat_MPIAIJ     *l = (Mat_MPIAIJ *) A->data;
314   int            i,ierr,N, *rows,*owners = l->rowners,numtids = l->numtids;
315   int            *procs,*nprocs,j,found,idx,nsends,*work;
316   int            nmax,*svalues,*starts,*owner,nrecvs,mytid = l->mytid;
317   int            *rvalues,tag = 67,count,base,slen,n,*source;
318   int            *lens,imdex,*lrows,*values;
319   MPI_Comm       comm = A->comm;
320   MPI_Request    *send_waits,*recv_waits;
321   MPI_Status     recv_status,*send_status;
322   IS             istmp;
323 
324   if (!l->assembled) SETERR(1,"MatZeroRows_MPIAIJ: must assemble matrix first");
325   ierr = ISGetLocalSize(is,&N); CHKERR(ierr);
326   ierr = ISGetIndices(is,&rows); CHKERR(ierr);
327 
328   /*  first count number of contributors to each processor */
329   nprocs = (int *) MALLOC( 2*numtids*sizeof(int) ); CHKPTR(nprocs);
330   MEMSET(nprocs,0,2*numtids*sizeof(int)); procs = nprocs + numtids;
331   owner = (int *) MALLOC((N+1)*sizeof(int)); CHKPTR(owner); /* see note*/
332   for ( i=0; i<N; i++ ) {
333     idx = rows[i];
334     found = 0;
335     for ( j=0; j<numtids; j++ ) {
336       if (idx >= owners[j] && idx < owners[j+1]) {
337         nprocs[j]++; procs[j] = 1; owner[i] = j; found = 1; break;
338       }
339     }
340     if (!found) SETERR(1,"Imdex out of range");
341   }
342   nsends = 0;  for ( i=0; i<numtids; i++ ) { nsends += procs[i];}
343 
344   /* inform other processors of number of messages and max length*/
345   work = (int *) MALLOC( numtids*sizeof(int) ); CHKPTR(work);
346   MPI_Allreduce((void *) procs,(void *) work,numtids,MPI_INT,MPI_SUM,comm);
347   nrecvs = work[mytid];
348   MPI_Allreduce((void *) nprocs,(void *) work,numtids,MPI_INT,MPI_MAX,comm);
349   nmax = work[mytid];
350   FREE(work);
351 
352   /* post receives:   */
353   rvalues = (int *) MALLOC((nrecvs+1)*(nmax+1)*sizeof(int)); /*see note */
354   CHKPTR(rvalues);
355   recv_waits = (MPI_Request *) MALLOC((nrecvs+1)*sizeof(MPI_Request));
356   CHKPTR(recv_waits);
357   for ( i=0; i<nrecvs; i++ ) {
358     MPI_Irecv((void *)(rvalues+nmax*i),nmax,MPI_INT,MPI_ANY_SOURCE,tag,
359               comm,recv_waits+i);
360   }
361 
362   /* do sends:
363       1) starts[i] gives the starting index in svalues for stuff going to
364          the ith processor
365   */
366   svalues = (int *) MALLOC( (N+1)*sizeof(int) ); CHKPTR(svalues);
367   send_waits = (MPI_Request *) MALLOC( (nsends+1)*sizeof(MPI_Request));
368   CHKPTR(send_waits);
369   starts = (int *) MALLOC( (numtids+1)*sizeof(int) ); CHKPTR(starts);
370   starts[0] = 0;
371   for ( i=1; i<numtids; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
372   for ( i=0; i<N; i++ ) {
373     svalues[starts[owner[i]]++] = rows[i];
374   }
375   ISRestoreIndices(is,&rows);
376 
377   starts[0] = 0;
378   for ( i=1; i<numtids+1; i++ ) { starts[i] = starts[i-1] + nprocs[i-1];}
379   count = 0;
380   for ( i=0; i<numtids; i++ ) {
381     if (procs[i]) {
382       MPI_Isend((void*)(svalues+starts[i]),nprocs[i],MPI_INT,i,tag,
383                 comm,send_waits+count++);
384     }
385   }
386   FREE(starts);
387 
388   base = owners[mytid];
389 
390   /*  wait on receives */
391   lens = (int *) MALLOC( 2*(nrecvs+1)*sizeof(int) ); CHKPTR(lens);
392   source = lens + nrecvs;
393   count = nrecvs; slen = 0;
394   while (count) {
395     MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);
396     /* unpack receives into our local space */
397     MPI_Get_count(&recv_status,MPI_INT,&n);
398     source[imdex]  = recv_status.MPI_SOURCE;
399     lens[imdex]  = n;
400     slen += n;
401     count--;
402   }
403   FREE(recv_waits);
404 
405   /* move the data into the send scatter */
406   lrows = (int *) MALLOC( slen*sizeof(int) ); CHKPTR(lrows);
407   count = 0;
408   for ( i=0; i<nrecvs; i++ ) {
409     values = rvalues + i*nmax;
410     for ( j=0; j<lens[i]; j++ ) {
411       lrows[count++] = values[j] - base;
412     }
413   }
414   FREE(rvalues); FREE(lens);
415   FREE(owner); FREE(nprocs);
416 
417   /* actually zap the local rows */
418   ierr = ISCreateSequential(slen,lrows,&istmp); CHKERR(ierr);  FREE(lrows);
419   ierr = MatZeroRows(l->A,istmp,diag); CHKERR(ierr);
420   ierr = MatZeroRows(l->B,istmp,0); CHKERR(ierr);
421   ierr = ISDestroy(istmp); CHKERR(ierr);
422 
423   /* wait on sends */
424   if (nsends) {
425     send_status = (MPI_Status *) MALLOC( nsends*sizeof(MPI_Status) );
426     CHKPTR(send_status);
427     MPI_Waitall(nsends,send_waits,send_status);
428     FREE(send_status);
429   }
430   FREE(send_waits); FREE(svalues);
431 
432 
433   return 0;
434 }
435 
436 static int MatMult_MPIAIJ(Mat aijin,Vec xx,Vec yy)
437 {
438   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data;
439   int        ierr;
440   if (!aij->assembled) SETERR(1,"MatMult_MPIAIJ: must assemble matrix first");
441   ierr = VecScatterBegin(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx);
442   CHKERR(ierr);
443   ierr = MatMult(aij->A,xx,yy); CHKERR(ierr);
444   ierr = VecScatterEnd(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx);
445   CHKERR(ierr);
446   ierr = MatMultAdd(aij->B,aij->lvec,yy,yy); CHKERR(ierr);
447   return 0;
448 }
449 
450 static int MatMultAdd_MPIAIJ(Mat aijin,Vec xx,Vec yy,Vec zz)
451 {
452   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data;
453   int        ierr;
454   if (!aij->assembled) SETERR(1,"MatMult_MPIAIJ: must assemble matrix first");
455   ierr = VecScatterBegin(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx);
456   CHKERR(ierr);
457   ierr = MatMultAdd(aij->A,xx,yy,zz); CHKERR(ierr);
458   ierr = VecScatterEnd(xx,0,aij->lvec,0,InsertValues,ScatterAll,aij->Mvctx);
459   CHKERR(ierr);
460   ierr = MatMultAdd(aij->B,aij->lvec,zz,zz); CHKERR(ierr);
461   return 0;
462 }
463 
464 static int MatMultTrans_MPIAIJ(Mat aijin,Vec xx,Vec yy)
465 {
466   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data;
467   int        ierr;
468 
469   if (!aij->assembled)
470     SETERR(1,"MatMulTrans_MPIAIJ: must assemble matrix first");
471   /* do nondiagonal part */
472   ierr = MatMultTrans(aij->B,xx,aij->lvec); CHKERR(ierr);
473   /* send it on its way */
474   ierr = VecScatterBegin(aij->lvec,0,yy,0,AddValues,
475                          ScatterAll|ScatterReverse,aij->Mvctx); CHKERR(ierr);
476   /* do local part */
477   ierr = MatMultTrans(aij->A,xx,yy); CHKERR(ierr);
478   /* receive remote parts: note this assumes the values are not actually */
479   /* inserted in yy until the next line, which is true for my implementation*/
480   /* but is not perhaps always true. */
481   ierr = VecScatterEnd(aij->lvec,0,yy,0,AddValues,ScatterAll|ScatterReverse,
482                          aij->Mvctx); CHKERR(ierr);
483   return 0;
484 }
485 
486 static int MatMultTransAdd_MPIAIJ(Mat aijin,Vec xx,Vec yy,Vec zz)
487 {
488   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data;
489   int        ierr;
490 
491   if (!aij->assembled)
492     SETERR(1,"MatMulTransAdd_MPIAIJ: must assemble matrix first");
493   /* do nondiagonal part */
494   ierr = MatMultTrans(aij->B,xx,aij->lvec); CHKERR(ierr);
495   /* send it on its way */
496   ierr = VecScatterBegin(aij->lvec,0,zz,0,AddValues,
497                          ScatterAll|ScatterReverse,aij->Mvctx); CHKERR(ierr);
498   /* do local part */
499   ierr = MatMultTransAdd(aij->A,xx,yy,zz); CHKERR(ierr);
500   /* receive remote parts: note this assumes the values are not actually */
501   /* inserted in yy until the next line, which is true for my implementation*/
502   /* but is not perhaps always true. */
503   ierr = VecScatterEnd(aij->lvec,0,zz,0,AddValues,ScatterAll|ScatterReverse,
504                          aij->Mvctx); CHKERR(ierr);
505   return 0;
506 }
507 
508 /*
509   This only works correctly for square matrices where the subblock A->A is the
510    diagonal block
511 */
512 static int MatGetDiag_MPIAIJ(Mat Ain,Vec v)
513 {
514   Mat_MPIAIJ *A = (Mat_MPIAIJ *) Ain->data;
515   if (!A->assembled) SETERR(1,"MatGetDiag_MPIAIJ: must assemble matrix first");
516   return MatGetDiagonal(A->A,v);
517 }
518 
519 static int MatDestroy_MPIAIJ(PetscObject obj)
520 {
521   Mat        mat = (Mat) obj;
522   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data;
523   int        ierr;
524 #if defined(PETSC_LOG)
525   PLogObjectState(obj,"Rows %d Cols %d",aij->M,aij->N);
526 #endif
527   FREE(aij->rowners);
528   ierr = MatDestroy(aij->A); CHKERR(ierr);
529   ierr = MatDestroy(aij->B); CHKERR(ierr);
530   if (aij->colmap) FREE(aij->colmap);
531   if (aij->garray) FREE(aij->garray);
532   if (aij->lvec) VecDestroy(aij->lvec);
533   if (aij->Mvctx) VecScatterCtxDestroy(aij->Mvctx);
534   FREE(aij);
535   PLogObjectDestroy(mat);
536   PETSCHEADERDESTROY(mat);
537   return 0;
538 }
539 
540 static int MatView_MPIAIJ(PetscObject obj,Viewer viewer)
541 {
542   Mat        mat = (Mat) obj;
543   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) mat->data;
544   int        ierr;
545   PetscObject vobj = (PetscObject) viewer;
546 
547   if (!viewer) { /* so that viewers may be used from debuggers */
548     viewer = STDOUT_VIEWER; vobj = (PetscObject) viewer;
549   }
550   if (!aij->assembled) SETERR(1,"MatView_MPIAIJ: must assemble matrix first");
551   if (vobj->cookie == VIEWER_COOKIE) {
552     FILE *fd = ViewerFileGetPointer(viewer);
553     if (vobj->type == FILE_VIEWER) {
554       MPE_Seq_begin(mat->comm,1);
555       fprintf(fd,"[%d] rows %d starts %d ends %d cols %d starts %d ends %d\n",
556              aij->mytid,aij->m,aij->rstart,aij->rend,aij->n,aij->cstart,
557              aij->cend);
558       ierr = MatView(aij->A,viewer); CHKERR(ierr);
559       ierr = MatView(aij->B,viewer); CHKERR(ierr);
560       fflush(fd);
561       MPE_Seq_end(mat->comm,1);
562     }
563     else if (vobj->type == FILES_VIEWER) {
564       int numtids = aij->numtids, mytid = aij->mytid;
565       if (numtids == 1) {
566         ierr = MatView(aij->A,viewer); CHKERR(ierr);
567       }
568       else {
569         /* assemble the entire matrix onto first processor. */
570         Mat     A;
571         Mat_AIJ *Aaij;
572         int     M = aij->M, N = aij->N,m,*ai,*aj,row,*cols,i,*ct;
573         Scalar  *a;
574         if (!mytid) {
575           ierr = MatCreateMPIAIJ(mat->comm,M,N,M,N,0,0,0,0,&A);
576         }
577         else {
578           ierr = MatCreateMPIAIJ(mat->comm,0,0,M,N,0,0,0,0,&A);
579         }
580         CHKERR(ierr);
581 
582         /* copy over the A part */
583         Aaij = (Mat_AIJ*) aij->A->data;
584         m = Aaij->m; ai = Aaij->i; aj = Aaij->j; a = Aaij->a;
585         row = aij->rstart;
586         for ( i=0; i<ai[m]; i++ ) {aj[i] += aij->cstart - 1;}
587         for ( i=0; i<m; i++ ) {
588           ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],aj,a,InsertValues);
589           CHKERR(ierr);
590           row++; a += ai[i+1]-ai[i]; aj += ai[i+1]-ai[i];
591         }
592         aj = Aaij->j;
593         for ( i=0; i<ai[m]; i++ ) {aj[i] -= aij->cstart - 1;}
594 
595         /* copy over the B part */
596         Aaij = (Mat_AIJ*) aij->B->data;
597         m = Aaij->m;  ai = Aaij->i; aj = Aaij->j; a = Aaij->a;
598         row = aij->rstart;
599         ct = cols = (int *) MALLOC( (ai[m]+1)*sizeof(int) ); CHKPTR(cols);
600         for ( i=0; i<ai[m]; i++ ) {cols[i] = aij->garray[aj[i]-1];}
601         for ( i=0; i<m; i++ ) {
602           ierr = MatSetValues(A,1,&row,ai[i+1]-ai[i],cols,a,InsertValues);
603           CHKERR(ierr);
604           row++; a += ai[i+1]-ai[i]; cols += ai[i+1]-ai[i];
605         }
606         FREE(ct);
607 
608         ierr = MatBeginAssembly(A); CHKERR(ierr);
609         ierr = MatEndAssembly(A); CHKERR(ierr);
610         if (!mytid) {
611           ierr = MatView(((Mat_MPIAIJ*)(A->data))->A,viewer); CHKERR(ierr);
612         }
613         ierr = MatDestroy(A); CHKERR(ierr);
614       }
615     }
616   }
617   return 0;
618 }
619 
620 extern int MatMarkDiag_AIJ(Mat_AIJ  *);
621 /*
622     This has to provide several versions.
623 
624      1) per sequential
625      2) a) use only local smoothing updating outer values only once.
626         b) local smoothing updating outer values each inner iteration
627      3) color updating out values betwen colors.
628 */
629 static int MatRelax_MPIAIJ(Mat matin,Vec bb,double omega,int flag,double shift,
630                         int its,Vec xx)
631 {
632   Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data;
633   Mat        AA = mat->A, BB = mat->B;
634   Mat_AIJ    *A = (Mat_AIJ *) AA->data, *B = (Mat_AIJ *)BB->data;
635   Scalar     zero = 0.0,*b,*x,*xs,*ls,d,*v,sum,scale,*t,*ts;
636   int        ierr,*idx, *diag;
637   int        n = mat->n, m = mat->m, i;
638   Vec        tt;
639 
640   if (!mat->assembled) SETERR(1,"MatRelax_MPIAIJ: must assemble matrix first");
641 
642   VecGetArray(xx,&x); VecGetArray(bb,&b); VecGetArray(mat->lvec,&ls);
643   xs = x -1; /* shift by one for index start of 1 */
644   ls--;
645   if (!A->diag) {if ((ierr = MatMarkDiag_AIJ(A))) return ierr;}
646   diag = A->diag;
647   if (flag == SOR_APPLY_UPPER || flag == SOR_APPLY_LOWER) {
648     SETERR(1,"That option not yet support for parallel AIJ matrices");
649   }
650   if (flag & SOR_EISENSTAT) {
651     /* Let  A = L + U + D; where L is lower trianglar,
652     U is upper triangular, E is diagonal; This routine applies
653 
654             (L + E)^{-1} A (U + E)^{-1}
655 
656     to a vector efficiently using Eisenstat's trick. This is for
657     the case of SSOR preconditioner, so E is D/omega where omega
658     is the relaxation factor.
659     */
660     ierr = VecCreate(xx,&tt); CHKERR(ierr);
661     VecGetArray(tt,&t);
662     scale = (2.0/omega) - 1.0;
663     /*  x = (E + U)^{-1} b */
664     VecSet(&zero,mat->lvec);
665     ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp,
666                               mat->Mvctx); CHKERR(ierr);
667     for ( i=m-1; i>-1; i-- ) {
668       n    = A->i[i+1] - diag[i] - 1;
669       idx  = A->j + diag[i];
670       v    = A->a + diag[i];
671       sum  = b[i];
672       SPARSEDENSEMDOT(sum,xs,v,idx,n);
673       d    = shift + A->a[diag[i]-1];
674       n    = B->i[i+1] - B->i[i];
675       idx  = B->j + B->i[i] - 1;
676       v    = B->a + B->i[i] - 1;
677       SPARSEDENSEMDOT(sum,ls,v,idx,n);
678       x[i] = omega*(sum/d);
679     }
680     ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp,
681                             mat->Mvctx); CHKERR(ierr);
682 
683     /*  t = b - (2*E - D)x */
684     v = A->a;
685     for ( i=0; i<m; i++ ) { t[i] = b[i] - scale*(v[*diag++ - 1])*x[i]; }
686 
687     /*  t = (E + L)^{-1}t */
688     ts = t - 1; /* shifted by one for index start of a or mat->j*/
689     diag = A->diag;
690     VecSet(&zero,mat->lvec);
691     ierr = VecPipelineBegin(tt,0,mat->lvec,0,InsertValues,PipelineDown,
692                                                  mat->Mvctx); CHKERR(ierr);
693     for ( i=0; i<m; i++ ) {
694       n    = diag[i] - A->i[i];
695       idx  = A->j + A->i[i] - 1;
696       v    = A->a + A->i[i] - 1;
697       sum  = t[i];
698       SPARSEDENSEMDOT(sum,ts,v,idx,n);
699       d    = shift + A->a[diag[i]-1];
700       n    = B->i[i+1] - B->i[i];
701       idx  = B->j + B->i[i] - 1;
702       v    = B->a + B->i[i] - 1;
703       SPARSEDENSEMDOT(sum,ls,v,idx,n);
704       t[i] = omega*(sum/d);
705     }
706     ierr = VecPipelineEnd(tt,0,mat->lvec,0,InsertValues,PipelineDown,
707                                                     mat->Mvctx); CHKERR(ierr);
708     /*  x = x + t */
709     for ( i=0; i<m; i++ ) { x[i] += t[i]; }
710     VecDestroy(tt);
711     return 0;
712   }
713 
714 
715   if ((flag & SOR_SYMMETRIC_SWEEP) == SOR_SYMMETRIC_SWEEP){
716     if (flag & SOR_ZERO_INITIAL_GUESS) {
717       VecSet(&zero,mat->lvec); VecSet(&zero,xx);
718     }
719     else {
720       ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx);
721       CHKERR(ierr);
722       ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx);
723       CHKERR(ierr);
724     }
725     while (its--) {
726       /* go down through the rows */
727       ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown,
728                               mat->Mvctx); CHKERR(ierr);
729       for ( i=0; i<m; i++ ) {
730         n    = A->i[i+1] - A->i[i];
731         idx  = A->j + A->i[i] - 1;
732         v    = A->a + A->i[i] - 1;
733         sum  = b[i];
734         SPARSEDENSEMDOT(sum,xs,v,idx,n);
735         d    = shift + A->a[diag[i]-1];
736         n    = B->i[i+1] - B->i[i];
737         idx  = B->j + B->i[i] - 1;
738         v    = B->a + B->i[i] - 1;
739         SPARSEDENSEMDOT(sum,ls,v,idx,n);
740         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
741       }
742       ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown,
743                             mat->Mvctx); CHKERR(ierr);
744       /* come up through the rows */
745       ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp,
746                               mat->Mvctx); CHKERR(ierr);
747       for ( i=m-1; i>-1; i-- ) {
748         n    = A->i[i+1] - A->i[i];
749         idx  = A->j + A->i[i] - 1;
750         v    = A->a + A->i[i] - 1;
751         sum  = b[i];
752         SPARSEDENSEMDOT(sum,xs,v,idx,n);
753         d    = shift + A->a[diag[i]-1];
754         n    = B->i[i+1] - B->i[i];
755         idx  = B->j + B->i[i] - 1;
756         v    = B->a + B->i[i] - 1;
757         SPARSEDENSEMDOT(sum,ls,v,idx,n);
758         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
759       }
760       ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp,
761                             mat->Mvctx); CHKERR(ierr);
762     }
763   }
764   else if (flag & SOR_FORWARD_SWEEP){
765     if (flag & SOR_ZERO_INITIAL_GUESS) {
766       VecSet(&zero,mat->lvec);
767       ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown,
768                               mat->Mvctx); CHKERR(ierr);
769       for ( i=0; i<m; i++ ) {
770         n    = diag[i] - A->i[i];
771         idx  = A->j + A->i[i] - 1;
772         v    = A->a + A->i[i] - 1;
773         sum  = b[i];
774         SPARSEDENSEMDOT(sum,xs,v,idx,n);
775         d    = shift + A->a[diag[i]-1];
776         n    = B->i[i+1] - B->i[i];
777         idx  = B->j + B->i[i] - 1;
778         v    = B->a + B->i[i] - 1;
779         SPARSEDENSEMDOT(sum,ls,v,idx,n);
780         x[i] = omega*(sum/d);
781       }
782       ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown,
783                             mat->Mvctx); CHKERR(ierr);
784       its--;
785     }
786     while (its--) {
787       ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx);
788       CHKERR(ierr);
789       ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterUp,mat->Mvctx);
790       CHKERR(ierr);
791       ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineDown,
792                               mat->Mvctx); CHKERR(ierr);
793       for ( i=0; i<m; i++ ) {
794         n    = A->i[i+1] - A->i[i];
795         idx  = A->j + A->i[i] - 1;
796         v    = A->a + A->i[i] - 1;
797         sum  = b[i];
798         SPARSEDENSEMDOT(sum,xs,v,idx,n);
799         d    = shift + A->a[diag[i]-1];
800         n    = B->i[i+1] - B->i[i];
801         idx  = B->j + B->i[i] - 1;
802         v    = B->a + B->i[i] - 1;
803         SPARSEDENSEMDOT(sum,ls,v,idx,n);
804         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
805       }
806       ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineDown,
807                             mat->Mvctx); CHKERR(ierr);
808     }
809   }
810   else if (flag & SOR_BACKWARD_SWEEP){
811     if (flag & SOR_ZERO_INITIAL_GUESS) {
812       VecSet(&zero,mat->lvec);
813       ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp,
814                               mat->Mvctx); CHKERR(ierr);
815       for ( i=m-1; i>-1; i-- ) {
816         n    = A->i[i+1] - diag[i] - 1;
817         idx  = A->j + diag[i];
818         v    = A->a + diag[i];
819         sum  = b[i];
820         SPARSEDENSEMDOT(sum,xs,v,idx,n);
821         d    = shift + A->a[diag[i]-1];
822         n    = B->i[i+1] - B->i[i];
823         idx  = B->j + B->i[i] - 1;
824         v    = B->a + B->i[i] - 1;
825         SPARSEDENSEMDOT(sum,ls,v,idx,n);
826         x[i] = omega*(sum/d);
827       }
828       ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp,
829                             mat->Mvctx); CHKERR(ierr);
830       its--;
831     }
832     while (its--) {
833       ierr = VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterDown,
834                             mat->Mvctx); CHKERR(ierr);
835       ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterDown,
836                             mat->Mvctx); CHKERR(ierr);
837       ierr = VecPipelineBegin(xx,0,mat->lvec,0,InsertValues,PipelineUp,
838                               mat->Mvctx); CHKERR(ierr);
839       for ( i=m-1; i>-1; i-- ) {
840         n    = A->i[i+1] - A->i[i];
841         idx  = A->j + A->i[i] - 1;
842         v    = A->a + A->i[i] - 1;
843         sum  = b[i];
844         SPARSEDENSEMDOT(sum,xs,v,idx,n);
845         d    = shift + A->a[diag[i]-1];
846         n    = B->i[i+1] - B->i[i];
847         idx  = B->j + B->i[i] - 1;
848         v    = B->a + B->i[i] - 1;
849         SPARSEDENSEMDOT(sum,ls,v,idx,n);
850         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
851       }
852       ierr = VecPipelineEnd(xx,0,mat->lvec,0,InsertValues,PipelineUp,
853                             mat->Mvctx); CHKERR(ierr);
854     }
855   }
856   else if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP){
857     if (flag & SOR_ZERO_INITIAL_GUESS) {
858       return MatRelax(mat->A,bb,omega,flag,shift,its,xx);
859     }
860     ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx);
861     CHKERR(ierr);
862     ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx);
863     CHKERR(ierr);
864     while (its--) {
865       /* go down through the rows */
866       for ( i=0; i<m; i++ ) {
867         n    = A->i[i+1] - A->i[i];
868         idx  = A->j + A->i[i] - 1;
869         v    = A->a + A->i[i] - 1;
870         sum  = b[i];
871         SPARSEDENSEMDOT(sum,xs,v,idx,n);
872         d    = shift + A->a[diag[i]-1];
873         n    = B->i[i+1] - B->i[i];
874         idx  = B->j + B->i[i] - 1;
875         v    = B->a + B->i[i] - 1;
876         SPARSEDENSEMDOT(sum,ls,v,idx,n);
877         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
878       }
879       /* come up through the rows */
880       for ( i=m-1; i>-1; i-- ) {
881         n    = A->i[i+1] - A->i[i];
882         idx  = A->j + A->i[i] - 1;
883         v    = A->a + A->i[i] - 1;
884         sum  = b[i];
885         SPARSEDENSEMDOT(sum,xs,v,idx,n);
886         d    = shift + A->a[diag[i]-1];
887         n    = B->i[i+1] - B->i[i];
888         idx  = B->j + B->i[i] - 1;
889         v    = B->a + B->i[i] - 1;
890         SPARSEDENSEMDOT(sum,ls,v,idx,n);
891         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
892       }
893     }
894   }
895   else if (flag & SOR_LOCAL_FORWARD_SWEEP){
896     if (flag & SOR_ZERO_INITIAL_GUESS) {
897       return MatRelax(mat->A,bb,omega,flag,shift,its,xx);
898     }
899     ierr=VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx);
900     CHKERR(ierr);
901     ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,mat->Mvctx);
902     CHKERR(ierr);
903     while (its--) {
904       for ( i=0; i<m; i++ ) {
905         n    = A->i[i+1] - A->i[i];
906         idx  = A->j + A->i[i] - 1;
907         v    = A->a + A->i[i] - 1;
908         sum  = b[i];
909         SPARSEDENSEMDOT(sum,xs,v,idx,n);
910         d    = shift + A->a[diag[i]-1];
911         n    = B->i[i+1] - B->i[i];
912         idx  = B->j + B->i[i] - 1;
913         v    = B->a + B->i[i] - 1;
914         SPARSEDENSEMDOT(sum,ls,v,idx,n);
915         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
916       }
917     }
918   }
919   else if (flag & SOR_LOCAL_BACKWARD_SWEEP){
920     if (flag & SOR_ZERO_INITIAL_GUESS) {
921       return MatRelax(mat->A,bb,omega,flag,shift,its,xx);
922     }
923     ierr = VecScatterBegin(xx,0,mat->lvec,0,InsertValues,ScatterAll,
924                             mat->Mvctx); CHKERR(ierr);
925     ierr = VecScatterEnd(xx,0,mat->lvec,0,InsertValues,ScatterAll,
926                             mat->Mvctx); CHKERR(ierr);
927     while (its--) {
928       for ( i=m-1; i>-1; i-- ) {
929         n    = A->i[i+1] - A->i[i];
930         idx  = A->j + A->i[i] - 1;
931         v    = A->a + A->i[i] - 1;
932         sum  = b[i];
933         SPARSEDENSEMDOT(sum,xs,v,idx,n);
934         d    = shift + A->a[diag[i]-1];
935         n    = B->i[i+1] - B->i[i];
936         idx  = B->j + B->i[i] - 1;
937         v    = B->a + B->i[i] - 1;
938         SPARSEDENSEMDOT(sum,ls,v,idx,n);
939         x[i] = (1. - omega)*x[i] + omega*(sum/d + x[i]);
940       }
941     }
942   }
943   return 0;
944 }
945 static int MatInsOpt_MPIAIJ(Mat aijin,int op)
946 {
947   Mat_MPIAIJ *aij = (Mat_MPIAIJ *) aijin->data;
948 
949   if      (op == NO_NEW_NONZERO_LOCATIONS)  {
950     MatSetOption(aij->A,op);
951     MatSetOption(aij->B,op);
952   }
953   else if (op == YES_NEW_NONZERO_LOCATIONS) {
954     MatSetOption(aij->A,op);
955     MatSetOption(aij->B,op);
956   }
957   else if (op == COLUMN_ORIENTED) SETERR(1,"Column oriented not supported");
958   return 0;
959 }
960 
961 static int MatSize_MPIAIJ(Mat matin,int *m,int *n)
962 {
963   Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data;
964   *m = mat->M; *n = mat->N;
965   return 0;
966 }
967 
968 static int MatLocalSize_MPIAIJ(Mat matin,int *m,int *n)
969 {
970   Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data;
971   *m = mat->m; *n = mat->n;
972   return 0;
973 }
974 
975 static int MatRange_MPIAIJ(Mat matin,int *m,int *n)
976 {
977   Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data;
978   *m = mat->rstart; *n = mat->rend;
979   return 0;
980 }
981 
982 static int MatGetRow_MPIAIJ(Mat matin,int row,int *nz,int **idx,Scalar **v)
983 {
984   Mat_MPIAIJ *mat = (Mat_MPIAIJ *) matin->data;
985   Scalar     *vworkA, *vworkB, **pvA, **pvB;
986   int        i, ierr, *cworkA, *cworkB, **pcA, **pcB, cstart = mat->cstart;
987   int        nztot, nzA, nzB, lrow, rstart = mat->rstart, rend = mat->rend;
988 
989   if (!mat->assembled)
990     SETERR(1,"MatGetRow_MPIAIJ: Must assemble matrix first.");
991   if (row < rstart || row >= rend)
992     SETERR(1,"MatGetRow_MPIAIJ: Currently you can get only local rows.")
993   lrow = row - rstart;
994 
995   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
996   if (!v)   {pvA = 0; pvB = 0;}
997   if (!idx) {pcA = 0; if (!v) pcB = 0;}
998   ierr = MatGetRow(mat->A,lrow,&nzA,pcA,pvA); CHKERR(ierr);
999   ierr = MatGetRow(mat->B,lrow,&nzB,pcB,pvB); CHKERR(ierr);
1000   nztot = nzA + nzB;
1001 
1002   if (v  || idx) {
1003     if (nztot) {
1004       /* Sort by increasing column numbers, assuming A and B already sorted */
1005       int imark, imark2;
1006       for (i=0; i<nzB; i++) cworkB[i] = mat->garray[cworkB[i]];
1007       if (v) {
1008         *v = (Scalar *) MALLOC( (nztot)*sizeof(Scalar) ); CHKPTR(*v);
1009         for ( i=0; i<nzB; i++ ) {
1010           if (cworkB[i] < cstart)   (*v)[i] = vworkB[i];
1011           else break;
1012         }
1013         imark = i;
1014         for ( i=0; i<nzA; i++ )     (*v)[imark+i] = vworkA[i];
1015         imark2 = imark+nzA;
1016         for ( i=imark; i<nzB; i++ ) (*v)[imark2+i] = vworkB[i];
1017       }
1018       if (idx) {
1019         *idx = (int *) MALLOC( (nztot)*sizeof(int) ); CHKPTR(*idx);
1020         for (i=0; i<nzA; i++) cworkA[i] += cstart;
1021         for ( i=0; i<nzB; i++ ) {
1022           if (cworkB[i] < cstart)   (*idx)[i] = cworkB[i];
1023           else break;
1024         }
1025         imark = i;
1026         for ( i=0; i<nzA; i++ )     (*idx)[imark+i] = cworkA[i];
1027         imark2 = imark+nzA;
1028         for ( i=imark; i<nzB; i++ ) (*idx)[imark2+i] = cworkB[i];
1029       }
1030     }
1031     else {*idx = 0; *v=0;}
1032   }
1033   *nz = nztot;
1034   ierr = MatRestoreRow(mat->A,lrow,&nzA,pcA,pvA); CHKERR(ierr);
1035   ierr = MatRestoreRow(mat->B,lrow,&nzB,pcB,pvB); CHKERR(ierr);
1036   return 0;
1037 }
1038 
1039 static int MatRestoreRow_MPIAIJ(Mat mat,int row,int *nz,int **idx,Scalar **v)
1040 {
1041   if (idx) FREE(*idx);
1042   if (v) FREE(*v);
1043   return 0;
1044 }
1045 
1046 static int MatCopy_MPIAIJ(Mat,Mat *);
1047 extern int MatConvert_MPIAIJ(Mat,MATTYPE,Mat *);
1048 
1049 /* -------------------------------------------------------------------*/
1050 static struct _MatOps MatOps = {MatInsertValues_MPIAIJ,
1051        MatGetRow_MPIAIJ,MatRestoreRow_MPIAIJ,
1052        MatMult_MPIAIJ,MatMultAdd_MPIAIJ,
1053        MatMultTrans_MPIAIJ,MatMultTransAdd_MPIAIJ,
1054        0,0,0,0,
1055        0,0,
1056        MatRelax_MPIAIJ,
1057        0,
1058        0,0,0,
1059        MatCopy_MPIAIJ,
1060        MatGetDiag_MPIAIJ,0,0,
1061        MatBeginAssemble_MPIAIJ,MatEndAssemble_MPIAIJ,
1062        0,
1063        MatInsOpt_MPIAIJ,MatZero_MPIAIJ,MatZeroRows_MPIAIJ,0,
1064        0,0,0,0,
1065        MatSize_MPIAIJ,MatLocalSize_MPIAIJ,MatRange_MPIAIJ,
1066        0,0,
1067        0,MatConvert_MPIAIJ };
1068 
1069 /*@
1070 
1071       MatCreateMPIAIJ - Creates a sparse parallel matrix
1072                                  in AIJ format.
1073 
1074   Input Parameters:
1075 .   comm - MPI communicator
1076 .   m,n - number of local rows and columns (or -1 to have calculated)
1077 .   M,N - global rows and columns (or -1 to have calculated)
1078 .   d_nz - total number nonzeros in diagonal portion of matrix
1079 .   d_nzz - number of nonzeros per row in diagonal portion of matrix or null
1080 .           You must leave room for the diagonal entry even if it is zero.
1081 .   o_nz - total number nonzeros in off-diagonal portion of matrix
1082 .   o_nzz - number of nonzeros per row in off-diagonal portion of matrix
1083 .           or null. You must have at least one nonzero per row.
1084 
1085   Output parameters:
1086 .  newmat - the matrix
1087 
1088   Keywords: matrix, aij, compressed row, sparse, parallel
1089 @*/
1090 int MatCreateMPIAIJ(MPI_Comm comm,int m,int n,int M,int N,
1091                  int d_nz,int *d_nnz, int o_nz,int *o_nnz,Mat *newmat)
1092 {
1093   Mat          mat;
1094   Mat_MPIAIJ   *aij;
1095   int          ierr, i,sum[2],work[2];
1096   *newmat         = 0;
1097   PETSCHEADERCREATE(mat,_Mat,MAT_COOKIE,MATMPIAIJ,comm);
1098   PLogObjectCreate(mat);
1099   mat->data       = (void *) (aij = NEW(Mat_MPIAIJ)); CHKPTR(aij);
1100   mat->ops        = &MatOps;
1101   mat->destroy    = MatDestroy_MPIAIJ;
1102   mat->view       = MatView_MPIAIJ;
1103   mat->factor     = 0;
1104   mat->row        = 0;
1105   mat->col        = 0;
1106 
1107   mat->comm       = comm;
1108   aij->insertmode = NotSetValues;
1109   MPI_Comm_rank(comm,&aij->mytid);
1110   MPI_Comm_size(comm,&aij->numtids);
1111 
1112   if (M == -1 || N == -1) {
1113     work[0] = m; work[1] = n;
1114     MPI_Allreduce((void *) work,(void *) sum,2,MPI_INT,MPI_SUM,comm );
1115     if (M == -1) M = sum[0];
1116     if (N == -1) N = sum[1];
1117   }
1118   if (m == -1) {m = M/aij->numtids + ((M % aij->numtids) > aij->mytid);}
1119   if (n == -1) {n = N/aij->numtids + ((N % aij->numtids) > aij->mytid);}
1120   aij->m       = m;
1121   aij->n       = n;
1122   aij->N       = N;
1123   aij->M       = M;
1124 
1125   /* build local table of row and column ownerships */
1126   aij->rowners = (int *) MALLOC(2*(aij->numtids+2)*sizeof(int));
1127   CHKPTR(aij->rowners);
1128   aij->cowners = aij->rowners + aij->numtids + 1;
1129   MPI_Allgather(&m,1,MPI_INT,aij->rowners+1,1,MPI_INT,comm);
1130   aij->rowners[0] = 0;
1131   for ( i=2; i<=aij->numtids; i++ ) {
1132     aij->rowners[i] += aij->rowners[i-1];
1133   }
1134   aij->rstart = aij->rowners[aij->mytid];
1135   aij->rend   = aij->rowners[aij->mytid+1];
1136   MPI_Allgather(&n,1,MPI_INT,aij->cowners+1,1,MPI_INT,comm);
1137   aij->cowners[0] = 0;
1138   for ( i=2; i<=aij->numtids; i++ ) {
1139     aij->cowners[i] += aij->cowners[i-1];
1140   }
1141   aij->cstart = aij->cowners[aij->mytid];
1142   aij->cend   = aij->cowners[aij->mytid+1];
1143 
1144 
1145   ierr = MatCreateSequentialAIJ(m,n,d_nz,d_nnz,&aij->A); CHKERR(ierr);
1146   PLogObjectParent(mat,aij->A);
1147   ierr = MatCreateSequentialAIJ(m,N,o_nz,o_nnz,&aij->B); CHKERR(ierr);
1148   PLogObjectParent(mat,aij->B);
1149 
1150   /* build cache for off array entries formed */
1151   aij->stash.nmax = CHUNCKSIZE; /* completely arbratray number */
1152   aij->stash.n    = 0;
1153   aij->stash.array = (Scalar *) MALLOC( aij->stash.nmax*(2*sizeof(int) +
1154                             sizeof(Scalar))); CHKPTR(aij->stash.array);
1155   aij->stash.idx = (int *) (aij->stash.array + aij->stash.nmax);
1156   aij->stash.idy = (int *) (aij->stash.idx + aij->stash.nmax);
1157   aij->colmap    = 0;
1158   aij->garray    = 0;
1159 
1160   /* stuff used for matrix vector multiply */
1161   aij->lvec      = 0;
1162   aij->Mvctx     = 0;
1163   aij->assembled = 0;
1164 
1165   *newmat = mat;
1166   return 0;
1167 }
1168 
1169 static int MatCopy_MPIAIJ(Mat matin,Mat *newmat)
1170 {
1171   Mat        mat;
1172   Mat_MPIAIJ *aij,*oldmat = (Mat_MPIAIJ *) matin->data;
1173   int        ierr;
1174   *newmat      = 0;
1175 
1176   if (!oldmat->assembled) SETERR(1,"Cannot copy unassembled matrix");
1177   PETSCHEADERCREATE(mat,_Mat,MAT_COOKIE,MATMPIAIJ,matin->comm);
1178   PLogObjectCreate(mat);
1179   mat->data       = (void *) (aij = NEW(Mat_MPIAIJ)); CHKPTR(aij);
1180   mat->ops        = &MatOps;
1181   mat->destroy    = MatDestroy_MPIAIJ;
1182   mat->view       = MatView_MPIAIJ;
1183   mat->factor     = matin->factor;
1184   mat->row        = 0;
1185   mat->col        = 0;
1186 
1187   aij->m          = oldmat->m;
1188   aij->n          = oldmat->n;
1189   aij->M          = oldmat->M;
1190   aij->N          = oldmat->N;
1191 
1192   aij->assembled  = 1;
1193   aij->rstart     = oldmat->rstart;
1194   aij->rend       = oldmat->rend;
1195   aij->cstart     = oldmat->cstart;
1196   aij->cend       = oldmat->cend;
1197   aij->numtids    = oldmat->numtids;
1198   aij->mytid      = oldmat->mytid;
1199   aij->insertmode = NotSetValues;
1200 
1201   aij->rowners    = (int *) MALLOC( (aij->numtids+1)*sizeof(int) );
1202   CHKPTR(aij->rowners);
1203   MEMCPY(aij->rowners,oldmat->rowners,(aij->numtids+1)*sizeof(int));
1204   aij->stash.nmax = 0;
1205   aij->stash.n    = 0;
1206   aij->stash.array= 0;
1207   aij->colmap     = 0;
1208   aij->garray     = 0;
1209   mat->comm       = matin->comm;
1210 
1211   ierr =  VecCreate(oldmat->lvec,&aij->lvec); CHKERR(ierr);
1212   PLogObjectParent(mat,aij->lvec);
1213   ierr =  VecScatterCtxCopy(oldmat->Mvctx,&aij->Mvctx); CHKERR(ierr);
1214   PLogObjectParent(mat,aij->Mvctx);
1215   ierr =  MatCopy(oldmat->A,&aij->A); CHKERR(ierr);
1216   PLogObjectParent(mat,aij->A);
1217   ierr =  MatCopy(oldmat->B,&aij->B); CHKERR(ierr);
1218   PLogObjectParent(mat,aij->B);
1219   *newmat = mat;
1220   return 0;
1221 }
1222