xref: /petsc/src/mat/impls/baij/mpi/mpibaij.c (revision dced61a5cfeeeda68dfa4ee3e53b34d3cfb8da9f)
1 
2 #include <../src/mat/impls/baij/mpi/mpibaij.h>   /*I  "petscmat.h"  I*/
3 
4 #include <petscblaslapack.h>
5 #include <petscsf.h>
6 
7 #undef __FUNCT__
8 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ"
9 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[])
10 {
11   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
12   PetscErrorCode ierr;
13   PetscInt       i,*idxb = 0;
14   PetscScalar    *va,*vb;
15   Vec            vtmp;
16 
17   PetscFunctionBegin;
18   ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr);
19   ierr = VecGetArray(v,&va);CHKERRQ(ierr);
20   if (idx) {
21     for (i=0; i<A->rmap->n; i++) {
22       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
23     }
24   }
25 
26   ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr);
27   if (idx) {ierr = PetscMalloc1(A->rmap->n,&idxb);CHKERRQ(ierr);}
28   ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr);
29   ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr);
30 
31   for (i=0; i<A->rmap->n; i++) {
32     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
33       va[i] = vb[i];
34       if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);
35     }
36   }
37 
38   ierr = VecRestoreArray(v,&va);CHKERRQ(ierr);
39   ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr);
40   ierr = PetscFree(idxb);CHKERRQ(ierr);
41   ierr = VecDestroy(&vtmp);CHKERRQ(ierr);
42   PetscFunctionReturn(0);
43 }
44 
45 #undef __FUNCT__
46 #define __FUNCT__ "MatStoreValues_MPIBAIJ"
47 PetscErrorCode  MatStoreValues_MPIBAIJ(Mat mat)
48 {
49   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;
50   PetscErrorCode ierr;
51 
52   PetscFunctionBegin;
53   ierr = MatStoreValues(aij->A);CHKERRQ(ierr);
54   ierr = MatStoreValues(aij->B);CHKERRQ(ierr);
55   PetscFunctionReturn(0);
56 }
57 
58 #undef __FUNCT__
59 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ"
60 PetscErrorCode  MatRetrieveValues_MPIBAIJ(Mat mat)
61 {
62   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;
63   PetscErrorCode ierr;
64 
65   PetscFunctionBegin;
66   ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr);
67   ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr);
68   PetscFunctionReturn(0);
69 }
70 
71 /*
72      Local utility routine that creates a mapping from the global column
73    number to the local number in the off-diagonal part of the local
74    storage of the matrix.  This is done in a non scalable way since the
75    length of colmap equals the global matrix length.
76 */
77 #undef __FUNCT__
78 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private"
79 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat)
80 {
81   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
82   Mat_SeqBAIJ    *B    = (Mat_SeqBAIJ*)baij->B->data;
83   PetscErrorCode ierr;
84   PetscInt       nbs = B->nbs,i,bs=mat->rmap->bs;
85 
86   PetscFunctionBegin;
87 #if defined(PETSC_USE_CTABLE)
88   ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr);
89   for (i=0; i<nbs; i++) {
90     ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr);
91   }
92 #else
93   ierr = PetscMalloc1(baij->Nbs+1,&baij->colmap);CHKERRQ(ierr);
94   ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr);
95   ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr);
96   for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
97 #endif
98   PetscFunctionReturn(0);
99 }
100 
101 #define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,orow,ocol)       \
102   { \
103  \
104     brow = row/bs;  \
105     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
106     rmax = aimax[brow]; nrow = ailen[brow]; \
107     bcol = col/bs; \
108     ridx = row % bs; cidx = col % bs; \
109     low  = 0; high = nrow; \
110     while (high-low > 3) { \
111       t = (low+high)/2; \
112       if (rp[t] > bcol) high = t; \
113       else              low  = t; \
114     } \
115     for (_i=low; _i<high; _i++) { \
116       if (rp[_i] > bcol) break; \
117       if (rp[_i] == bcol) { \
118         bap = ap +  bs2*_i + bs*cidx + ridx; \
119         if (addv == ADD_VALUES) *bap += value;  \
120         else                    *bap  = value;  \
121         goto a_noinsert; \
122       } \
123     } \
124     if (a->nonew == 1) goto a_noinsert; \
125     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
126     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
127     N = nrow++ - 1;  \
128     /* shift up all the later entries in this row */ \
129     for (ii=N; ii>=_i; ii--) { \
130       rp[ii+1] = rp[ii]; \
131       ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
132     } \
133     if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); }  \
134     rp[_i]                      = bcol;  \
135     ap[bs2*_i + bs*cidx + ridx] = value;  \
136 a_noinsert:; \
137     ailen[brow] = nrow; \
138   }
139 
140 #define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,orow,ocol)       \
141   { \
142     brow = row/bs;  \
143     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
144     rmax = bimax[brow]; nrow = bilen[brow]; \
145     bcol = col/bs; \
146     ridx = row % bs; cidx = col % bs; \
147     low  = 0; high = nrow; \
148     while (high-low > 3) { \
149       t = (low+high)/2; \
150       if (rp[t] > bcol) high = t; \
151       else              low  = t; \
152     } \
153     for (_i=low; _i<high; _i++) { \
154       if (rp[_i] > bcol) break; \
155       if (rp[_i] == bcol) { \
156         bap = ap +  bs2*_i + bs*cidx + ridx; \
157         if (addv == ADD_VALUES) *bap += value;  \
158         else                    *bap  = value;  \
159         goto b_noinsert; \
160       } \
161     } \
162     if (b->nonew == 1) goto b_noinsert; \
163     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column  (%D, %D) into matrix", orow, ocol); \
164     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
165     N = nrow++ - 1;  \
166     /* shift up all the later entries in this row */ \
167     for (ii=N; ii>=_i; ii--) { \
168       rp[ii+1] = rp[ii]; \
169       ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
170     } \
171     if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);}  \
172     rp[_i]                      = bcol;  \
173     ap[bs2*_i + bs*cidx + ridx] = value;  \
174 b_noinsert:; \
175     bilen[brow] = nrow; \
176   }
177 
178 #undef __FUNCT__
179 #define __FUNCT__ "MatSetValues_MPIBAIJ"
180 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
181 {
182   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
183   MatScalar      value;
184   PetscBool      roworiented = baij->roworiented;
185   PetscErrorCode ierr;
186   PetscInt       i,j,row,col;
187   PetscInt       rstart_orig=mat->rmap->rstart;
188   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
189   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;
190 
191   /* Some Variables required in the macro */
192   Mat         A     = baij->A;
193   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ*)(A)->data;
194   PetscInt    *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
195   MatScalar   *aa   =a->a;
196 
197   Mat         B     = baij->B;
198   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
199   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
200   MatScalar   *ba   =b->a;
201 
202   PetscInt  *rp,ii,nrow,_i,rmax,N,brow,bcol;
203   PetscInt  low,high,t,ridx,cidx,bs2=a->bs2;
204   MatScalar *ap,*bap;
205 
206   PetscFunctionBegin;
207   for (i=0; i<m; i++) {
208     if (im[i] < 0) continue;
209 #if defined(PETSC_USE_DEBUG)
210     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
211 #endif
212     if (im[i] >= rstart_orig && im[i] < rend_orig) {
213       row = im[i] - rstart_orig;
214       for (j=0; j<n; j++) {
215         if (in[j] >= cstart_orig && in[j] < cend_orig) {
216           col = in[j] - cstart_orig;
217           if (roworiented) value = v[i*n+j];
218           else             value = v[i+j*m];
219           MatSetValues_SeqBAIJ_A_Private(row,col,value,addv,im[i],in[j]);
220           /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
221         } else if (in[j] < 0) continue;
222 #if defined(PETSC_USE_DEBUG)
223         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
224 #endif
225         else {
226           if (mat->was_assembled) {
227             if (!baij->colmap) {
228               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
229             }
230 #if defined(PETSC_USE_CTABLE)
231             ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr);
232             col  = col - 1;
233 #else
234             col = baij->colmap[in[j]/bs] - 1;
235 #endif
236             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
237               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
238               col  =  in[j];
239               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
240               B    = baij->B;
241               b    = (Mat_SeqBAIJ*)(B)->data;
242               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
243               ba   =b->a;
244             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]);
245             else col += in[j]%bs;
246           } else col = in[j];
247           if (roworiented) value = v[i*n+j];
248           else             value = v[i+j*m];
249           MatSetValues_SeqBAIJ_B_Private(row,col,value,addv,im[i],in[j]);
250           /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
251         }
252       }
253     } else {
254       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
255       if (!baij->donotstash) {
256         mat->assembled = PETSC_FALSE;
257         if (roworiented) {
258           ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr);
259         } else {
260           ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr);
261         }
262       }
263     }
264   }
265   PetscFunctionReturn(0);
266 }
267 
268 #undef __FUNCT__
269 #define __FUNCT__ "MatSetValuesBlocked_SeqBAIJ_Inlined"
270 PETSC_STATIC_INLINE PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A,PetscInt row,PetscInt col,const PetscScalar v[],InsertMode is,PetscInt orow,PetscInt ocol)
271 {
272   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
273   PetscInt          *rp,low,high,t,ii,jj,nrow,i,rmax,N;
274   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
275   PetscErrorCode    ierr;
276   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs;
277   PetscBool         roworiented=a->roworiented;
278   const PetscScalar *value     = v;
279   MatScalar         *ap,*aa = a->a,*bap;
280 
281   PetscFunctionBegin;
282   rp   = aj + ai[row];
283   ap   = aa + bs2*ai[row];
284   rmax = imax[row];
285   nrow = ailen[row];
286   low  = 0;
287   high = nrow;
288   value = v;
289   low = 0;
290   high = nrow;
291   while (high-low > 7) {
292     t = (low+high)/2;
293     if (rp[t] > col) high = t;
294     else             low  = t;
295   }
296   for (i=low; i<high; i++) {
297     if (rp[i] > col) break;
298     if (rp[i] == col) {
299       bap = ap +  bs2*i;
300       if (roworiented) {
301         if (is == ADD_VALUES) {
302           for (ii=0; ii<bs; ii++) {
303             for (jj=ii; jj<bs2; jj+=bs) {
304               bap[jj] += *value++;
305             }
306           }
307         } else {
308           for (ii=0; ii<bs; ii++) {
309             for (jj=ii; jj<bs2; jj+=bs) {
310               bap[jj] = *value++;
311             }
312           }
313         }
314       } else {
315         if (is == ADD_VALUES) {
316           for (ii=0; ii<bs; ii++,value+=bs) {
317             for (jj=0; jj<bs; jj++) {
318               bap[jj] += value[jj];
319             }
320             bap += bs;
321           }
322         } else {
323           for (ii=0; ii<bs; ii++,value+=bs) {
324             for (jj=0; jj<bs; jj++) {
325               bap[jj]  = value[jj];
326             }
327             bap += bs;
328           }
329         }
330       }
331       goto noinsert2;
332     }
333   }
334   if (nonew == 1) goto noinsert2;
335   if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new global block indexed nonzero block (%D, %D) in the matrix", orow, ocol);
336   MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
337   N = nrow++ - 1; high++;
338   /* shift up all the later entries in this row */
339   for (ii=N; ii>=i; ii--) {
340     rp[ii+1] = rp[ii];
341     ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr);
342   }
343   if (N >= i) {
344     ierr = PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));CHKERRQ(ierr);
345   }
346   rp[i] = col;
347   bap   = ap +  bs2*i;
348   if (roworiented) {
349     for (ii=0; ii<bs; ii++) {
350       for (jj=ii; jj<bs2; jj+=bs) {
351         bap[jj] = *value++;
352       }
353     }
354   } else {
355     for (ii=0; ii<bs; ii++) {
356       for (jj=0; jj<bs; jj++) {
357         *bap++ = *value++;
358       }
359     }
360   }
361   noinsert2:;
362   ailen[row] = nrow;
363   PetscFunctionReturn(0);
364 }
365 
366 #undef __FUNCT__
367 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ"
368 /*
369     This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed
370     by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine
371 */
372 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
373 {
374   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
375   const PetscScalar *value;
376   MatScalar         *barray     = baij->barray;
377   PetscBool         roworiented = baij->roworiented;
378   PetscErrorCode    ierr;
379   PetscInt          i,j,ii,jj,row,col,rstart=baij->rstartbs;
380   PetscInt          rend=baij->rendbs,cstart=baij->cstartbs,stepval;
381   PetscInt          cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;
382 
383   PetscFunctionBegin;
384   if (!barray) {
385     ierr         = PetscMalloc1(bs2,&barray);CHKERRQ(ierr);
386     baij->barray = barray;
387   }
388 
389   if (roworiented) stepval = (n-1)*bs;
390   else stepval = (m-1)*bs;
391 
392   for (i=0; i<m; i++) {
393     if (im[i] < 0) continue;
394 #if defined(PETSC_USE_DEBUG)
395     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed row too large %D max %D",im[i],baij->Mbs-1);
396 #endif
397     if (im[i] >= rstart && im[i] < rend) {
398       row = im[i] - rstart;
399       for (j=0; j<n; j++) {
400         /* If NumCol = 1 then a copy is not required */
401         if ((roworiented) && (n == 1)) {
402           barray = (MatScalar*)v + i*bs2;
403         } else if ((!roworiented) && (m == 1)) {
404           barray = (MatScalar*)v + j*bs2;
405         } else { /* Here a copy is required */
406           if (roworiented) {
407             value = v + (i*(stepval+bs) + j)*bs;
408           } else {
409             value = v + (j*(stepval+bs) + i)*bs;
410           }
411           for (ii=0; ii<bs; ii++,value+=bs+stepval) {
412             for (jj=0; jj<bs; jj++) barray[jj] = value[jj];
413             barray += bs;
414           }
415           barray -= bs2;
416         }
417 
418         if (in[j] >= cstart && in[j] < cend) {
419           col  = in[j] - cstart;
420           ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr);
421         } else if (in[j] < 0) continue;
422 #if defined(PETSC_USE_DEBUG)
423         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block indexed column too large %D max %D",in[j],baij->Nbs-1);
424 #endif
425         else {
426           if (mat->was_assembled) {
427             if (!baij->colmap) {
428               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
429             }
430 
431 #if defined(PETSC_USE_DEBUG)
432 #if defined(PETSC_USE_CTABLE)
433             { PetscInt data;
434               ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
435               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
436             }
437 #else
438             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
439 #endif
440 #endif
441 #if defined(PETSC_USE_CTABLE)
442             ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
443             col  = (col - 1)/bs;
444 #else
445             col = (baij->colmap[in[j]] - 1)/bs;
446 #endif
447             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
448               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
449               col  =  in[j];
450             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked indexed nonzero block (%D, %D) into matrix",im[i],in[j]);
451           } else col = in[j];
452           ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr);
453         }
454       }
455     } else {
456       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process block indexed row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
457       if (!baij->donotstash) {
458         if (roworiented) {
459           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
460         } else {
461           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
462         }
463       }
464     }
465   }
466   PetscFunctionReturn(0);
467 }
468 
469 #define HASH_KEY 0.6180339887
470 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp)))
471 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
472 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
473 #undef __FUNCT__
474 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT"
475 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
476 {
477   Mat_MPIBAIJ    *baij       = (Mat_MPIBAIJ*)mat->data;
478   PetscBool      roworiented = baij->roworiented;
479   PetscErrorCode ierr;
480   PetscInt       i,j,row,col;
481   PetscInt       rstart_orig=mat->rmap->rstart;
482   PetscInt       rend_orig  =mat->rmap->rend,Nbs=baij->Nbs;
483   PetscInt       h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx;
484   PetscReal      tmp;
485   MatScalar      **HD = baij->hd,value;
486 #if defined(PETSC_USE_DEBUG)
487   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
488 #endif
489 
490   PetscFunctionBegin;
491   for (i=0; i<m; i++) {
492 #if defined(PETSC_USE_DEBUG)
493     if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
494     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
495 #endif
496     row = im[i];
497     if (row >= rstart_orig && row < rend_orig) {
498       for (j=0; j<n; j++) {
499         col = in[j];
500         if (roworiented) value = v[i*n+j];
501         else             value = v[i+j*m];
502         /* Look up PetscInto the Hash Table */
503         key = (row/bs)*Nbs+(col/bs)+1;
504         h1  = HASH(size,key,tmp);
505 
506 
507         idx = h1;
508 #if defined(PETSC_USE_DEBUG)
509         insert_ct++;
510         total_ct++;
511         if (HT[idx] != key) {
512           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
513           if (idx == size) {
514             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
515             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
516           }
517         }
518 #else
519         if (HT[idx] != key) {
520           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
521           if (idx == size) {
522             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
523             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
524           }
525         }
526 #endif
527         /* A HASH table entry is found, so insert the values at the correct address */
528         if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
529         else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
530       }
531     } else if (!baij->donotstash) {
532       if (roworiented) {
533         ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr);
534       } else {
535         ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr);
536       }
537     }
538   }
539 #if defined(PETSC_USE_DEBUG)
540   baij->ht_total_ct  = total_ct;
541   baij->ht_insert_ct = insert_ct;
542 #endif
543   PetscFunctionReturn(0);
544 }
545 
546 #undef __FUNCT__
547 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT"
548 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
549 {
550   Mat_MPIBAIJ       *baij       = (Mat_MPIBAIJ*)mat->data;
551   PetscBool         roworiented = baij->roworiented;
552   PetscErrorCode    ierr;
553   PetscInt          i,j,ii,jj,row,col;
554   PetscInt          rstart=baij->rstartbs;
555   PetscInt          rend  =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2;
556   PetscInt          h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
557   PetscReal         tmp;
558   MatScalar         **HD = baij->hd,*baij_a;
559   const PetscScalar *v_t,*value;
560 #if defined(PETSC_USE_DEBUG)
561   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
562 #endif
563 
564   PetscFunctionBegin;
565   if (roworiented) stepval = (n-1)*bs;
566   else stepval = (m-1)*bs;
567 
568   for (i=0; i<m; i++) {
569 #if defined(PETSC_USE_DEBUG)
570     if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]);
571     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],baij->Mbs-1);
572 #endif
573     row = im[i];
574     v_t = v + i*nbs2;
575     if (row >= rstart && row < rend) {
576       for (j=0; j<n; j++) {
577         col = in[j];
578 
579         /* Look up into the Hash Table */
580         key = row*Nbs+col+1;
581         h1  = HASH(size,key,tmp);
582 
583         idx = h1;
584 #if defined(PETSC_USE_DEBUG)
585         total_ct++;
586         insert_ct++;
587         if (HT[idx] != key) {
588           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
589           if (idx == size) {
590             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
591             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
592           }
593         }
594 #else
595         if (HT[idx] != key) {
596           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
597           if (idx == size) {
598             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
599             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
600           }
601         }
602 #endif
603         baij_a = HD[idx];
604         if (roworiented) {
605           /*value = v + i*(stepval+bs)*bs + j*bs;*/
606           /* value = v + (i*(stepval+bs)+j)*bs; */
607           value = v_t;
608           v_t  += bs;
609           if (addv == ADD_VALUES) {
610             for (ii=0; ii<bs; ii++,value+=stepval) {
611               for (jj=ii; jj<bs2; jj+=bs) {
612                 baij_a[jj] += *value++;
613               }
614             }
615           } else {
616             for (ii=0; ii<bs; ii++,value+=stepval) {
617               for (jj=ii; jj<bs2; jj+=bs) {
618                 baij_a[jj] = *value++;
619               }
620             }
621           }
622         } else {
623           value = v + j*(stepval+bs)*bs + i*bs;
624           if (addv == ADD_VALUES) {
625             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
626               for (jj=0; jj<bs; jj++) {
627                 baij_a[jj] += *value++;
628               }
629             }
630           } else {
631             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
632               for (jj=0; jj<bs; jj++) {
633                 baij_a[jj] = *value++;
634               }
635             }
636           }
637         }
638       }
639     } else {
640       if (!baij->donotstash) {
641         if (roworiented) {
642           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
643         } else {
644           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
645         }
646       }
647     }
648   }
649 #if defined(PETSC_USE_DEBUG)
650   baij->ht_total_ct  = total_ct;
651   baij->ht_insert_ct = insert_ct;
652 #endif
653   PetscFunctionReturn(0);
654 }
655 
656 #undef __FUNCT__
657 #define __FUNCT__ "MatGetValues_MPIBAIJ"
658 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
659 {
660   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
661   PetscErrorCode ierr;
662   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
663   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;
664 
665   PetscFunctionBegin;
666   for (i=0; i<m; i++) {
667     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
668     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
669     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
670       row = idxm[i] - bsrstart;
671       for (j=0; j<n; j++) {
672         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
673         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
674         if (idxn[j] >= bscstart && idxn[j] < bscend) {
675           col  = idxn[j] - bscstart;
676           ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
677         } else {
678           if (!baij->colmap) {
679             ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
680           }
681 #if defined(PETSC_USE_CTABLE)
682           ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr);
683           data--;
684 #else
685           data = baij->colmap[idxn[j]/bs]-1;
686 #endif
687           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
688           else {
689             col  = data + idxn[j]%bs;
690             ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
691           }
692         }
693       }
694     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
695   }
696   PetscFunctionReturn(0);
697 }
698 
699 #undef __FUNCT__
700 #define __FUNCT__ "MatNorm_MPIBAIJ"
701 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm)
702 {
703   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
704   Mat_SeqBAIJ    *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data;
705   PetscErrorCode ierr;
706   PetscInt       i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col;
707   PetscReal      sum = 0.0;
708   MatScalar      *v;
709 
710   PetscFunctionBegin;
711   if (baij->size == 1) {
712     ierr =  MatNorm(baij->A,type,nrm);CHKERRQ(ierr);
713   } else {
714     if (type == NORM_FROBENIUS) {
715       v  = amat->a;
716       nz = amat->nz*bs2;
717       for (i=0; i<nz; i++) {
718         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
719       }
720       v  = bmat->a;
721       nz = bmat->nz*bs2;
722       for (i=0; i<nz; i++) {
723         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
724       }
725       ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
726       *nrm = PetscSqrtReal(*nrm);
727     } else if (type == NORM_1) { /* max column sum */
728       PetscReal *tmp,*tmp2;
729       PetscInt  *jj,*garray=baij->garray,cstart=baij->rstartbs;
730       ierr = PetscMalloc2(mat->cmap->N,&tmp,mat->cmap->N,&tmp2);CHKERRQ(ierr);
731       ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr);
732       v    = amat->a; jj = amat->j;
733       for (i=0; i<amat->nz; i++) {
734         for (j=0; j<bs; j++) {
735           col = bs*(cstart + *jj) + j; /* column index */
736           for (row=0; row<bs; row++) {
737             tmp[col] += PetscAbsScalar(*v);  v++;
738           }
739         }
740         jj++;
741       }
742       v = bmat->a; jj = bmat->j;
743       for (i=0; i<bmat->nz; i++) {
744         for (j=0; j<bs; j++) {
745           col = bs*garray[*jj] + j;
746           for (row=0; row<bs; row++) {
747             tmp[col] += PetscAbsScalar(*v); v++;
748           }
749         }
750         jj++;
751       }
752       ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
753       *nrm = 0.0;
754       for (j=0; j<mat->cmap->N; j++) {
755         if (tmp2[j] > *nrm) *nrm = tmp2[j];
756       }
757       ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr);
758     } else if (type == NORM_INFINITY) { /* max row sum */
759       PetscReal *sums;
760       ierr = PetscMalloc1(bs,&sums);CHKERRQ(ierr);
761       sum  = 0.0;
762       for (j=0; j<amat->mbs; j++) {
763         for (row=0; row<bs; row++) sums[row] = 0.0;
764         v  = amat->a + bs2*amat->i[j];
765         nz = amat->i[j+1]-amat->i[j];
766         for (i=0; i<nz; i++) {
767           for (col=0; col<bs; col++) {
768             for (row=0; row<bs; row++) {
769               sums[row] += PetscAbsScalar(*v); v++;
770             }
771           }
772         }
773         v  = bmat->a + bs2*bmat->i[j];
774         nz = bmat->i[j+1]-bmat->i[j];
775         for (i=0; i<nz; i++) {
776           for (col=0; col<bs; col++) {
777             for (row=0; row<bs; row++) {
778               sums[row] += PetscAbsScalar(*v); v++;
779             }
780           }
781         }
782         for (row=0; row<bs; row++) {
783           if (sums[row] > sum) sum = sums[row];
784         }
785       }
786       ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
787       ierr = PetscFree(sums);CHKERRQ(ierr);
788     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet");
789   }
790   PetscFunctionReturn(0);
791 }
792 
793 /*
794   Creates the hash table, and sets the table
795   This table is created only once.
796   If new entried need to be added to the matrix
797   then the hash table has to be destroyed and
798   recreated.
799 */
800 #undef __FUNCT__
801 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private"
802 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor)
803 {
804   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
805   Mat            A     = baij->A,B=baij->B;
806   Mat_SeqBAIJ    *a    = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data;
807   PetscInt       i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
808   PetscErrorCode ierr;
809   PetscInt       ht_size,bs2=baij->bs2,rstart=baij->rstartbs;
810   PetscInt       cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs;
811   PetscInt       *HT,key;
812   MatScalar      **HD;
813   PetscReal      tmp;
814 #if defined(PETSC_USE_INFO)
815   PetscInt ct=0,max=0;
816 #endif
817 
818   PetscFunctionBegin;
819   if (baij->ht) PetscFunctionReturn(0);
820 
821   baij->ht_size = (PetscInt)(factor*nz);
822   ht_size       = baij->ht_size;
823 
824   /* Allocate Memory for Hash Table */
825   ierr = PetscCalloc2(ht_size,&baij->hd,ht_size,&baij->ht);CHKERRQ(ierr);
826   HD   = baij->hd;
827   HT   = baij->ht;
828 
829   /* Loop Over A */
830   for (i=0; i<a->mbs; i++) {
831     for (j=ai[i]; j<ai[i+1]; j++) {
832       row = i+rstart;
833       col = aj[j]+cstart;
834 
835       key = row*Nbs + col + 1;
836       h1  = HASH(ht_size,key,tmp);
837       for (k=0; k<ht_size; k++) {
838         if (!HT[(h1+k)%ht_size]) {
839           HT[(h1+k)%ht_size] = key;
840           HD[(h1+k)%ht_size] = a->a + j*bs2;
841           break;
842 #if defined(PETSC_USE_INFO)
843         } else {
844           ct++;
845 #endif
846         }
847       }
848 #if defined(PETSC_USE_INFO)
849       if (k> max) max = k;
850 #endif
851     }
852   }
853   /* Loop Over B */
854   for (i=0; i<b->mbs; i++) {
855     for (j=bi[i]; j<bi[i+1]; j++) {
856       row = i+rstart;
857       col = garray[bj[j]];
858       key = row*Nbs + col + 1;
859       h1  = HASH(ht_size,key,tmp);
860       for (k=0; k<ht_size; k++) {
861         if (!HT[(h1+k)%ht_size]) {
862           HT[(h1+k)%ht_size] = key;
863           HD[(h1+k)%ht_size] = b->a + j*bs2;
864           break;
865 #if defined(PETSC_USE_INFO)
866         } else {
867           ct++;
868 #endif
869         }
870       }
871 #if defined(PETSC_USE_INFO)
872       if (k> max) max = k;
873 #endif
874     }
875   }
876 
877   /* Print Summary */
878 #if defined(PETSC_USE_INFO)
879   for (i=0,j=0; i<ht_size; i++) {
880     if (HT[i]) j++;
881   }
882   ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr);
883 #endif
884   PetscFunctionReturn(0);
885 }
886 
887 #undef __FUNCT__
888 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ"
889 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
890 {
891   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
892   PetscErrorCode ierr;
893   PetscInt       nstash,reallocs;
894   InsertMode     addv;
895 
896   PetscFunctionBegin;
897   if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0);
898 
899   /* make sure all processors are either in INSERTMODE or ADDMODE */
900   ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
901   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
902   mat->insertmode = addv; /* in case this processor had no cache */
903 
904   ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr);
905   ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr);
906   ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr);
907   ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr);
908   ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr);
909   ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr);
910   PetscFunctionReturn(0);
911 }
912 
913 #undef __FUNCT__
914 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ"
915 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
916 {
917   Mat_MPIBAIJ    *baij=(Mat_MPIBAIJ*)mat->data;
918   Mat_SeqBAIJ    *a   =(Mat_SeqBAIJ*)baij->A->data;
919   PetscErrorCode ierr;
920   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
921   PetscInt       *row,*col;
922   PetscBool      r1,r2,r3,other_disassembled;
923   MatScalar      *val;
924   InsertMode     addv = mat->insertmode;
925   PetscMPIInt    n;
926 
927   PetscFunctionBegin;
928   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
929   if (!baij->donotstash && !mat->nooffprocentries) {
930     while (1) {
931       ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
932       if (!flg) break;
933 
934       for (i=0; i<n;) {
935         /* Now identify the consecutive vals belonging to the same row */
936         for (j=i,rstart=row[j]; j<n; j++) {
937           if (row[j] != rstart) break;
938         }
939         if (j < n) ncols = j-i;
940         else       ncols = n-i;
941         /* Now assemble all these values with a single function call */
942         ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr);
943         i    = j;
944       }
945     }
946     ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr);
947     /* Now process the block-stash. Since the values are stashed column-oriented,
948        set the roworiented flag to column oriented, and after MatSetValues()
949        restore the original flags */
950     r1 = baij->roworiented;
951     r2 = a->roworiented;
952     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
953 
954     baij->roworiented = PETSC_FALSE;
955     a->roworiented    = PETSC_FALSE;
956 
957     (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */
958     while (1) {
959       ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
960       if (!flg) break;
961 
962       for (i=0; i<n;) {
963         /* Now identify the consecutive vals belonging to the same row */
964         for (j=i,rstart=row[j]; j<n; j++) {
965           if (row[j] != rstart) break;
966         }
967         if (j < n) ncols = j-i;
968         else       ncols = n-i;
969         ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr);
970         i    = j;
971       }
972     }
973     ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr);
974 
975     baij->roworiented = r1;
976     a->roworiented    = r2;
977 
978     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */
979   }
980 
981   ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr);
982   ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr);
983 
984   /* determine if any processor has disassembled, if so we must
985      also disassemble ourselfs, in order that we may reassemble. */
986   /*
987      if nonzero structure of submatrix B cannot change then we know that
988      no processor disassembled thus we can skip this stuff
989   */
990   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
991     ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
992     if (mat->was_assembled && !other_disassembled) {
993       ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
994     }
995   }
996 
997   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
998     ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr);
999   }
1000   ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr);
1001   ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr);
1002 
1003 #if defined(PETSC_USE_INFO)
1004   if (baij->ht && mode== MAT_FINAL_ASSEMBLY) {
1005     ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr);
1006 
1007     baij->ht_total_ct  = 0;
1008     baij->ht_insert_ct = 0;
1009   }
1010 #endif
1011   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
1012     ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr);
1013 
1014     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
1015     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
1016   }
1017 
1018   ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr);
1019 
1020   baij->rowvalues = 0;
1021 
1022   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
1023   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
1024     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
1025     ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1026   }
1027   PetscFunctionReturn(0);
1028 }
1029 
1030 extern PetscErrorCode MatView_SeqBAIJ(Mat,PetscViewer);
1031 #include <petscdraw.h>
1032 #undef __FUNCT__
1033 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket"
1034 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
1035 {
1036   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
1037   PetscErrorCode    ierr;
1038   PetscMPIInt       rank = baij->rank;
1039   PetscInt          bs   = mat->rmap->bs;
1040   PetscBool         iascii,isdraw;
1041   PetscViewer       sviewer;
1042   PetscViewerFormat format;
1043 
1044   PetscFunctionBegin;
1045   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1046   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
1047   if (iascii) {
1048     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
1049     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1050       MatInfo info;
1051       ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr);
1052       ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr);
1053       ierr = PetscViewerASCIIPushSynchronized(viewer);CHKERRQ(ierr);
1054       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",
1055                                                 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr);
1056       ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr);
1057       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr);
1058       ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr);
1059       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr);
1060       ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
1061       ierr = PetscViewerASCIIPopSynchronized(viewer);CHKERRQ(ierr);
1062       ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr);
1063       ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr);
1064       PetscFunctionReturn(0);
1065     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1066       ierr = PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);CHKERRQ(ierr);
1067       PetscFunctionReturn(0);
1068     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1069       PetscFunctionReturn(0);
1070     }
1071   }
1072 
1073   if (isdraw) {
1074     PetscDraw draw;
1075     PetscBool isnull;
1076     ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
1077     ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
1078   }
1079 
1080   {
1081     /* assemble the entire matrix onto first processor. */
1082     Mat         A;
1083     Mat_SeqBAIJ *Aloc;
1084     PetscInt    M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
1085     MatScalar   *a;
1086     const char  *matname;
1087 
1088     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
1089     /* Perhaps this should be the type of mat? */
1090     ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr);
1091     if (!rank) {
1092       ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr);
1093     } else {
1094       ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr);
1095     }
1096     ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr);
1097     ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr);
1098     ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
1099     ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr);
1100 
1101     /* copy over the A part */
1102     Aloc = (Mat_SeqBAIJ*)baij->A->data;
1103     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1104     ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr);
1105 
1106     for (i=0; i<mbs; i++) {
1107       rvals[0] = bs*(baij->rstartbs + i);
1108       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1109       for (j=ai[i]; j<ai[i+1]; j++) {
1110         col = (baij->cstartbs+aj[j])*bs;
1111         for (k=0; k<bs; k++) {
1112           ierr      = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
1113           col++; a += bs;
1114         }
1115       }
1116     }
1117     /* copy over the B part */
1118     Aloc = (Mat_SeqBAIJ*)baij->B->data;
1119     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1120     for (i=0; i<mbs; i++) {
1121       rvals[0] = bs*(baij->rstartbs + i);
1122       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1123       for (j=ai[i]; j<ai[i+1]; j++) {
1124         col = baij->garray[aj[j]]*bs;
1125         for (k=0; k<bs; k++) {
1126           ierr      = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
1127           col++; a += bs;
1128         }
1129       }
1130     }
1131     ierr = PetscFree(rvals);CHKERRQ(ierr);
1132     ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1133     ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1134     /*
1135        Everyone has to call to draw the matrix since the graphics waits are
1136        synchronized across all processors that share the PetscDraw object
1137     */
1138     ierr = PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr);
1139     ierr = PetscObjectGetName((PetscObject)mat,&matname);CHKERRQ(ierr);
1140     if (!rank) {
1141       ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,matname);CHKERRQ(ierr);
1142       ierr = MatView_SeqBAIJ(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr);
1143     }
1144     ierr = PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);CHKERRQ(ierr);
1145     ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
1146     ierr = MatDestroy(&A);CHKERRQ(ierr);
1147   }
1148   PetscFunctionReturn(0);
1149 }
1150 
1151 #undef __FUNCT__
1152 #define __FUNCT__ "MatView_MPIBAIJ_Binary"
1153 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer)
1154 {
1155   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)mat->data;
1156   Mat_SeqBAIJ    *A = (Mat_SeqBAIJ*)a->A->data;
1157   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
1158   PetscErrorCode ierr;
1159   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
1160   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
1161   int            fd;
1162   PetscScalar    *column_values;
1163   FILE           *file;
1164   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1165   PetscInt       message_count,flowcontrolcount;
1166 
1167   PetscFunctionBegin;
1168   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr);
1169   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
1170   nz   = bs2*(A->nz + B->nz);
1171   rlen = mat->rmap->n;
1172   ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
1173   if (!rank) {
1174     header[0] = MAT_FILE_CLASSID;
1175     header[1] = mat->rmap->N;
1176     header[2] = mat->cmap->N;
1177 
1178     ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1179     ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1180     /* get largest number of rows any processor has */
1181     range = mat->rmap->range;
1182     for (i=1; i<size; i++) {
1183       rlen = PetscMax(rlen,range[i+1] - range[i]);
1184     }
1185   } else {
1186     ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1187   }
1188 
1189   ierr = PetscMalloc1(rlen/bs,&crow_lens);CHKERRQ(ierr);
1190   /* compute lengths of each row  */
1191   for (i=0; i<a->mbs; i++) {
1192     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1193   }
1194   /* store the row lengths to the file */
1195   ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr);
1196   if (!rank) {
1197     MPI_Status status;
1198     ierr = PetscMalloc1(rlen,&row_lens);CHKERRQ(ierr);
1199     rlen = (range[1] - range[0])/bs;
1200     for (i=0; i<rlen; i++) {
1201       for (j=0; j<bs; j++) {
1202         row_lens[i*bs+j] = bs*crow_lens[i];
1203       }
1204     }
1205     ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1206     for (i=1; i<size; i++) {
1207       rlen = (range[i+1] - range[i])/bs;
1208       ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr);
1209       ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1210       for (k=0; k<rlen; k++) {
1211         for (j=0; j<bs; j++) {
1212           row_lens[k*bs+j] = bs*crow_lens[k];
1213         }
1214       }
1215       ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1216     }
1217     ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr);
1218     ierr = PetscFree(row_lens);CHKERRQ(ierr);
1219   } else {
1220     ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr);
1221     ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1222     ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr);
1223   }
1224   ierr = PetscFree(crow_lens);CHKERRQ(ierr);
1225 
1226   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
1227      information needed to make it for each row from a block row. This does require more communication but still not more than
1228      the communication needed for the nonzero values  */
1229   nzmax = nz; /*  space a largest processor needs */
1230   ierr  = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1231   ierr  = PetscMalloc1(nzmax,&column_indices);CHKERRQ(ierr);
1232   cnt   = 0;
1233   for (i=0; i<a->mbs; i++) {
1234     pcnt = cnt;
1235     for (j=B->i[i]; j<B->i[i+1]; j++) {
1236       if ((col = garray[B->j[j]]) > cstart) break;
1237       for (l=0; l<bs; l++) {
1238         column_indices[cnt++] = bs*col+l;
1239       }
1240     }
1241     for (k=A->i[i]; k<A->i[i+1]; k++) {
1242       for (l=0; l<bs; l++) {
1243         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1244       }
1245     }
1246     for (; j<B->i[i+1]; j++) {
1247       for (l=0; l<bs; l++) {
1248         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1249       }
1250     }
1251     len = cnt - pcnt;
1252     for (k=1; k<bs; k++) {
1253       ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr);
1254       cnt += len;
1255     }
1256   }
1257   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1258 
1259   /* store the columns to the file */
1260   ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr);
1261   if (!rank) {
1262     MPI_Status status;
1263     ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1264     for (i=1; i<size; i++) {
1265       ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr);
1266       ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1267       ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1268       ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1269     }
1270     ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr);
1271   } else {
1272     ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr);
1273     ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1274     ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1275     ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr);
1276   }
1277   ierr = PetscFree(column_indices);CHKERRQ(ierr);
1278 
1279   /* load up the numerical values */
1280   ierr = PetscMalloc1(nzmax,&column_values);CHKERRQ(ierr);
1281   cnt  = 0;
1282   for (i=0; i<a->mbs; i++) {
1283     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1284     for (j=B->i[i]; j<B->i[i+1]; j++) {
1285       if (garray[B->j[j]] > cstart) break;
1286       for (l=0; l<bs; l++) {
1287         for (ll=0; ll<bs; ll++) {
1288           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1289         }
1290       }
1291       cnt += bs;
1292     }
1293     for (k=A->i[i]; k<A->i[i+1]; k++) {
1294       for (l=0; l<bs; l++) {
1295         for (ll=0; ll<bs; ll++) {
1296           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1297         }
1298       }
1299       cnt += bs;
1300     }
1301     for (; j<B->i[i+1]; j++) {
1302       for (l=0; l<bs; l++) {
1303         for (ll=0; ll<bs; ll++) {
1304           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1305         }
1306       }
1307       cnt += bs;
1308     }
1309     cnt += (bs-1)*rlen;
1310   }
1311   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1312 
1313   /* store the column values to the file */
1314   ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr);
1315   if (!rank) {
1316     MPI_Status status;
1317     ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr);
1318     for (i=1; i<size; i++) {
1319       ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr);
1320       ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1321       ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1322       ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr);
1323     }
1324     ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr);
1325   } else {
1326     ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr);
1327     ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1328     ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1329     ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr);
1330   }
1331   ierr = PetscFree(column_values);CHKERRQ(ierr);
1332 
1333   ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr);
1334   if (file) {
1335     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1336   }
1337   PetscFunctionReturn(0);
1338 }
1339 
1340 #undef __FUNCT__
1341 #define __FUNCT__ "MatView_MPIBAIJ"
1342 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
1343 {
1344   PetscErrorCode ierr;
1345   PetscBool      iascii,isdraw,issocket,isbinary;
1346 
1347   PetscFunctionBegin;
1348   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1349   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
1350   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr);
1351   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
1352   if (iascii || isdraw || issocket) {
1353     ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr);
1354   } else if (isbinary) {
1355     ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr);
1356   }
1357   PetscFunctionReturn(0);
1358 }
1359 
1360 #undef __FUNCT__
1361 #define __FUNCT__ "MatDestroy_MPIBAIJ"
1362 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
1363 {
1364   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
1365   PetscErrorCode ierr;
1366 
1367   PetscFunctionBegin;
1368 #if defined(PETSC_USE_LOG)
1369   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1370 #endif
1371   ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr);
1372   ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr);
1373   ierr = MatDestroy(&baij->A);CHKERRQ(ierr);
1374   ierr = MatDestroy(&baij->B);CHKERRQ(ierr);
1375 #if defined(PETSC_USE_CTABLE)
1376   ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr);
1377 #else
1378   ierr = PetscFree(baij->colmap);CHKERRQ(ierr);
1379 #endif
1380   ierr = PetscFree(baij->garray);CHKERRQ(ierr);
1381   ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr);
1382   ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr);
1383   ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr);
1384   ierr = PetscFree(baij->barray);CHKERRQ(ierr);
1385   ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr);
1386   ierr = PetscFree(baij->rangebs);CHKERRQ(ierr);
1387   ierr = PetscFree(mat->data);CHKERRQ(ierr);
1388 
1389   ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr);
1390   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr);
1391   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr);
1392   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr);
1393   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr);
1394   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr);
1395   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr);
1396   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr);
1397   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr);
1398   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr);
1399   PetscFunctionReturn(0);
1400 }
1401 
1402 #undef __FUNCT__
1403 #define __FUNCT__ "MatMult_MPIBAIJ"
1404 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
1405 {
1406   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1407   PetscErrorCode ierr;
1408   PetscInt       nt;
1409 
1410   PetscFunctionBegin;
1411   ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr);
1412   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1413   ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr);
1414   if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
1415   ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1416   ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr);
1417   ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1418   ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr);
1419   PetscFunctionReturn(0);
1420 }
1421 
1422 #undef __FUNCT__
1423 #define __FUNCT__ "MatMultAdd_MPIBAIJ"
1424 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1425 {
1426   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1427   PetscErrorCode ierr;
1428 
1429   PetscFunctionBegin;
1430   ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1431   ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr);
1432   ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1433   ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr);
1434   PetscFunctionReturn(0);
1435 }
1436 
1437 #undef __FUNCT__
1438 #define __FUNCT__ "MatMultTranspose_MPIBAIJ"
1439 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
1440 {
1441   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1442   PetscErrorCode ierr;
1443   PetscBool      merged;
1444 
1445   PetscFunctionBegin;
1446   ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr);
1447   /* do nondiagonal part */
1448   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr);
1449   if (!merged) {
1450     /* send it on its way */
1451     ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1452     /* do local part */
1453     ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr);
1454     /* receive remote parts: note this assumes the values are not actually */
1455     /* inserted in yy until the next line */
1456     ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1457   } else {
1458     /* do local part */
1459     ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr);
1460     /* send it on its way */
1461     ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1462     /* values actually were received in the Begin() but we need to call this nop */
1463     ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1464   }
1465   PetscFunctionReturn(0);
1466 }
1467 
1468 #undef __FUNCT__
1469 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ"
1470 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1471 {
1472   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1473   PetscErrorCode ierr;
1474 
1475   PetscFunctionBegin;
1476   /* do nondiagonal part */
1477   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr);
1478   /* send it on its way */
1479   ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1480   /* do local part */
1481   ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr);
1482   /* receive remote parts: note this assumes the values are not actually */
1483   /* inserted in yy until the next line, which is true for my implementation*/
1484   /* but is not perhaps always true. */
1485   ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1486   PetscFunctionReturn(0);
1487 }
1488 
1489 /*
1490   This only works correctly for square matrices where the subblock A->A is the
1491    diagonal block
1492 */
1493 #undef __FUNCT__
1494 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ"
1495 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
1496 {
1497   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1498   PetscErrorCode ierr;
1499 
1500   PetscFunctionBegin;
1501   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1502   ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr);
1503   PetscFunctionReturn(0);
1504 }
1505 
1506 #undef __FUNCT__
1507 #define __FUNCT__ "MatScale_MPIBAIJ"
1508 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa)
1509 {
1510   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1511   PetscErrorCode ierr;
1512 
1513   PetscFunctionBegin;
1514   ierr = MatScale(a->A,aa);CHKERRQ(ierr);
1515   ierr = MatScale(a->B,aa);CHKERRQ(ierr);
1516   PetscFunctionReturn(0);
1517 }
1518 
1519 #undef __FUNCT__
1520 #define __FUNCT__ "MatGetRow_MPIBAIJ"
1521 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1522 {
1523   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
1524   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1525   PetscErrorCode ierr;
1526   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1527   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1528   PetscInt       *cmap,*idx_p,cstart = mat->cstartbs;
1529 
1530   PetscFunctionBegin;
1531   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1532   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1533   mat->getrowactive = PETSC_TRUE;
1534 
1535   if (!mat->rowvalues && (idx || v)) {
1536     /*
1537         allocate enough space to hold information from the longest row.
1538     */
1539     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data;
1540     PetscInt    max = 1,mbs = mat->mbs,tmp;
1541     for (i=0; i<mbs; i++) {
1542       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1543       if (max < tmp) max = tmp;
1544     }
1545     ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr);
1546   }
1547   lrow = row - brstart;
1548 
1549   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1550   if (!v)   {pvA = 0; pvB = 0;}
1551   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1552   ierr  = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr);
1553   ierr  = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr);
1554   nztot = nzA + nzB;
1555 
1556   cmap = mat->garray;
1557   if (v  || idx) {
1558     if (nztot) {
1559       /* Sort by increasing column numbers, assuming A and B already sorted */
1560       PetscInt imark = -1;
1561       if (v) {
1562         *v = v_p = mat->rowvalues;
1563         for (i=0; i<nzB; i++) {
1564           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1565           else break;
1566         }
1567         imark = i;
1568         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1569         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1570       }
1571       if (idx) {
1572         *idx = idx_p = mat->rowindices;
1573         if (imark > -1) {
1574           for (i=0; i<imark; i++) {
1575             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1576           }
1577         } else {
1578           for (i=0; i<nzB; i++) {
1579             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1580             else break;
1581           }
1582           imark = i;
1583         }
1584         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1585         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1586       }
1587     } else {
1588       if (idx) *idx = 0;
1589       if (v)   *v   = 0;
1590     }
1591   }
1592   *nz  = nztot;
1593   ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr);
1594   ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr);
1595   PetscFunctionReturn(0);
1596 }
1597 
1598 #undef __FUNCT__
1599 #define __FUNCT__ "MatRestoreRow_MPIBAIJ"
1600 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1601 {
1602   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
1603 
1604   PetscFunctionBegin;
1605   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called");
1606   baij->getrowactive = PETSC_FALSE;
1607   PetscFunctionReturn(0);
1608 }
1609 
1610 #undef __FUNCT__
1611 #define __FUNCT__ "MatZeroEntries_MPIBAIJ"
1612 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
1613 {
1614   Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;
1615   PetscErrorCode ierr;
1616 
1617   PetscFunctionBegin;
1618   ierr = MatZeroEntries(l->A);CHKERRQ(ierr);
1619   ierr = MatZeroEntries(l->B);CHKERRQ(ierr);
1620   PetscFunctionReturn(0);
1621 }
1622 
1623 #undef __FUNCT__
1624 #define __FUNCT__ "MatGetInfo_MPIBAIJ"
1625 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1626 {
1627   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)matin->data;
1628   Mat            A  = a->A,B = a->B;
1629   PetscErrorCode ierr;
1630   PetscReal      isend[5],irecv[5];
1631 
1632   PetscFunctionBegin;
1633   info->block_size = (PetscReal)matin->rmap->bs;
1634 
1635   ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr);
1636 
1637   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1638   isend[3] = info->memory;  isend[4] = info->mallocs;
1639 
1640   ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr);
1641 
1642   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1643   isend[3] += info->memory;  isend[4] += info->mallocs;
1644 
1645   if (flag == MAT_LOCAL) {
1646     info->nz_used      = isend[0];
1647     info->nz_allocated = isend[1];
1648     info->nz_unneeded  = isend[2];
1649     info->memory       = isend[3];
1650     info->mallocs      = isend[4];
1651   } else if (flag == MAT_GLOBAL_MAX) {
1652     ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr);
1653 
1654     info->nz_used      = irecv[0];
1655     info->nz_allocated = irecv[1];
1656     info->nz_unneeded  = irecv[2];
1657     info->memory       = irecv[3];
1658     info->mallocs      = irecv[4];
1659   } else if (flag == MAT_GLOBAL_SUM) {
1660     ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr);
1661 
1662     info->nz_used      = irecv[0];
1663     info->nz_allocated = irecv[1];
1664     info->nz_unneeded  = irecv[2];
1665     info->memory       = irecv[3];
1666     info->mallocs      = irecv[4];
1667   } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1668   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1669   info->fill_ratio_needed = 0;
1670   info->factor_mallocs    = 0;
1671   PetscFunctionReturn(0);
1672 }
1673 
1674 #undef __FUNCT__
1675 #define __FUNCT__ "MatSetOption_MPIBAIJ"
1676 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg)
1677 {
1678   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1679   PetscErrorCode ierr;
1680 
1681   PetscFunctionBegin;
1682   switch (op) {
1683   case MAT_NEW_NONZERO_LOCATIONS:
1684   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1685   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1686   case MAT_KEEP_NONZERO_PATTERN:
1687   case MAT_NEW_NONZERO_LOCATION_ERR:
1688     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1689     ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr);
1690     break;
1691   case MAT_ROW_ORIENTED:
1692     a->roworiented = flg;
1693 
1694     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1695     ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr);
1696     break;
1697   case MAT_NEW_DIAGONALS:
1698     ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr);
1699     break;
1700   case MAT_IGNORE_OFF_PROC_ENTRIES:
1701     a->donotstash = flg;
1702     break;
1703   case MAT_USE_HASH_TABLE:
1704     a->ht_flag = flg;
1705     break;
1706   case MAT_SYMMETRIC:
1707   case MAT_STRUCTURALLY_SYMMETRIC:
1708   case MAT_HERMITIAN:
1709   case MAT_SYMMETRY_ETERNAL:
1710     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1711     break;
1712   default:
1713     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op);
1714   }
1715   PetscFunctionReturn(0);
1716 }
1717 
1718 #undef __FUNCT__
1719 #define __FUNCT__ "MatTranspose_MPIBAIJ"
1720 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout)
1721 {
1722   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
1723   Mat_SeqBAIJ    *Aloc;
1724   Mat            B;
1725   PetscErrorCode ierr;
1726   PetscInt       M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col;
1727   PetscInt       bs=A->rmap->bs,mbs=baij->mbs;
1728   MatScalar      *a;
1729 
1730   PetscFunctionBegin;
1731   if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1732   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1733     ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1734     ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr);
1735     ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr);
1736     /* Do not know preallocation information, but must set block size */
1737     ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr);
1738   } else {
1739     B = *matout;
1740   }
1741 
1742   /* copy over the A part */
1743   Aloc = (Mat_SeqBAIJ*)baij->A->data;
1744   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1745   ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr);
1746 
1747   for (i=0; i<mbs; i++) {
1748     rvals[0] = bs*(baij->rstartbs + i);
1749     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1750     for (j=ai[i]; j<ai[i+1]; j++) {
1751       col = (baij->cstartbs+aj[j])*bs;
1752       for (k=0; k<bs; k++) {
1753         ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
1754 
1755         col++; a += bs;
1756       }
1757     }
1758   }
1759   /* copy over the B part */
1760   Aloc = (Mat_SeqBAIJ*)baij->B->data;
1761   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1762   for (i=0; i<mbs; i++) {
1763     rvals[0] = bs*(baij->rstartbs + i);
1764     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1765     for (j=ai[i]; j<ai[i+1]; j++) {
1766       col = baij->garray[aj[j]]*bs;
1767       for (k=0; k<bs; k++) {
1768         ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
1769         col++;
1770         a += bs;
1771       }
1772     }
1773   }
1774   ierr = PetscFree(rvals);CHKERRQ(ierr);
1775   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1776   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1777 
1778   if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B;
1779   else {
1780     ierr = MatHeaderMerge(A,B);CHKERRQ(ierr);
1781   }
1782   PetscFunctionReturn(0);
1783 }
1784 
1785 #undef __FUNCT__
1786 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ"
1787 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr)
1788 {
1789   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
1790   Mat            a     = baij->A,b = baij->B;
1791   PetscErrorCode ierr;
1792   PetscInt       s1,s2,s3;
1793 
1794   PetscFunctionBegin;
1795   ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr);
1796   if (rr) {
1797     ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr);
1798     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
1799     /* Overlap communication with computation. */
1800     ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1801   }
1802   if (ll) {
1803     ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr);
1804     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
1805     ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr);
1806   }
1807   /* scale  the diagonal block */
1808   ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr);
1809 
1810   if (rr) {
1811     /* Do a scatter end and then right scale the off-diagonal block */
1812     ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1813     ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr);
1814   }
1815   PetscFunctionReturn(0);
1816 }
1817 
1818 #undef __FUNCT__
1819 #define __FUNCT__ "MatZeroRows_MPIBAIJ"
1820 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1821 {
1822   Mat_MPIBAIJ   *l      = (Mat_MPIBAIJ *) A->data;
1823   PetscInt      *owners = A->rmap->range;
1824   PetscInt       n      = A->rmap->n;
1825   PetscSF        sf;
1826   PetscInt      *lrows;
1827   PetscSFNode   *rrows;
1828   PetscInt       r, p = 0, len = 0;
1829   PetscErrorCode ierr;
1830 
1831   PetscFunctionBegin;
1832   /* Create SF where leaves are input rows and roots are owned rows */
1833   ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr);
1834   for (r = 0; r < n; ++r) lrows[r] = -1;
1835   if (!A->nooffproczerorows) {ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);}
1836   for (r = 0; r < N; ++r) {
1837     const PetscInt idx   = rows[r];
1838     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
1839     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
1840       ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr);
1841     }
1842     if (A->nooffproczerorows) {
1843       if (p != l->rank) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"MAT_NO_OFF_PROC_ZERO_ROWS set, but row %D is not owned by rank %d",idx,l->rank);
1844       lrows[len++] = idx - owners[p];
1845     } else {
1846       rrows[r].rank = p;
1847       rrows[r].index = rows[r] - owners[p];
1848     }
1849   }
1850   if (!A->nooffproczerorows) {
1851     ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr);
1852     ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr);
1853     /* Collect flags for rows to be zeroed */
1854     ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr);
1855     ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr);
1856     ierr = PetscSFDestroy(&sf);CHKERRQ(ierr);
1857     /* Compress and put in row numbers */
1858     for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
1859   }
1860   /* fix right hand side if needed */
1861   if (x && b) {
1862     const PetscScalar *xx;
1863     PetscScalar       *bb;
1864 
1865     ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr);
1866     ierr = VecGetArray(b,&bb);CHKERRQ(ierr);
1867     for (r = 0; r < len; ++r) bb[lrows[r]] = diag*xx[lrows[r]];
1868     ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr);
1869     ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr);
1870   }
1871 
1872   /* actually zap the local rows */
1873   /*
1874         Zero the required rows. If the "diagonal block" of the matrix
1875      is square and the user wishes to set the diagonal we use separate
1876      code so that MatSetValues() is not called for each diagonal allocating
1877      new memory, thus calling lots of mallocs and slowing things down.
1878 
1879   */
1880   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
1881   ierr = MatZeroRows_SeqBAIJ(l->B,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr);
1882   if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) {
1883     ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,diag,NULL,NULL);CHKERRQ(ierr);
1884   } else if (diag != 0.0) {
1885     ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,0,0);CHKERRQ(ierr);
1886     if (((Mat_SeqBAIJ*)l->A->data)->nonew) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatZeroRows() on rectangular matrices cannot be used with the Mat options \n\
1887        MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
1888     for (r = 0; r < len; ++r) {
1889       const PetscInt row = lrows[r] + A->rmap->rstart;
1890       ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr);
1891     }
1892     ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1893     ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1894   } else {
1895     ierr = MatZeroRows_SeqBAIJ(l->A,len,lrows,0.0,NULL,NULL);CHKERRQ(ierr);
1896   }
1897   ierr = PetscFree(lrows);CHKERRQ(ierr);
1898 
1899   /* only change matrix nonzero state if pattern was allowed to be changed */
1900   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
1901     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1902     ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
1903   }
1904   PetscFunctionReturn(0);
1905 }
1906 
1907 #undef __FUNCT__
1908 #define __FUNCT__ "MatZeroRowsColumns_MPIBAIJ"
1909 PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1910 {
1911   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ*)A->data;
1912   PetscErrorCode    ierr;
1913   PetscMPIInt       n = A->rmap->n;
1914   PetscInt          i,j,k,r,p = 0,len = 0,row,col,count;
1915   PetscInt          *lrows,*owners = A->rmap->range;
1916   PetscSFNode       *rrows;
1917   PetscSF           sf;
1918   const PetscScalar *xx;
1919   PetscScalar       *bb,*mask;
1920   Vec               xmask,lmask;
1921   Mat_SeqBAIJ       *baij = (Mat_SeqBAIJ*)l->B->data;
1922   PetscInt           bs = A->rmap->bs, bs2 = baij->bs2;
1923   PetscScalar       *aa;
1924 
1925   PetscFunctionBegin;
1926   /* Create SF where leaves are input rows and roots are owned rows */
1927   ierr = PetscMalloc1(n, &lrows);CHKERRQ(ierr);
1928   for (r = 0; r < n; ++r) lrows[r] = -1;
1929   ierr = PetscMalloc1(N, &rrows);CHKERRQ(ierr);
1930   for (r = 0; r < N; ++r) {
1931     const PetscInt idx   = rows[r];
1932     if (idx < 0 || A->rmap->N <= idx) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range [0,%D)",idx,A->rmap->N);
1933     if (idx < owners[p] || owners[p+1] <= idx) { /* short-circuit the search if the last p owns this row too */
1934       ierr = PetscLayoutFindOwner(A->rmap,idx,&p);CHKERRQ(ierr);
1935     }
1936     rrows[r].rank  = p;
1937     rrows[r].index = rows[r] - owners[p];
1938   }
1939   ierr = PetscSFCreate(PetscObjectComm((PetscObject) A), &sf);CHKERRQ(ierr);
1940   ierr = PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER);CHKERRQ(ierr);
1941   /* Collect flags for rows to be zeroed */
1942   ierr = PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr);
1943   ierr = PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *) rows, lrows, MPI_LOR);CHKERRQ(ierr);
1944   ierr = PetscSFDestroy(&sf);CHKERRQ(ierr);
1945   /* Compress and put in row numbers */
1946   for (r = 0; r < n; ++r) if (lrows[r] >= 0) lrows[len++] = r;
1947   /* zero diagonal part of matrix */
1948   ierr = MatZeroRowsColumns(l->A,len,lrows,diag,x,b);CHKERRQ(ierr);
1949   /* handle off diagonal part of matrix */
1950   ierr = MatCreateVecs(A,&xmask,NULL);CHKERRQ(ierr);
1951   ierr = VecDuplicate(l->lvec,&lmask);CHKERRQ(ierr);
1952   ierr = VecGetArray(xmask,&bb);CHKERRQ(ierr);
1953   for (i=0; i<len; i++) bb[lrows[i]] = 1;
1954   ierr = VecRestoreArray(xmask,&bb);CHKERRQ(ierr);
1955   ierr = VecScatterBegin(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1956   ierr = VecScatterEnd(l->Mvctx,xmask,lmask,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1957   ierr = VecDestroy(&xmask);CHKERRQ(ierr);
1958   if (x) {
1959     ierr = VecScatterBegin(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1960     ierr = VecScatterEnd(l->Mvctx,x,l->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1961     ierr = VecGetArrayRead(l->lvec,&xx);CHKERRQ(ierr);
1962     ierr = VecGetArray(b,&bb);CHKERRQ(ierr);
1963   }
1964   ierr = VecGetArray(lmask,&mask);CHKERRQ(ierr);
1965   /* remove zeroed rows of off diagonal matrix */
1966   for (i = 0; i < len; ++i) {
1967     row   = lrows[i];
1968     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
1969     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
1970     for (k = 0; k < count; ++k) {
1971       aa[0] = 0.0;
1972       aa   += bs;
1973     }
1974   }
1975   /* loop over all elements of off process part of matrix zeroing removed columns*/
1976   for (i = 0; i < l->B->rmap->N; ++i) {
1977     row = i/bs;
1978     for (j = baij->i[row]; j < baij->i[row+1]; ++j) {
1979       for (k = 0; k < bs; ++k) {
1980         col = bs*baij->j[j] + k;
1981         if (PetscAbsScalar(mask[col])) {
1982           aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
1983           if (b) bb[i] -= aa[0]*xx[col];
1984           aa[0] = 0.0;
1985         }
1986       }
1987     }
1988   }
1989   if (x) {
1990     ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr);
1991     ierr = VecRestoreArrayRead(l->lvec,&xx);CHKERRQ(ierr);
1992   }
1993   ierr = VecRestoreArray(lmask,&mask);CHKERRQ(ierr);
1994   ierr = VecDestroy(&lmask);CHKERRQ(ierr);
1995   ierr = PetscFree(lrows);CHKERRQ(ierr);
1996 
1997   /* only change matrix nonzero state if pattern was allowed to be changed */
1998   if (!((Mat_SeqBAIJ*)(l->A->data))->keepnonzeropattern) {
1999     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
2000     ierr = MPI_Allreduce(&state,&A->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2001   }
2002   PetscFunctionReturn(0);
2003 }
2004 
2005 #undef __FUNCT__
2006 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ"
2007 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
2008 {
2009   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2010   PetscErrorCode ierr;
2011 
2012   PetscFunctionBegin;
2013   ierr = MatSetUnfactored(a->A);CHKERRQ(ierr);
2014   PetscFunctionReturn(0);
2015 }
2016 
2017 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*);
2018 
2019 #undef __FUNCT__
2020 #define __FUNCT__ "MatEqual_MPIBAIJ"
2021 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool  *flag)
2022 {
2023   Mat_MPIBAIJ    *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
2024   Mat            a,b,c,d;
2025   PetscBool      flg;
2026   PetscErrorCode ierr;
2027 
2028   PetscFunctionBegin;
2029   a = matA->A; b = matA->B;
2030   c = matB->A; d = matB->B;
2031 
2032   ierr = MatEqual(a,c,&flg);CHKERRQ(ierr);
2033   if (flg) {
2034     ierr = MatEqual(b,d,&flg);CHKERRQ(ierr);
2035   }
2036   ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2037   PetscFunctionReturn(0);
2038 }
2039 
2040 #undef __FUNCT__
2041 #define __FUNCT__ "MatCopy_MPIBAIJ"
2042 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str)
2043 {
2044   PetscErrorCode ierr;
2045   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2046   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
2047 
2048   PetscFunctionBegin;
2049   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
2050   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
2051     ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr);
2052   } else {
2053     ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr);
2054     ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr);
2055   }
2056   PetscFunctionReturn(0);
2057 }
2058 
2059 #undef __FUNCT__
2060 #define __FUNCT__ "MatSetUp_MPIBAIJ"
2061 PetscErrorCode MatSetUp_MPIBAIJ(Mat A)
2062 {
2063   PetscErrorCode ierr;
2064 
2065   PetscFunctionBegin;
2066   ierr = MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr);
2067   PetscFunctionReturn(0);
2068 }
2069 
2070 #undef __FUNCT__
2071 #define __FUNCT__ "MatAXPYGetPreallocation_MPIBAIJ"
2072 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y,const PetscInt *yltog,Mat X,const PetscInt *xltog,PetscInt *nnz)
2073 {
2074   PetscErrorCode ierr;
2075   PetscInt       bs = Y->rmap->bs,m = Y->rmap->N/bs;
2076   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
2077   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;
2078 
2079   PetscFunctionBegin;
2080   ierr = MatAXPYGetPreallocation_MPIX_private(m,x->i,x->j,xltog,y->i,y->j,yltog,nnz);CHKERRQ(ierr);
2081   PetscFunctionReturn(0);
2082 }
2083 
2084 #undef __FUNCT__
2085 #define __FUNCT__ "MatAXPY_MPIBAIJ"
2086 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2087 {
2088   PetscErrorCode ierr;
2089   Mat_MPIBAIJ    *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data;
2090   PetscBLASInt   bnz,one=1;
2091   Mat_SeqBAIJ    *x,*y;
2092 
2093   PetscFunctionBegin;
2094   if (str == SAME_NONZERO_PATTERN) {
2095     PetscScalar alpha = a;
2096     x    = (Mat_SeqBAIJ*)xx->A->data;
2097     y    = (Mat_SeqBAIJ*)yy->A->data;
2098     ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr);
2099     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2100     x    = (Mat_SeqBAIJ*)xx->B->data;
2101     y    = (Mat_SeqBAIJ*)yy->B->data;
2102     ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr);
2103     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2104     ierr = PetscObjectStateIncrease((PetscObject)Y);CHKERRQ(ierr);
2105   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2106     ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr);
2107   } else {
2108     Mat      B;
2109     PetscInt *nnz_d,*nnz_o,bs=Y->rmap->bs;
2110     ierr = PetscMalloc1(yy->A->rmap->N,&nnz_d);CHKERRQ(ierr);
2111     ierr = PetscMalloc1(yy->B->rmap->N,&nnz_o);CHKERRQ(ierr);
2112     ierr = MatCreate(PetscObjectComm((PetscObject)Y),&B);CHKERRQ(ierr);
2113     ierr = PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);CHKERRQ(ierr);
2114     ierr = MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);CHKERRQ(ierr);
2115     ierr = MatSetBlockSizesFromMats(B,Y,Y);CHKERRQ(ierr);
2116     ierr = MatSetType(B,MATMPIBAIJ);CHKERRQ(ierr);
2117     ierr = MatAXPYGetPreallocation_SeqBAIJ(yy->A,xx->A,nnz_d);CHKERRQ(ierr);
2118     ierr = MatAXPYGetPreallocation_MPIBAIJ(yy->B,yy->garray,xx->B,xx->garray,nnz_o);CHKERRQ(ierr);
2119     ierr = MatMPIBAIJSetPreallocation(B,bs,0,nnz_d,0,nnz_o);CHKERRQ(ierr);
2120     /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */
2121     ierr = MatAXPY_BasicWithPreallocation(B,Y,a,X,str);CHKERRQ(ierr);
2122     ierr = MatHeaderReplace(Y,B);CHKERRQ(ierr);
2123     ierr = PetscFree(nnz_d);CHKERRQ(ierr);
2124     ierr = PetscFree(nnz_o);CHKERRQ(ierr);
2125   }
2126   PetscFunctionReturn(0);
2127 }
2128 
2129 #undef __FUNCT__
2130 #define __FUNCT__ "MatRealPart_MPIBAIJ"
2131 PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
2132 {
2133   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2134   PetscErrorCode ierr;
2135 
2136   PetscFunctionBegin;
2137   ierr = MatRealPart(a->A);CHKERRQ(ierr);
2138   ierr = MatRealPart(a->B);CHKERRQ(ierr);
2139   PetscFunctionReturn(0);
2140 }
2141 
2142 #undef __FUNCT__
2143 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ"
2144 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
2145 {
2146   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2147   PetscErrorCode ierr;
2148 
2149   PetscFunctionBegin;
2150   ierr = MatImaginaryPart(a->A);CHKERRQ(ierr);
2151   ierr = MatImaginaryPart(a->B);CHKERRQ(ierr);
2152   PetscFunctionReturn(0);
2153 }
2154 
2155 #undef __FUNCT__
2156 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ"
2157 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
2158 {
2159   PetscErrorCode ierr;
2160   IS             iscol_local;
2161   PetscInt       csize;
2162 
2163   PetscFunctionBegin;
2164   ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr);
2165   if (call == MAT_REUSE_MATRIX) {
2166     ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr);
2167     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2168   } else {
2169     ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr);
2170   }
2171   ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr);
2172   if (call == MAT_INITIAL_MATRIX) {
2173     ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr);
2174     ierr = ISDestroy(&iscol_local);CHKERRQ(ierr);
2175   }
2176   PetscFunctionReturn(0);
2177 }
2178 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*);
2179 #undef __FUNCT__
2180 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private"
2181 /*
2182   Not great since it makes two copies of the submatrix, first an SeqBAIJ
2183   in local and then by concatenating the local matrices the end result.
2184   Writing it directly would be much like MatGetSubMatrices_MPIBAIJ().
2185   This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency).
2186 */
2187 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
2188 {
2189   PetscErrorCode ierr;
2190   PetscMPIInt    rank,size;
2191   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs;
2192   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow;
2193   Mat            M,Mreuse;
2194   MatScalar      *vwork,*aa;
2195   MPI_Comm       comm;
2196   IS             isrow_new, iscol_new;
2197   PetscBool      idflag,allrows, allcols;
2198   Mat_SeqBAIJ    *aij;
2199 
2200   PetscFunctionBegin;
2201   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
2202   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
2203   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
2204   /* The compression and expansion should be avoided. Doesn't point
2205      out errors, might change the indices, hence buggey */
2206   ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr);
2207   ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr);
2208 
2209   /* Check for special case: each processor gets entire matrix columns */
2210   ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr);
2211   ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr);
2212   if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE;
2213   else allcols = PETSC_FALSE;
2214 
2215   ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr);
2216   ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr);
2217   if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE;
2218   else allrows = PETSC_FALSE;
2219 
2220   if (call ==  MAT_REUSE_MATRIX) {
2221     ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr);
2222     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2223     ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr);
2224   } else {
2225     ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr);
2226   }
2227   ierr = ISDestroy(&isrow_new);CHKERRQ(ierr);
2228   ierr = ISDestroy(&iscol_new);CHKERRQ(ierr);
2229   /*
2230       m - number of local rows
2231       n - number of columns (same on all processors)
2232       rstart - first row in new global matrix generated
2233   */
2234   ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr);
2235   ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr);
2236   m    = m/bs;
2237   n    = n/bs;
2238 
2239   if (call == MAT_INITIAL_MATRIX) {
2240     aij = (Mat_SeqBAIJ*)(Mreuse)->data;
2241     ii  = aij->i;
2242     jj  = aij->j;
2243 
2244     /*
2245         Determine the number of non-zeros in the diagonal and off-diagonal
2246         portions of the matrix in order to do correct preallocation
2247     */
2248 
2249     /* first get start and end of "diagonal" columns */
2250     if (csize == PETSC_DECIDE) {
2251       ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr);
2252       if (mglobal == n*bs) { /* square matrix */
2253         nlocal = m;
2254       } else {
2255         nlocal = n/size + ((n % size) > rank);
2256       }
2257     } else {
2258       nlocal = csize/bs;
2259     }
2260     ierr   = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr);
2261     rstart = rend - nlocal;
2262     if (rank == size - 1 && rend != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Local column sizes %D do not add up to total number of columns %D",rend,n);
2263 
2264     /* next, compute all the lengths */
2265     ierr  = PetscMalloc2(m+1,&dlens,m+1,&olens);CHKERRQ(ierr);
2266     for (i=0; i<m; i++) {
2267       jend = ii[i+1] - ii[i];
2268       olen = 0;
2269       dlen = 0;
2270       for (j=0; j<jend; j++) {
2271         if (*jj < rstart || *jj >= rend) olen++;
2272         else dlen++;
2273         jj++;
2274       }
2275       olens[i] = olen;
2276       dlens[i] = dlen;
2277     }
2278     ierr = MatCreate(comm,&M);CHKERRQ(ierr);
2279     ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr);
2280     ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr);
2281     ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr);
2282     ierr = MatMPISBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr);
2283     ierr = PetscFree2(dlens,olens);CHKERRQ(ierr);
2284   } else {
2285     PetscInt ml,nl;
2286 
2287     M    = *newmat;
2288     ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr);
2289     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
2290     ierr = MatZeroEntries(M);CHKERRQ(ierr);
2291     /*
2292          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
2293        rather than the slower MatSetValues().
2294     */
2295     M->was_assembled = PETSC_TRUE;
2296     M->assembled     = PETSC_FALSE;
2297   }
2298   ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr);
2299   ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr);
2300   aij  = (Mat_SeqBAIJ*)(Mreuse)->data;
2301   ii   = aij->i;
2302   jj   = aij->j;
2303   aa   = aij->a;
2304   for (i=0; i<m; i++) {
2305     row   = rstart/bs + i;
2306     nz    = ii[i+1] - ii[i];
2307     cwork = jj;     jj += nz;
2308     vwork = aa;     aa += nz*bs*bs;
2309     ierr  = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr);
2310   }
2311 
2312   ierr    = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2313   ierr    = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2314   *newmat = M;
2315 
2316   /* save submatrix used in processor for next request */
2317   if (call ==  MAT_INITIAL_MATRIX) {
2318     ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr);
2319     ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr);
2320   }
2321   PetscFunctionReturn(0);
2322 }
2323 
2324 #undef __FUNCT__
2325 #define __FUNCT__ "MatPermute_MPIBAIJ"
2326 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B)
2327 {
2328   MPI_Comm       comm,pcomm;
2329   PetscInt       clocal_size,nrows;
2330   const PetscInt *rows;
2331   PetscMPIInt    size;
2332   IS             crowp,lcolp;
2333   PetscErrorCode ierr;
2334 
2335   PetscFunctionBegin;
2336   ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr);
2337   /* make a collective version of 'rowp' */
2338   ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr);
2339   if (pcomm==comm) {
2340     crowp = rowp;
2341   } else {
2342     ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr);
2343     ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr);
2344     ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr);
2345     ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr);
2346   }
2347   ierr = ISSetPermutation(crowp);CHKERRQ(ierr);
2348   /* make a local version of 'colp' */
2349   ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr);
2350   ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr);
2351   if (size==1) {
2352     lcolp = colp;
2353   } else {
2354     ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr);
2355   }
2356   ierr = ISSetPermutation(lcolp);CHKERRQ(ierr);
2357   /* now we just get the submatrix */
2358   ierr = MatGetLocalSize(A,NULL,&clocal_size);CHKERRQ(ierr);
2359   ierr = MatGetSubMatrix_MPIBAIJ_Private(A,crowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr);
2360   /* clean up */
2361   if (pcomm!=comm) {
2362     ierr = ISDestroy(&crowp);CHKERRQ(ierr);
2363   }
2364   if (size>1) {
2365     ierr = ISDestroy(&lcolp);CHKERRQ(ierr);
2366   }
2367   PetscFunctionReturn(0);
2368 }
2369 
2370 #undef __FUNCT__
2371 #define __FUNCT__ "MatGetGhosts_MPIBAIJ"
2372 PetscErrorCode  MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
2373 {
2374   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data;
2375   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ*)baij->B->data;
2376 
2377   PetscFunctionBegin;
2378   if (nghosts) *nghosts = B->nbs;
2379   if (ghosts) *ghosts = baij->garray;
2380   PetscFunctionReturn(0);
2381 }
2382 
2383 #undef __FUNCT__
2384 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ"
2385 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
2386 {
2387   Mat            B;
2388   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
2389   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
2390   Mat_SeqAIJ     *b;
2391   PetscErrorCode ierr;
2392   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
2393   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
2394   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;
2395 
2396   PetscFunctionBegin;
2397   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr);
2398   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr);
2399 
2400   /* ----------------------------------------------------------------
2401      Tell every processor the number of nonzeros per row
2402   */
2403   ierr = PetscMalloc1(A->rmap->N/bs,&lens);CHKERRQ(ierr);
2404   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
2405     lens[i] = ad->i[i-A->rmap->rstart/bs+1] - ad->i[i-A->rmap->rstart/bs] + bd->i[i-A->rmap->rstart/bs+1] - bd->i[i-A->rmap->rstart/bs];
2406   }
2407   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
2408   ierr      = PetscMalloc1(2*size,&recvcounts);CHKERRQ(ierr);
2409   displs    = recvcounts + size;
2410   for (i=0; i<size; i++) {
2411     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
2412     displs[i]     = A->rmap->range[i]/bs;
2413   }
2414 #if defined(PETSC_HAVE_MPI_IN_PLACE)
2415   ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2416 #else
2417   ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2418 #endif
2419   /* ---------------------------------------------------------------
2420      Create the sequential matrix of the same type as the local block diagonal
2421   */
2422   ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr);
2423   ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr);
2424   ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr);
2425   ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr);
2426   b    = (Mat_SeqAIJ*)B->data;
2427 
2428   /*--------------------------------------------------------------------
2429     Copy my part of matrix column indices over
2430   */
2431   sendcount  = ad->nz + bd->nz;
2432   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
2433   a_jsendbuf = ad->j;
2434   b_jsendbuf = bd->j;
2435   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
2436   cnt        = 0;
2437   for (i=0; i<n; i++) {
2438 
2439     /* put in lower diagonal portion */
2440     m = bd->i[i+1] - bd->i[i];
2441     while (m > 0) {
2442       /* is it above diagonal (in bd (compressed) numbering) */
2443       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
2444       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2445       m--;
2446     }
2447 
2448     /* put in diagonal portion */
2449     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
2450       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
2451     }
2452 
2453     /* put in upper diagonal portion */
2454     while (m-- > 0) {
2455       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2456     }
2457   }
2458   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);
2459 
2460   /*--------------------------------------------------------------------
2461     Gather all column indices to all processors
2462   */
2463   for (i=0; i<size; i++) {
2464     recvcounts[i] = 0;
2465     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
2466       recvcounts[i] += lens[j];
2467     }
2468   }
2469   displs[0] = 0;
2470   for (i=1; i<size; i++) {
2471     displs[i] = displs[i-1] + recvcounts[i-1];
2472   }
2473 #if defined(PETSC_HAVE_MPI_IN_PLACE)
2474   ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2475 #else
2476   ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2477 #endif
2478   /*--------------------------------------------------------------------
2479     Assemble the matrix into useable form (note numerical values not yet set)
2480   */
2481   /* set the b->ilen (length of each row) values */
2482   ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr);
2483   /* set the b->i indices */
2484   b->i[0] = 0;
2485   for (i=1; i<=A->rmap->N/bs; i++) {
2486     b->i[i] = b->i[i-1] + lens[i-1];
2487   }
2488   ierr = PetscFree(lens);CHKERRQ(ierr);
2489   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2490   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2491   ierr = PetscFree(recvcounts);CHKERRQ(ierr);
2492 
2493   if (A->symmetric) {
2494     ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
2495   } else if (A->hermitian) {
2496     ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr);
2497   } else if (A->structurally_symmetric) {
2498     ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
2499   }
2500   *newmat = B;
2501   PetscFunctionReturn(0);
2502 }
2503 
2504 #undef __FUNCT__
2505 #define __FUNCT__ "MatSOR_MPIBAIJ"
2506 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2507 {
2508   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
2509   PetscErrorCode ierr;
2510   Vec            bb1 = 0;
2511 
2512   PetscFunctionBegin;
2513   if (flag == SOR_APPLY_UPPER) {
2514     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2515     PetscFunctionReturn(0);
2516   }
2517 
2518   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
2519     ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr);
2520   }
2521 
2522   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2523     if (flag & SOR_ZERO_INITIAL_GUESS) {
2524       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2525       its--;
2526     }
2527 
2528     while (its--) {
2529       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2530       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2531 
2532       /* update rhs: bb1 = bb - B*x */
2533       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2534       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2535 
2536       /* local sweep */
2537       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2538     }
2539   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
2540     if (flag & SOR_ZERO_INITIAL_GUESS) {
2541       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2542       its--;
2543     }
2544     while (its--) {
2545       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2546       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2547 
2548       /* update rhs: bb1 = bb - B*x */
2549       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2550       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2551 
2552       /* local sweep */
2553       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2554     }
2555   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
2556     if (flag & SOR_ZERO_INITIAL_GUESS) {
2557       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2558       its--;
2559     }
2560     while (its--) {
2561       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2562       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2563 
2564       /* update rhs: bb1 = bb - B*x */
2565       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2566       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2567 
2568       /* local sweep */
2569       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2570     }
2571   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");
2572 
2573   ierr = VecDestroy(&bb1);CHKERRQ(ierr);
2574   PetscFunctionReturn(0);
2575 }
2576 
2577 #undef __FUNCT__
2578 #define __FUNCT__ "MatGetColumnNorms_MPIBAIJ"
2579 PetscErrorCode MatGetColumnNorms_MPIBAIJ(Mat A,NormType type,PetscReal *norms)
2580 {
2581   PetscErrorCode ierr;
2582   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)A->data;
2583   PetscInt       N,i,*garray = aij->garray;
2584   PetscInt       ib,jb,bs = A->rmap->bs;
2585   Mat_SeqBAIJ    *a_aij = (Mat_SeqBAIJ*) aij->A->data;
2586   MatScalar      *a_val = a_aij->a;
2587   Mat_SeqBAIJ    *b_aij = (Mat_SeqBAIJ*) aij->B->data;
2588   MatScalar      *b_val = b_aij->a;
2589   PetscReal      *work;
2590 
2591   PetscFunctionBegin;
2592   ierr = MatGetSize(A,NULL,&N);CHKERRQ(ierr);
2593   ierr = PetscCalloc1(N,&work);CHKERRQ(ierr);
2594   if (type == NORM_2) {
2595     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
2596       for (jb=0; jb<bs; jb++) {
2597         for (ib=0; ib<bs; ib++) {
2598           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val);
2599           a_val++;
2600         }
2601       }
2602     }
2603     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
2604       for (jb=0; jb<bs; jb++) {
2605         for (ib=0; ib<bs; ib++) {
2606           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val);
2607           b_val++;
2608         }
2609       }
2610     }
2611   } else if (type == NORM_1) {
2612     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
2613       for (jb=0; jb<bs; jb++) {
2614         for (ib=0; ib<bs; ib++) {
2615           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val);
2616           a_val++;
2617         }
2618       }
2619     }
2620     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
2621       for (jb=0; jb<bs; jb++) {
2622        for (ib=0; ib<bs; ib++) {
2623           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val);
2624           b_val++;
2625         }
2626       }
2627     }
2628   } else if (type == NORM_INFINITY) {
2629     for (i=a_aij->i[0]; i<a_aij->i[aij->A->rmap->n/bs]; i++) {
2630       for (jb=0; jb<bs; jb++) {
2631         for (ib=0; ib<bs; ib++) {
2632           int col = A->cmap->rstart + a_aij->j[i] * bs + jb;
2633           work[col] = PetscMax(PetscAbsScalar(*a_val), work[col]);
2634           a_val++;
2635         }
2636       }
2637     }
2638     for (i=b_aij->i[0]; i<b_aij->i[aij->B->rmap->n/bs]; i++) {
2639       for (jb=0; jb<bs; jb++) {
2640         for (ib=0; ib<bs; ib++) {
2641           int col = garray[b_aij->j[i]] * bs + jb;
2642           work[col] = PetscMax(PetscAbsScalar(*b_val), work[col]);
2643           b_val++;
2644         }
2645       }
2646     }
2647   } else SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Unknown NormType");
2648   if (type == NORM_INFINITY) {
2649     ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2650   } else {
2651     ierr = MPI_Allreduce(work,norms,N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2652   }
2653   ierr = PetscFree(work);CHKERRQ(ierr);
2654   if (type == NORM_2) {
2655     for (i=0; i<N; i++) norms[i] = PetscSqrtReal(norms[i]);
2656   }
2657   PetscFunctionReturn(0);
2658 }
2659 
2660 #undef __FUNCT__
2661 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ"
2662 PetscErrorCode  MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
2663 {
2664   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;
2665   PetscErrorCode ierr;
2666 
2667   PetscFunctionBegin;
2668   ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr);
2669   PetscFunctionReturn(0);
2670 }
2671 
2672 #undef __FUNCT__
2673 #define __FUNCT__ "MatShift_MPIBAIJ"
2674 PetscErrorCode MatShift_MPIBAIJ(Mat Y,PetscScalar a)
2675 {
2676   PetscErrorCode ierr;
2677   Mat_MPIBAIJ    *maij = (Mat_MPIBAIJ*)Y->data;
2678   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)maij->A->data;
2679 
2680   PetscFunctionBegin;
2681   if (!Y->preallocated) {
2682     ierr = MatMPIBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL,0,NULL);CHKERRQ(ierr);
2683   } else if (!aij->nz) {
2684     ierr = MatSeqBAIJSetPreallocation(maij->A,Y->rmap->bs,1,NULL);CHKERRQ(ierr);
2685   }
2686   ierr = MatShift_Basic(Y,a);CHKERRQ(ierr);
2687   PetscFunctionReturn(0);
2688 }
2689 
2690 /* -------------------------------------------------------------------*/
2691 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
2692                                        MatGetRow_MPIBAIJ,
2693                                        MatRestoreRow_MPIBAIJ,
2694                                        MatMult_MPIBAIJ,
2695                                 /* 4*/ MatMultAdd_MPIBAIJ,
2696                                        MatMultTranspose_MPIBAIJ,
2697                                        MatMultTransposeAdd_MPIBAIJ,
2698                                        0,
2699                                        0,
2700                                        0,
2701                                 /*10*/ 0,
2702                                        0,
2703                                        0,
2704                                        MatSOR_MPIBAIJ,
2705                                        MatTranspose_MPIBAIJ,
2706                                 /*15*/ MatGetInfo_MPIBAIJ,
2707                                        MatEqual_MPIBAIJ,
2708                                        MatGetDiagonal_MPIBAIJ,
2709                                        MatDiagonalScale_MPIBAIJ,
2710                                        MatNorm_MPIBAIJ,
2711                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
2712                                        MatAssemblyEnd_MPIBAIJ,
2713                                        MatSetOption_MPIBAIJ,
2714                                        MatZeroEntries_MPIBAIJ,
2715                                 /*24*/ MatZeroRows_MPIBAIJ,
2716                                        0,
2717                                        0,
2718                                        0,
2719                                        0,
2720                                 /*29*/ MatSetUp_MPIBAIJ,
2721                                        0,
2722                                        0,
2723                                        0,
2724                                        0,
2725                                 /*34*/ MatDuplicate_MPIBAIJ,
2726                                        0,
2727                                        0,
2728                                        0,
2729                                        0,
2730                                 /*39*/ MatAXPY_MPIBAIJ,
2731                                        MatGetSubMatrices_MPIBAIJ,
2732                                        MatIncreaseOverlap_MPIBAIJ,
2733                                        MatGetValues_MPIBAIJ,
2734                                        MatCopy_MPIBAIJ,
2735                                 /*44*/ 0,
2736                                        MatScale_MPIBAIJ,
2737                                        MatShift_MPIBAIJ,
2738                                        0,
2739                                        MatZeroRowsColumns_MPIBAIJ,
2740                                 /*49*/ 0,
2741                                        0,
2742                                        0,
2743                                        0,
2744                                        0,
2745                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2746                                        0,
2747                                        MatSetUnfactored_MPIBAIJ,
2748                                        MatPermute_MPIBAIJ,
2749                                        MatSetValuesBlocked_MPIBAIJ,
2750                                 /*59*/ MatGetSubMatrix_MPIBAIJ,
2751                                        MatDestroy_MPIBAIJ,
2752                                        MatView_MPIBAIJ,
2753                                        0,
2754                                        0,
2755                                 /*64*/ 0,
2756                                        0,
2757                                        0,
2758                                        0,
2759                                        0,
2760                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
2761                                        0,
2762                                        0,
2763                                        0,
2764                                        0,
2765                                 /*74*/ 0,
2766                                        MatFDColoringApply_BAIJ,
2767                                        0,
2768                                        0,
2769                                        0,
2770                                 /*79*/ 0,
2771                                        0,
2772                                        0,
2773                                        0,
2774                                        MatLoad_MPIBAIJ,
2775                                 /*84*/ 0,
2776                                        0,
2777                                        0,
2778                                        0,
2779                                        0,
2780                                 /*89*/ 0,
2781                                        0,
2782                                        0,
2783                                        0,
2784                                        0,
2785                                 /*94*/ 0,
2786                                        0,
2787                                        0,
2788                                        0,
2789                                        0,
2790                                 /*99*/ 0,
2791                                        0,
2792                                        0,
2793                                        0,
2794                                        0,
2795                                 /*104*/0,
2796                                        MatRealPart_MPIBAIJ,
2797                                        MatImaginaryPart_MPIBAIJ,
2798                                        0,
2799                                        0,
2800                                 /*109*/0,
2801                                        0,
2802                                        0,
2803                                        0,
2804                                        0,
2805                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
2806                                        0,
2807                                        MatGetGhosts_MPIBAIJ,
2808                                        0,
2809                                        0,
2810                                 /*119*/0,
2811                                        0,
2812                                        0,
2813                                        0,
2814                                        MatGetMultiProcBlock_MPIBAIJ,
2815                                 /*124*/0,
2816                                        MatGetColumnNorms_MPIBAIJ,
2817                                        MatInvertBlockDiagonal_MPIBAIJ,
2818                                        0,
2819                                        0,
2820                                /*129*/ 0,
2821                                        0,
2822                                        0,
2823                                        0,
2824                                        0,
2825                                /*134*/ 0,
2826                                        0,
2827                                        0,
2828                                        0,
2829                                        0,
2830                                /*139*/ 0,
2831                                        0,
2832                                        0,
2833                                        MatFDColoringSetUp_MPIXAIJ,
2834                                        0,
2835                                 /*144*/MatCreateMPIMatConcatenateSeqMat_MPIBAIJ
2836 };
2837 
2838 #undef __FUNCT__
2839 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ"
2840 PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
2841 {
2842   PetscFunctionBegin;
2843   *a = ((Mat_MPIBAIJ*)A->data)->A;
2844   PetscFunctionReturn(0);
2845 }
2846 
2847 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*);
2848 
2849 #undef __FUNCT__
2850 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ"
2851 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2852 {
2853   PetscInt       m,rstart,cstart,cend;
2854   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2855   const PetscInt *JJ    =0;
2856   PetscScalar    *values=0;
2857   PetscBool      roworiented = ((Mat_MPIBAIJ*)B->data)->roworiented;
2858   PetscErrorCode ierr;
2859 
2860   PetscFunctionBegin;
2861   ierr   = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr);
2862   ierr   = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr);
2863   ierr   = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
2864   ierr   = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
2865   ierr   = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
2866   m      = B->rmap->n/bs;
2867   rstart = B->rmap->rstart/bs;
2868   cstart = B->cmap->rstart/bs;
2869   cend   = B->cmap->rend/bs;
2870 
2871   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2872   ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr);
2873   for (i=0; i<m; i++) {
2874     nz = ii[i+1] - ii[i];
2875     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2876     nz_max = PetscMax(nz_max,nz);
2877     JJ     = jj + ii[i];
2878     for (j=0; j<nz; j++) {
2879       if (*JJ >= cstart) break;
2880       JJ++;
2881     }
2882     d = 0;
2883     for (; j<nz; j++) {
2884       if (*JJ++ >= cend) break;
2885       d++;
2886     }
2887     d_nnz[i] = d;
2888     o_nnz[i] = nz - d;
2889   }
2890   ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr);
2891   ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr);
2892 
2893   values = (PetscScalar*)V;
2894   if (!values) {
2895     ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr);
2896     ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr);
2897   }
2898   for (i=0; i<m; i++) {
2899     PetscInt          row    = i + rstart;
2900     PetscInt          ncols  = ii[i+1] - ii[i];
2901     const PetscInt    *icols = jj + ii[i];
2902     if (!roworiented) {         /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2903       const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2904       ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr);
2905     } else {                    /* block ordering does not match so we can only insert one block at a time. */
2906       PetscInt j;
2907       for (j=0; j<ncols; j++) {
2908         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2909         ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,1,&icols[j],svals,INSERT_VALUES);CHKERRQ(ierr);
2910       }
2911     }
2912   }
2913 
2914   if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); }
2915   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2916   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2917   ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);
2918   PetscFunctionReturn(0);
2919 }
2920 
2921 #undef __FUNCT__
2922 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR"
2923 /*@C
2924    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2925    (the default parallel PETSc format).
2926 
2927    Collective on MPI_Comm
2928 
2929    Input Parameters:
2930 +  B - the matrix
2931 .  bs - the block size
2932 .  i - the indices into j for the start of each local row (starts with zero)
2933 .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2934 -  v - optional values in the matrix
2935 
2936    Level: developer
2937 
2938    Notes: The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
2939    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
2940    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
2941    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
2942    block column and the second index is over columns within a block.
2943 
2944 .keywords: matrix, aij, compressed row, sparse, parallel
2945 
2946 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ, MatCreateMPIBAIJWithArrays(), MPIBAIJ
2947 @*/
2948 PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2949 {
2950   PetscErrorCode ierr;
2951 
2952   PetscFunctionBegin;
2953   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
2954   PetscValidType(B,1);
2955   PetscValidLogicalCollectiveInt(B,bs,2);
2956   ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr);
2957   PetscFunctionReturn(0);
2958 }
2959 
2960 #undef __FUNCT__
2961 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ"
2962 PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2963 {
2964   Mat_MPIBAIJ    *b;
2965   PetscErrorCode ierr;
2966   PetscInt       i;
2967 
2968   PetscFunctionBegin;
2969   ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr);
2970   ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
2971   ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
2972   ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
2973 
2974   if (d_nnz) {
2975     for (i=0; i<B->rmap->n/bs; i++) {
2976       if (d_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"d_nnz cannot be less than -1: local row %D value %D",i,d_nnz[i]);
2977     }
2978   }
2979   if (o_nnz) {
2980     for (i=0; i<B->rmap->n/bs; i++) {
2981       if (o_nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"o_nnz cannot be less than -1: local row %D value %D",i,o_nnz[i]);
2982     }
2983   }
2984 
2985   b      = (Mat_MPIBAIJ*)B->data;
2986   b->bs2 = bs*bs;
2987   b->mbs = B->rmap->n/bs;
2988   b->nbs = B->cmap->n/bs;
2989   b->Mbs = B->rmap->N/bs;
2990   b->Nbs = B->cmap->N/bs;
2991 
2992   for (i=0; i<=b->size; i++) {
2993     b->rangebs[i] = B->rmap->range[i]/bs;
2994   }
2995   b->rstartbs = B->rmap->rstart/bs;
2996   b->rendbs   = B->rmap->rend/bs;
2997   b->cstartbs = B->cmap->rstart/bs;
2998   b->cendbs   = B->cmap->rend/bs;
2999 
3000   if (!B->preallocated) {
3001     ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr);
3002     ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr);
3003     ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr);
3004     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr);
3005     ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr);
3006     ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr);
3007     ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr);
3008     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr);
3009     ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr);
3010   }
3011 
3012   ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr);
3013   ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr);
3014   B->preallocated = PETSC_TRUE;
3015   PetscFunctionReturn(0);
3016 }
3017 
3018 extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
3019 extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);
3020 
3021 #undef __FUNCT__
3022 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj"
3023 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
3024 {
3025   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
3026   PetscErrorCode ierr;
3027   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
3028   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
3029   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;
3030 
3031   PetscFunctionBegin;
3032   ierr  = PetscMalloc1(M+1,&ii);CHKERRQ(ierr);
3033   ii[0] = 0;
3034   for (i=0; i<M; i++) {
3035     if ((id[i+1] - id[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,id[i],id[i+1]);
3036     if ((io[i+1] - io[i]) < 0) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Indices wrong %D %D %D",i,io[i],io[i+1]);
3037     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
3038     /* remove one from count of matrix has diagonal */
3039     for (j=id[i]; j<id[i+1]; j++) {
3040       if (jd[j] == i) {ii[i+1]--;break;}
3041     }
3042   }
3043   ierr = PetscMalloc1(ii[M],&jj);CHKERRQ(ierr);
3044   cnt  = 0;
3045   for (i=0; i<M; i++) {
3046     for (j=io[i]; j<io[i+1]; j++) {
3047       if (garray[jo[j]] > rstart) break;
3048       jj[cnt++] = garray[jo[j]];
3049     }
3050     for (k=id[i]; k<id[i+1]; k++) {
3051       if (jd[k] != i) {
3052         jj[cnt++] = rstart + jd[k];
3053       }
3054     }
3055     for (; j<io[i+1]; j++) {
3056       jj[cnt++] = garray[jo[j]];
3057     }
3058   }
3059   ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr);
3060   PetscFunctionReturn(0);
3061 }
3062 
3063 #include <../src/mat/impls/aij/mpi/mpiaij.h>
3064 
3065 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);
3066 
3067 #undef __FUNCT__
3068 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ"
3069 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
3070 {
3071   PetscErrorCode ierr;
3072   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
3073   Mat            B;
3074   Mat_MPIAIJ     *b;
3075 
3076   PetscFunctionBegin;
3077   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");
3078 
3079   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
3080   ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr);
3081   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
3082   ierr = MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);CHKERRQ(ierr);
3083   ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr);
3084   ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr);
3085   b    = (Mat_MPIAIJ*) B->data;
3086 
3087   ierr = MatDestroy(&b->A);CHKERRQ(ierr);
3088   ierr = MatDestroy(&b->B);CHKERRQ(ierr);
3089   ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr);
3090   ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr);
3091   ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr);
3092   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3093   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3094   ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3095   ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3096   if (reuse == MAT_REUSE_MATRIX) {
3097     ierr = MatHeaderReplace(A,B);CHKERRQ(ierr);
3098   } else {
3099    *newmat = B;
3100   }
3101   PetscFunctionReturn(0);
3102 }
3103 
3104 /*MC
3105    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.
3106 
3107    Options Database Keys:
3108 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
3109 . -mat_block_size <bs> - set the blocksize used to store the matrix
3110 - -mat_use_hash_table <fact>
3111 
3112   Level: beginner
3113 
3114 .seealso: MatCreateMPIBAIJ
3115 M*/
3116 
3117 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);
3118 
3119 #undef __FUNCT__
3120 #define __FUNCT__ "MatCreate_MPIBAIJ"
3121 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
3122 {
3123   Mat_MPIBAIJ    *b;
3124   PetscErrorCode ierr;
3125   PetscBool      flg = PETSC_FALSE;
3126 
3127   PetscFunctionBegin;
3128   ierr    = PetscNewLog(B,&b);CHKERRQ(ierr);
3129   B->data = (void*)b;
3130 
3131   ierr         = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr);
3132   B->assembled = PETSC_FALSE;
3133 
3134   B->insertmode = NOT_SET_VALUES;
3135   ierr          = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr);
3136   ierr          = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr);
3137 
3138   /* build local table of row and column ownerships */
3139   ierr = PetscMalloc1(b->size+1,&b->rangebs);CHKERRQ(ierr);
3140 
3141   /* build cache for off array entries formed */
3142   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr);
3143 
3144   b->donotstash  = PETSC_FALSE;
3145   b->colmap      = NULL;
3146   b->garray      = NULL;
3147   b->roworiented = PETSC_TRUE;
3148 
3149   /* stuff used in block assembly */
3150   b->barray = 0;
3151 
3152   /* stuff used for matrix vector multiply */
3153   b->lvec  = 0;
3154   b->Mvctx = 0;
3155 
3156   /* stuff for MatGetRow() */
3157   b->rowindices   = 0;
3158   b->rowvalues    = 0;
3159   b->getrowactive = PETSC_FALSE;
3160 
3161   /* hash table stuff */
3162   b->ht           = 0;
3163   b->hd           = 0;
3164   b->ht_size      = 0;
3165   b->ht_flag      = PETSC_FALSE;
3166   b->ht_fact      = 0;
3167   b->ht_total_ct  = 0;
3168   b->ht_insert_ct = 0;
3169 
3170   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
3171   b->ijonly = PETSC_FALSE;
3172 
3173 
3174   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr);
3175   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr);
3176   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr);
3177   ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr);
3178   ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr);
3179   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr);
3180   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr);
3181   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr);
3182   ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr);
3183   ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr);
3184   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr);
3185   ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr);
3186 
3187   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr);
3188   ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",flg,&flg,NULL);CHKERRQ(ierr);
3189   if (flg) {
3190     PetscReal fact = 1.39;
3191     ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr);
3192     ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr);
3193     if (fact <= 1.0) fact = 1.39;
3194     ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr);
3195     ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr);
3196   }
3197   ierr = PetscOptionsEnd();CHKERRQ(ierr);
3198   PetscFunctionReturn(0);
3199 }
3200 
3201 /*MC
3202    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.
3203 
3204    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
3205    and MATMPIBAIJ otherwise.
3206 
3207    Options Database Keys:
3208 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()
3209 
3210   Level: beginner
3211 
3212 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3213 M*/
3214 
3215 #undef __FUNCT__
3216 #define __FUNCT__ "MatMPIBAIJSetPreallocation"
3217 /*@C
3218    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
3219    (block compressed row).  For good matrix assembly performance
3220    the user should preallocate the matrix storage by setting the parameters
3221    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3222    performance can be increased by more than a factor of 50.
3223 
3224    Collective on Mat
3225 
3226    Input Parameters:
3227 +  B - the matrix
3228 .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
3229           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
3230 .  d_nz  - number of block nonzeros per block row in diagonal portion of local
3231            submatrix  (same for all local rows)
3232 .  d_nnz - array containing the number of block nonzeros in the various block rows
3233            of the in diagonal portion of the local (possibly different for each block
3234            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
3235            set it even if it is zero.
3236 .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
3237            submatrix (same for all local rows).
3238 -  o_nnz - array containing the number of nonzeros in the various block rows of the
3239            off-diagonal portion of the local submatrix (possibly different for
3240            each block row) or NULL.
3241 
3242    If the *_nnz parameter is given then the *_nz parameter is ignored
3243 
3244    Options Database Keys:
3245 +   -mat_block_size - size of the blocks to use
3246 -   -mat_use_hash_table <fact>
3247 
3248    Notes:
3249    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3250    than it must be used on all processors that share the object for that argument.
3251 
3252    Storage Information:
3253    For a square global matrix we define each processor's diagonal portion
3254    to be its local rows and the corresponding columns (a square submatrix);
3255    each processor's off-diagonal portion encompasses the remainder of the
3256    local matrix (a rectangular submatrix).
3257 
3258    The user can specify preallocated storage for the diagonal part of
3259    the local submatrix with either d_nz or d_nnz (not both).  Set
3260    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3261    memory allocation.  Likewise, specify preallocated storage for the
3262    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
3263 
3264    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3265    the figure below we depict these three local rows and all columns (0-11).
3266 
3267 .vb
3268            0 1 2 3 4 5 6 7 8 9 10 11
3269           --------------------------
3270    row 3  |o o o d d d o o o o  o  o
3271    row 4  |o o o d d d o o o o  o  o
3272    row 5  |o o o d d d o o o o  o  o
3273           --------------------------
3274 .ve
3275 
3276    Thus, any entries in the d locations are stored in the d (diagonal)
3277    submatrix, and any entries in the o locations are stored in the
3278    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3279    stored simply in the MATSEQBAIJ format for compressed row storage.
3280 
3281    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3282    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3283    In general, for PDE problems in which most nonzeros are near the diagonal,
3284    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3285    or you will get TERRIBLE performance; see the users' manual chapter on
3286    matrices.
3287 
3288    You can call MatGetInfo() to get information on how effective the preallocation was;
3289    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3290    You can also run with the option -info and look for messages with the string
3291    malloc in them to see if additional memory allocation was needed.
3292 
3293    Level: intermediate
3294 
3295 .keywords: matrix, block, aij, compressed row, sparse, parallel
3296 
3297 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
3298 @*/
3299 PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3300 {
3301   PetscErrorCode ierr;
3302 
3303   PetscFunctionBegin;
3304   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
3305   PetscValidType(B,1);
3306   PetscValidLogicalCollectiveInt(B,bs,2);
3307   ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr);
3308   PetscFunctionReturn(0);
3309 }
3310 
3311 #undef __FUNCT__
3312 #define __FUNCT__ "MatCreateBAIJ"
3313 /*@C
3314    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
3315    (block compressed row).  For good matrix assembly performance
3316    the user should preallocate the matrix storage by setting the parameters
3317    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3318    performance can be increased by more than a factor of 50.
3319 
3320    Collective on MPI_Comm
3321 
3322    Input Parameters:
3323 +  comm - MPI communicator
3324 .  bs   - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
3325           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
3326 .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3327            This value should be the same as the local size used in creating the
3328            y vector for the matrix-vector product y = Ax.
3329 .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
3330            This value should be the same as the local size used in creating the
3331            x vector for the matrix-vector product y = Ax.
3332 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3333 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3334 .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
3335            submatrix  (same for all local rows)
3336 .  d_nnz - array containing the number of nonzero blocks in the various block rows
3337            of the in diagonal portion of the local (possibly different for each block
3338            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
3339            and set it even if it is zero.
3340 .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
3341            submatrix (same for all local rows).
3342 -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
3343            off-diagonal portion of the local submatrix (possibly different for
3344            each block row) or NULL.
3345 
3346    Output Parameter:
3347 .  A - the matrix
3348 
3349    Options Database Keys:
3350 +   -mat_block_size - size of the blocks to use
3351 -   -mat_use_hash_table <fact>
3352 
3353    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3354    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3355    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
3356 
3357    Notes:
3358    If the *_nnz parameter is given then the *_nz parameter is ignored
3359 
3360    A nonzero block is any block that as 1 or more nonzeros in it
3361 
3362    The user MUST specify either the local or global matrix dimensions
3363    (possibly both).
3364 
3365    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3366    than it must be used on all processors that share the object for that argument.
3367 
3368    Storage Information:
3369    For a square global matrix we define each processor's diagonal portion
3370    to be its local rows and the corresponding columns (a square submatrix);
3371    each processor's off-diagonal portion encompasses the remainder of the
3372    local matrix (a rectangular submatrix).
3373 
3374    The user can specify preallocated storage for the diagonal part of
3375    the local submatrix with either d_nz or d_nnz (not both).  Set
3376    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3377    memory allocation.  Likewise, specify preallocated storage for the
3378    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
3379 
3380    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3381    the figure below we depict these three local rows and all columns (0-11).
3382 
3383 .vb
3384            0 1 2 3 4 5 6 7 8 9 10 11
3385           --------------------------
3386    row 3  |o o o d d d o o o o  o  o
3387    row 4  |o o o d d d o o o o  o  o
3388    row 5  |o o o d d d o o o o  o  o
3389           --------------------------
3390 .ve
3391 
3392    Thus, any entries in the d locations are stored in the d (diagonal)
3393    submatrix, and any entries in the o locations are stored in the
3394    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3395    stored simply in the MATSEQBAIJ format for compressed row storage.
3396 
3397    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3398    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3399    In general, for PDE problems in which most nonzeros are near the diagonal,
3400    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3401    or you will get TERRIBLE performance; see the users' manual chapter on
3402    matrices.
3403 
3404    Level: intermediate
3405 
3406 .keywords: matrix, block, aij, compressed row, sparse, parallel
3407 
3408 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3409 @*/
3410 PetscErrorCode  MatCreateBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[],Mat *A)
3411 {
3412   PetscErrorCode ierr;
3413   PetscMPIInt    size;
3414 
3415   PetscFunctionBegin;
3416   ierr = MatCreate(comm,A);CHKERRQ(ierr);
3417   ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr);
3418   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
3419   if (size > 1) {
3420     ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr);
3421     ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr);
3422   } else {
3423     ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr);
3424     ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr);
3425   }
3426   PetscFunctionReturn(0);
3427 }
3428 
3429 #undef __FUNCT__
3430 #define __FUNCT__ "MatDuplicate_MPIBAIJ"
3431 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
3432 {
3433   Mat            mat;
3434   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
3435   PetscErrorCode ierr;
3436   PetscInt       len=0;
3437 
3438   PetscFunctionBegin;
3439   *newmat = 0;
3440   ierr    = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr);
3441   ierr    = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr);
3442   ierr    = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr);
3443   ierr    = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr);
3444 
3445   mat->factortype   = matin->factortype;
3446   mat->preallocated = PETSC_TRUE;
3447   mat->assembled    = PETSC_TRUE;
3448   mat->insertmode   = NOT_SET_VALUES;
3449 
3450   a             = (Mat_MPIBAIJ*)mat->data;
3451   mat->rmap->bs = matin->rmap->bs;
3452   a->bs2        = oldmat->bs2;
3453   a->mbs        = oldmat->mbs;
3454   a->nbs        = oldmat->nbs;
3455   a->Mbs        = oldmat->Mbs;
3456   a->Nbs        = oldmat->Nbs;
3457 
3458   ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr);
3459   ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr);
3460 
3461   a->size         = oldmat->size;
3462   a->rank         = oldmat->rank;
3463   a->donotstash   = oldmat->donotstash;
3464   a->roworiented  = oldmat->roworiented;
3465   a->rowindices   = 0;
3466   a->rowvalues    = 0;
3467   a->getrowactive = PETSC_FALSE;
3468   a->barray       = 0;
3469   a->rstartbs     = oldmat->rstartbs;
3470   a->rendbs       = oldmat->rendbs;
3471   a->cstartbs     = oldmat->cstartbs;
3472   a->cendbs       = oldmat->cendbs;
3473 
3474   /* hash table stuff */
3475   a->ht           = 0;
3476   a->hd           = 0;
3477   a->ht_size      = 0;
3478   a->ht_flag      = oldmat->ht_flag;
3479   a->ht_fact      = oldmat->ht_fact;
3480   a->ht_total_ct  = 0;
3481   a->ht_insert_ct = 0;
3482 
3483   ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr);
3484   if (oldmat->colmap) {
3485 #if defined(PETSC_USE_CTABLE)
3486     ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr);
3487 #else
3488     ierr = PetscMalloc1(a->Nbs,&a->colmap);CHKERRQ(ierr);
3489     ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
3490     ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
3491 #endif
3492   } else a->colmap = 0;
3493 
3494   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
3495     ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr);
3496     ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr);
3497     ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr);
3498   } else a->garray = 0;
3499 
3500   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr);
3501   ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr);
3502   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr);
3503   ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr);
3504   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr);
3505 
3506   ierr    = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr);
3507   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr);
3508   ierr    = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr);
3509   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr);
3510   ierr    = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr);
3511   *newmat = mat;
3512   PetscFunctionReturn(0);
3513 }
3514 
3515 #undef __FUNCT__
3516 #define __FUNCT__ "MatLoad_MPIBAIJ"
3517 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
3518 {
3519   PetscErrorCode ierr;
3520   int            fd;
3521   PetscInt       i,nz,j,rstart,rend;
3522   PetscScalar    *vals,*buf;
3523   MPI_Comm       comm;
3524   MPI_Status     status;
3525   PetscMPIInt    rank,size,maxnz;
3526   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
3527   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
3528   PetscInt       jj,*mycols,*ibuf,bs = newmat->rmap->bs,Mbs,mbs,extra_rows,mmax;
3529   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
3530   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
3531   PetscInt       dcount,kmax,k,nzcount,tmp,mend;
3532 
3533   PetscFunctionBegin;
3534   /* force binary viewer to load .info file if it has not yet done so */
3535   ierr = PetscViewerSetUp(viewer);CHKERRQ(ierr);
3536   ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr);
3537   ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr);
3538   ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr);
3539   ierr = PetscOptionsEnd();CHKERRQ(ierr);
3540   if (bs < 0) bs = 1;
3541 
3542   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
3543   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
3544   ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
3545   if (!rank) {
3546     ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr);
3547     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
3548   }
3549   ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr);
3550   M    = header[1]; N = header[2];
3551 
3552   /* If global sizes are set, check if they are consistent with that given in the file */
3553   if (newmat->rmap->N >= 0 && newmat->rmap->N != M) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of rows:Matrix in file has (%D) and input matrix has (%D)",newmat->rmap->N,M);
3554   if (newmat->cmap->N >= 0 && newmat->cmap->N != N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Inconsistent # of cols:Matrix in file has (%D) and input matrix has (%D)",newmat->cmap->N,N);
3555 
3556   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");
3557 
3558   /*
3559      This code adds extra rows to make sure the number of rows is
3560      divisible by the blocksize
3561   */
3562   Mbs        = M/bs;
3563   extra_rows = bs - M + bs*Mbs;
3564   if (extra_rows == bs) extra_rows = 0;
3565   else                  Mbs++;
3566   if (extra_rows && !rank) {
3567     ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr);
3568   }
3569 
3570   /* determine ownership of all rows */
3571   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
3572     mbs = Mbs/size + ((Mbs % size) > rank);
3573     m   = mbs*bs;
3574   } else { /* User set */
3575     m   = newmat->rmap->n;
3576     mbs = m/bs;
3577   }
3578   ierr = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr);
3579   ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr);
3580 
3581   /* process 0 needs enough room for process with most rows */
3582   if (!rank) {
3583     mmax = rowners[1];
3584     for (i=2; i<=size; i++) {
3585       mmax = PetscMax(mmax,rowners[i]);
3586     }
3587     mmax*=bs;
3588   } else mmax = -1;             /* unused, but compiler warns anyway */
3589 
3590   rowners[0] = 0;
3591   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
3592   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
3593   rstart = rowners[rank];
3594   rend   = rowners[rank+1];
3595 
3596   /* distribute row lengths to all processors */
3597   ierr = PetscMalloc1(m,&locrowlens);CHKERRQ(ierr);
3598   if (!rank) {
3599     mend = m;
3600     if (size == 1) mend = mend - extra_rows;
3601     ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr);
3602     for (j=mend; j<m; j++) locrowlens[j] = 1;
3603     ierr = PetscMalloc1(mmax,&rowlengths);CHKERRQ(ierr);
3604     ierr = PetscCalloc1(size,&procsnz);CHKERRQ(ierr);
3605     for (j=0; j<m; j++) {
3606       procsnz[0] += locrowlens[j];
3607     }
3608     for (i=1; i<size; i++) {
3609       mend = browners[i+1] - browners[i];
3610       if (i == size-1) mend = mend - extra_rows;
3611       ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr);
3612       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
3613       /* calculate the number of nonzeros on each processor */
3614       for (j=0; j<browners[i+1]-browners[i]; j++) {
3615         procsnz[i] += rowlengths[j];
3616       }
3617       ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr);
3618     }
3619     ierr = PetscFree(rowlengths);CHKERRQ(ierr);
3620   } else {
3621     ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
3622   }
3623 
3624   if (!rank) {
3625     /* determine max buffer needed and allocate it */
3626     maxnz = procsnz[0];
3627     for (i=1; i<size; i++) {
3628       maxnz = PetscMax(maxnz,procsnz[i]);
3629     }
3630     ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr);
3631 
3632     /* read in my part of the matrix column indices  */
3633     nz     = procsnz[0];
3634     ierr   = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr);
3635     mycols = ibuf;
3636     if (size == 1) nz -= extra_rows;
3637     ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr);
3638     if (size == 1) {
3639       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
3640     }
3641 
3642     /* read in every ones (except the last) and ship off */
3643     for (i=1; i<size-1; i++) {
3644       nz   = procsnz[i];
3645       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
3646       ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr);
3647     }
3648     /* read in the stuff for the last proc */
3649     if (size != 1) {
3650       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
3651       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
3652       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
3653       ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr);
3654     }
3655     ierr = PetscFree(cols);CHKERRQ(ierr);
3656   } else {
3657     /* determine buffer space needed for message */
3658     nz = 0;
3659     for (i=0; i<m; i++) {
3660       nz += locrowlens[i];
3661     }
3662     ierr   = PetscMalloc1(nz+1,&ibuf);CHKERRQ(ierr);
3663     mycols = ibuf;
3664     /* receive message of column indices*/
3665     ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
3666     ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr);
3667     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
3668   }
3669 
3670   /* loop over local rows, determining number of off diagonal entries */
3671   ierr     = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr);
3672   ierr     = PetscCalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr);
3673   rowcount = 0; nzcount = 0;
3674   for (i=0; i<mbs; i++) {
3675     dcount  = 0;
3676     odcount = 0;
3677     for (j=0; j<bs; j++) {
3678       kmax = locrowlens[rowcount];
3679       for (k=0; k<kmax; k++) {
3680         tmp = mycols[nzcount++]/bs;
3681         if (!mask[tmp]) {
3682           mask[tmp] = 1;
3683           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
3684           else masked1[dcount++] = tmp;
3685         }
3686       }
3687       rowcount++;
3688     }
3689 
3690     dlens[i]  = dcount;
3691     odlens[i] = odcount;
3692 
3693     /* zero out the mask elements we set */
3694     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
3695     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
3696   }
3697 
3698   ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr);
3699   ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr);
3700 
3701   if (!rank) {
3702     ierr = PetscMalloc1(maxnz+1,&buf);CHKERRQ(ierr);
3703     /* read in my part of the matrix numerical values  */
3704     nz     = procsnz[0];
3705     vals   = buf;
3706     mycols = ibuf;
3707     if (size == 1) nz -= extra_rows;
3708     ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3709     if (size == 1) {
3710       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
3711     }
3712 
3713     /* insert into matrix */
3714     jj = rstart*bs;
3715     for (i=0; i<m; i++) {
3716       ierr    = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
3717       mycols += locrowlens[i];
3718       vals   += locrowlens[i];
3719       jj++;
3720     }
3721     /* read in other processors (except the last one) and ship out */
3722     for (i=1; i<size-1; i++) {
3723       nz   = procsnz[i];
3724       vals = buf;
3725       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3726       ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3727     }
3728     /* the last proc */
3729     if (size != 1) {
3730       nz   = procsnz[i] - extra_rows;
3731       vals = buf;
3732       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3733       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
3734       ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3735     }
3736     ierr = PetscFree(procsnz);CHKERRQ(ierr);
3737   } else {
3738     /* receive numeric values */
3739     ierr = PetscMalloc1(nz+1,&buf);CHKERRQ(ierr);
3740 
3741     /* receive message of values*/
3742     vals   = buf;
3743     mycols = ibuf;
3744     ierr   = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3745 
3746     /* insert into matrix */
3747     jj = rstart*bs;
3748     for (i=0; i<m; i++) {
3749       ierr    = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
3750       mycols += locrowlens[i];
3751       vals   += locrowlens[i];
3752       jj++;
3753     }
3754   }
3755   ierr = PetscFree(locrowlens);CHKERRQ(ierr);
3756   ierr = PetscFree(buf);CHKERRQ(ierr);
3757   ierr = PetscFree(ibuf);CHKERRQ(ierr);
3758   ierr = PetscFree2(rowners,browners);CHKERRQ(ierr);
3759   ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr);
3760   ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr);
3761   ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3762   ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3763   PetscFunctionReturn(0);
3764 }
3765 
3766 #undef __FUNCT__
3767 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor"
3768 /*@
3769    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.
3770 
3771    Input Parameters:
3772 .  mat  - the matrix
3773 .  fact - factor
3774 
3775    Not Collective, each process can use a different factor
3776 
3777    Level: advanced
3778 
3779   Notes:
3780    This can also be set by the command line option: -mat_use_hash_table <fact>
3781 
3782 .keywords: matrix, hashtable, factor, HT
3783 
3784 .seealso: MatSetOption()
3785 @*/
3786 PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
3787 {
3788   PetscErrorCode ierr;
3789 
3790   PetscFunctionBegin;
3791   ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr);
3792   PetscFunctionReturn(0);
3793 }
3794 
3795 #undef __FUNCT__
3796 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ"
3797 PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
3798 {
3799   Mat_MPIBAIJ *baij;
3800 
3801   PetscFunctionBegin;
3802   baij          = (Mat_MPIBAIJ*)mat->data;
3803   baij->ht_fact = fact;
3804   PetscFunctionReturn(0);
3805 }
3806 
3807 #undef __FUNCT__
3808 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ"
3809 PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3810 {
3811   Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;
3812 
3813   PetscFunctionBegin;
3814   if (Ad)     *Ad     = a->A;
3815   if (Ao)     *Ao     = a->B;
3816   if (colmap) *colmap = a->garray;
3817   PetscFunctionReturn(0);
3818 }
3819 
3820 /*
3821     Special version for direct calls from Fortran (to eliminate two function call overheads
3822 */
3823 #if defined(PETSC_HAVE_FORTRAN_CAPS)
3824 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
3825 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
3826 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
3827 #endif
3828 
3829 #undef __FUNCT__
3830 #define __FUNCT__ "matmpibiajsetvaluesblocked"
3831 /*@C
3832   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()
3833 
3834   Collective on Mat
3835 
3836   Input Parameters:
3837 + mat - the matrix
3838 . min - number of input rows
3839 . im - input rows
3840 . nin - number of input columns
3841 . in - input columns
3842 . v - numerical values input
3843 - addvin - INSERT_VALUES or ADD_VALUES
3844 
3845   Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.
3846 
3847   Level: advanced
3848 
3849 .seealso:   MatSetValuesBlocked()
3850 @*/
3851 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
3852 {
3853   /* convert input arguments to C version */
3854   Mat        mat  = *matin;
3855   PetscInt   m    = *min, n = *nin;
3856   InsertMode addv = *addvin;
3857 
3858   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
3859   const MatScalar *value;
3860   MatScalar       *barray     = baij->barray;
3861   PetscBool       roworiented = baij->roworiented;
3862   PetscErrorCode  ierr;
3863   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
3864   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
3865   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;
3866 
3867   PetscFunctionBegin;
3868   /* tasks normally handled by MatSetValuesBlocked() */
3869   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
3870 #if defined(PETSC_USE_DEBUG)
3871   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
3872   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
3873 #endif
3874   if (mat->assembled) {
3875     mat->was_assembled = PETSC_TRUE;
3876     mat->assembled     = PETSC_FALSE;
3877   }
3878   ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr);
3879 
3880 
3881   if (!barray) {
3882     ierr         = PetscMalloc1(bs2,&barray);CHKERRQ(ierr);
3883     baij->barray = barray;
3884   }
3885 
3886   if (roworiented) stepval = (n-1)*bs;
3887   else stepval = (m-1)*bs;
3888 
3889   for (i=0; i<m; i++) {
3890     if (im[i] < 0) continue;
3891 #if defined(PETSC_USE_DEBUG)
3892     if (im[i] >= baij->Mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large, row %D max %D",im[i],baij->Mbs-1);
3893 #endif
3894     if (im[i] >= rstart && im[i] < rend) {
3895       row = im[i] - rstart;
3896       for (j=0; j<n; j++) {
3897         /* If NumCol = 1 then a copy is not required */
3898         if ((roworiented) && (n == 1)) {
3899           barray = (MatScalar*)v + i*bs2;
3900         } else if ((!roworiented) && (m == 1)) {
3901           barray = (MatScalar*)v + j*bs2;
3902         } else { /* Here a copy is required */
3903           if (roworiented) {
3904             value = v + i*(stepval+bs)*bs + j*bs;
3905           } else {
3906             value = v + j*(stepval+bs)*bs + i*bs;
3907           }
3908           for (ii=0; ii<bs; ii++,value+=stepval) {
3909             for (jj=0; jj<bs; jj++) {
3910               *barray++ = *value++;
3911             }
3912           }
3913           barray -=bs2;
3914         }
3915 
3916         if (in[j] >= cstart && in[j] < cend) {
3917           col  = in[j] - cstart;
3918           ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr);
3919         } else if (in[j] < 0) continue;
3920 #if defined(PETSC_USE_DEBUG)
3921         else if (in[j] >= baij->Nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large, col %D max %D",in[j],baij->Nbs-1);
3922 #endif
3923         else {
3924           if (mat->was_assembled) {
3925             if (!baij->colmap) {
3926               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
3927             }
3928 
3929 #if defined(PETSC_USE_DEBUG)
3930 #if defined(PETSC_USE_CTABLE)
3931             { PetscInt data;
3932               ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
3933               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3934             }
3935 #else
3936             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3937 #endif
3938 #endif
3939 #if defined(PETSC_USE_CTABLE)
3940             ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
3941             col  = (col - 1)/bs;
3942 #else
3943             col = (baij->colmap[in[j]] - 1)/bs;
3944 #endif
3945             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
3946               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
3947               col  =  in[j];
3948             }
3949           } else col = in[j];
3950           ierr = MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B,row,col,barray,addv,im[i],in[j]);CHKERRQ(ierr);
3951         }
3952       }
3953     } else {
3954       if (!baij->donotstash) {
3955         if (roworiented) {
3956           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
3957         } else {
3958           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
3959         }
3960       }
3961     }
3962   }
3963 
3964   /* task normally handled by MatSetValuesBlocked() */
3965   ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr);
3966   PetscFunctionReturn(0);
3967 }
3968 
3969 #undef __FUNCT__
3970 #define __FUNCT__ "MatCreateMPIBAIJWithArrays"
3971 /*@
3972      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
3973          CSR format the local rows.
3974 
3975    Collective on MPI_Comm
3976 
3977    Input Parameters:
3978 +  comm - MPI communicator
3979 .  bs - the block size, only a block size of 1 is supported
3980 .  m - number of local rows (Cannot be PETSC_DECIDE)
3981 .  n - This value should be the same as the local size used in creating the
3982        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3983        calculated if N is given) For square matrices n is almost always m.
3984 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3985 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3986 .   i - row indices
3987 .   j - column indices
3988 -   a - matrix values
3989 
3990    Output Parameter:
3991 .   mat - the matrix
3992 
3993    Level: intermediate
3994 
3995    Notes:
3996        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3997      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3998      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3999 
4000      The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
4001      the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
4002      block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
4003      with column-major ordering within blocks.
4004 
4005        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
4006 
4007 .keywords: matrix, aij, compressed row, sparse, parallel
4008 
4009 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4010           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4011 @*/
4012 PetscErrorCode  MatCreateMPIBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
4013 {
4014   PetscErrorCode ierr;
4015 
4016   PetscFunctionBegin;
4017   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4018   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4019   ierr = MatCreate(comm,mat);CHKERRQ(ierr);
4020   ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr);
4021   ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr);
4022   ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr);
4023   ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr);
4024   ierr = MatSetOption(*mat,MAT_ROW_ORIENTED,PETSC_TRUE);CHKERRQ(ierr);
4025   PetscFunctionReturn(0);
4026 }
4027 
4028 #undef __FUNCT__
4029 #define __FUNCT__ "MatCreateMPIMatConcatenateSeqMat_MPIBAIJ"
4030 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
4031 {
4032   PetscErrorCode ierr;
4033   PetscInt       m,N,i,rstart,nnz,Ii,bs,cbs;
4034   PetscInt       *indx;
4035   PetscScalar    *values;
4036 
4037   PetscFunctionBegin;
4038   ierr = MatGetSize(inmat,&m,&N);CHKERRQ(ierr);
4039   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
4040     Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inmat->data;
4041     PetscInt       *dnz,*onz,sum,mbs,Nbs;
4042     PetscInt       *bindx,rmax=a->rmax,j;
4043 
4044     ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr);
4045     mbs = m/bs; Nbs = N/cbs;
4046     if (n == PETSC_DECIDE) {
4047       ierr = PetscSplitOwnership(comm,&n,&Nbs);CHKERRQ(ierr);
4048     }
4049     /* Check sum(n) = Nbs */
4050     ierr = MPI_Allreduce(&n,&sum,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr);
4051     if (sum != Nbs) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Sum of local columns != global columns %d",Nbs);
4052 
4053     ierr    = MPI_Scan(&mbs, &rstart,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr);
4054     rstart -= mbs;
4055 
4056     ierr = PetscMalloc1(rmax,&bindx);CHKERRQ(ierr);
4057     ierr = MatPreallocateInitialize(comm,mbs,n,dnz,onz);CHKERRQ(ierr);
4058     for (i=0; i<mbs; i++) {
4059       ierr = MatGetRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr); /* non-blocked nnz and indx */
4060       nnz = nnz/bs;
4061       for (j=0; j<nnz; j++) bindx[j] = indx[j*bs]/bs;
4062       ierr = MatPreallocateSet(i+rstart,nnz,bindx,dnz,onz);CHKERRQ(ierr);
4063       ierr = MatRestoreRow_SeqBAIJ(inmat,i*bs,&nnz,&indx,NULL);CHKERRQ(ierr);
4064     }
4065     ierr = PetscFree(bindx);CHKERRQ(ierr);
4066 
4067     ierr = MatCreate(comm,outmat);CHKERRQ(ierr);
4068     ierr = MatSetSizes(*outmat,m,n*bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr);
4069     ierr = MatSetBlockSizes(*outmat,bs,cbs);CHKERRQ(ierr);
4070     ierr = MatSetType(*outmat,MATMPIBAIJ);CHKERRQ(ierr);
4071     ierr = MatMPIBAIJSetPreallocation(*outmat,bs,0,dnz,0,onz);CHKERRQ(ierr);
4072     ierr = MatPreallocateFinalize(dnz,onz);CHKERRQ(ierr);
4073   }
4074 
4075   /* numeric phase */
4076   ierr = MatGetBlockSizes(inmat,&bs,&cbs);CHKERRQ(ierr);
4077   ierr = MatGetOwnershipRange(*outmat,&rstart,NULL);CHKERRQ(ierr);
4078 
4079   for (i=0; i<m; i++) {
4080     ierr = MatGetRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr);
4081     Ii   = i + rstart;
4082     ierr = MatSetValues(*outmat,1,&Ii,nnz,indx,values,INSERT_VALUES);CHKERRQ(ierr);
4083     ierr = MatRestoreRow_SeqBAIJ(inmat,i,&nnz,&indx,&values);CHKERRQ(ierr);
4084   }
4085   ierr = MatAssemblyBegin(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
4086   ierr = MatAssemblyEnd(*outmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
4087   PetscFunctionReturn(0);
4088 }
4089