xref: /petsc/src/mat/impls/baij/mpi/mpibaij.c (revision 0775d057cef51002cda4c91b978db4f8c586b313)
1 
2 #include <../src/mat/impls/baij/mpi/mpibaij.h>   /*I  "petscmat.h"  I*/
3 #include <petscblaslapack.h>
4 
5 extern PetscErrorCode MatSetUpMultiply_MPIBAIJ(Mat);
6 extern PetscErrorCode MatDisAssemble_MPIBAIJ(Mat);
7 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],PetscScalar []);
8 extern PetscErrorCode MatSetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt [],const PetscScalar [],InsertMode);
9 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
10 extern PetscErrorCode MatGetRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]);
11 extern PetscErrorCode MatRestoreRow_SeqBAIJ(Mat,PetscInt,PetscInt*,PetscInt*[],PetscScalar*[]);
12 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscScalar,Vec,Vec);
13 
14 #undef __FUNCT__
15 #define __FUNCT__ "MatGetRowMaxAbs_MPIBAIJ"
16 PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A,Vec v,PetscInt idx[])
17 {
18   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
19   PetscErrorCode ierr;
20   PetscInt       i,*idxb = 0;
21   PetscScalar    *va,*vb;
22   Vec            vtmp;
23 
24   PetscFunctionBegin;
25   ierr = MatGetRowMaxAbs(a->A,v,idx);CHKERRQ(ierr);
26   ierr = VecGetArray(v,&va);CHKERRQ(ierr);
27   if (idx) {
28     for (i=0; i<A->rmap->n; i++) {
29       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
30     }
31   }
32 
33   ierr = VecCreateSeq(PETSC_COMM_SELF,A->rmap->n,&vtmp);CHKERRQ(ierr);
34   if (idx) {ierr = PetscMalloc(A->rmap->n*sizeof(PetscInt),&idxb);CHKERRQ(ierr);}
35   ierr = MatGetRowMaxAbs(a->B,vtmp,idxb);CHKERRQ(ierr);
36   ierr = VecGetArray(vtmp,&vb);CHKERRQ(ierr);
37 
38   for (i=0; i<A->rmap->n; i++) {
39     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
40       va[i] = vb[i];
41       if (idx) idx[i] = A->cmap->bs*a->garray[idxb[i]/A->cmap->bs] + (idxb[i] % A->cmap->bs);
42     }
43   }
44 
45   ierr = VecRestoreArray(v,&va);CHKERRQ(ierr);
46   ierr = VecRestoreArray(vtmp,&vb);CHKERRQ(ierr);
47   ierr = PetscFree(idxb);CHKERRQ(ierr);
48   ierr = VecDestroy(&vtmp);CHKERRQ(ierr);
49   PetscFunctionReturn(0);
50 }
51 
52 #undef __FUNCT__
53 #define __FUNCT__ "MatStoreValues_MPIBAIJ"
54 PetscErrorCode  MatStoreValues_MPIBAIJ(Mat mat)
55 {
56   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;
57   PetscErrorCode ierr;
58 
59   PetscFunctionBegin;
60   ierr = MatStoreValues(aij->A);CHKERRQ(ierr);
61   ierr = MatStoreValues(aij->B);CHKERRQ(ierr);
62   PetscFunctionReturn(0);
63 }
64 
65 #undef __FUNCT__
66 #define __FUNCT__ "MatRetrieveValues_MPIBAIJ"
67 PetscErrorCode  MatRetrieveValues_MPIBAIJ(Mat mat)
68 {
69   Mat_MPIBAIJ    *aij = (Mat_MPIBAIJ*)mat->data;
70   PetscErrorCode ierr;
71 
72   PetscFunctionBegin;
73   ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr);
74   ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr);
75   PetscFunctionReturn(0);
76 }
77 
78 /*
79      Local utility routine that creates a mapping from the global column
80    number to the local number in the off-diagonal part of the local
81    storage of the matrix.  This is done in a non scalable way since the
82    length of colmap equals the global matrix length.
83 */
84 #undef __FUNCT__
85 #define __FUNCT__ "MatCreateColmap_MPIBAIJ_Private"
86 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat)
87 {
88   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
89   Mat_SeqBAIJ    *B    = (Mat_SeqBAIJ*)baij->B->data;
90   PetscErrorCode ierr;
91   PetscInt       nbs = B->nbs,i,bs=mat->rmap->bs;
92 
93   PetscFunctionBegin;
94 #if defined(PETSC_USE_CTABLE)
95   ierr = PetscTableCreate(baij->nbs,baij->Nbs+1,&baij->colmap);CHKERRQ(ierr);
96   for (i=0; i<nbs; i++) {
97     ierr = PetscTableAdd(baij->colmap,baij->garray[i]+1,i*bs+1,INSERT_VALUES);CHKERRQ(ierr);
98   }
99 #else
100   ierr = PetscMalloc((baij->Nbs+1)*sizeof(PetscInt),&baij->colmap);CHKERRQ(ierr);
101   ierr = PetscLogObjectMemory((PetscObject)mat,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr);
102   ierr = PetscMemzero(baij->colmap,baij->Nbs*sizeof(PetscInt));CHKERRQ(ierr);
103   for (i=0; i<nbs; i++) baij->colmap[baij->garray[i]] = i*bs+1;
104 #endif
105   PetscFunctionReturn(0);
106 }
107 
108 #define  MatSetValues_SeqBAIJ_A_Private(row,col,value,addv) \
109   { \
110  \
111     brow = row/bs;  \
112     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
113     rmax = aimax[brow]; nrow = ailen[brow]; \
114     bcol = col/bs; \
115     ridx = row % bs; cidx = col % bs; \
116     low  = 0; high = nrow; \
117     while (high-low > 3) { \
118       t = (low+high)/2; \
119       if (rp[t] > bcol) high = t; \
120       else              low  = t; \
121     } \
122     for (_i=low; _i<high; _i++) { \
123       if (rp[_i] > bcol) break; \
124       if (rp[_i] == bcol) { \
125         bap = ap +  bs2*_i + bs*cidx + ridx; \
126         if (addv == ADD_VALUES) *bap += value;  \
127         else                    *bap  = value;  \
128         goto a_noinsert; \
129       } \
130     } \
131     if (a->nonew == 1) goto a_noinsert; \
132     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
133     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
134     N = nrow++ - 1;  \
135     /* shift up all the later entries in this row */ \
136     for (ii=N; ii>=_i; ii--) { \
137       rp[ii+1] = rp[ii]; \
138       ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
139     } \
140     if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); }  \
141     rp[_i]                      = bcol;  \
142     ap[bs2*_i + bs*cidx + ridx] = value;  \
143 a_noinsert:; \
144     ailen[brow] = nrow; \
145   }
146 
147 #define  MatSetValues_SeqBAIJ_B_Private(row,col,value,addv) \
148   { \
149     brow = row/bs;  \
150     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
151     rmax = bimax[brow]; nrow = bilen[brow]; \
152     bcol = col/bs; \
153     ridx = row % bs; cidx = col % bs; \
154     low  = 0; high = nrow; \
155     while (high-low > 3) { \
156       t = (low+high)/2; \
157       if (rp[t] > bcol) high = t; \
158       else              low  = t; \
159     } \
160     for (_i=low; _i<high; _i++) { \
161       if (rp[_i] > bcol) break; \
162       if (rp[_i] == bcol) { \
163         bap = ap +  bs2*_i + bs*cidx + ridx; \
164         if (addv == ADD_VALUES) *bap += value;  \
165         else                    *bap  = value;  \
166         goto b_noinsert; \
167       } \
168     } \
169     if (b->nonew == 1) goto b_noinsert; \
170     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
171     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
172     N = nrow++ - 1;  \
173     /* shift up all the later entries in this row */ \
174     for (ii=N; ii>=_i; ii--) { \
175       rp[ii+1] = rp[ii]; \
176       ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
177     } \
178     if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);}  \
179     rp[_i]                      = bcol;  \
180     ap[bs2*_i + bs*cidx + ridx] = value;  \
181 b_noinsert:; \
182     bilen[brow] = nrow; \
183   }
184 
185 #undef __FUNCT__
186 #define __FUNCT__ "MatSetValues_MPIBAIJ"
187 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
188 {
189   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
190   MatScalar      value;
191   PetscBool      roworiented = baij->roworiented;
192   PetscErrorCode ierr;
193   PetscInt       i,j,row,col;
194   PetscInt       rstart_orig=mat->rmap->rstart;
195   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
196   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;
197 
198   /* Some Variables required in the macro */
199   Mat         A     = baij->A;
200   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ*)(A)->data;
201   PetscInt    *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
202   MatScalar   *aa   =a->a;
203 
204   Mat         B     = baij->B;
205   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
206   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
207   MatScalar   *ba   =b->a;
208 
209   PetscInt  *rp,ii,nrow,_i,rmax,N,brow,bcol;
210   PetscInt  low,high,t,ridx,cidx,bs2=a->bs2;
211   MatScalar *ap,*bap;
212 
213   PetscFunctionBegin;
214   if (v) PetscValidScalarPointer(v,6);
215   for (i=0; i<m; i++) {
216     if (im[i] < 0) continue;
217 #if defined(PETSC_USE_DEBUG)
218     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);
219 #endif
220     if (im[i] >= rstart_orig && im[i] < rend_orig) {
221       row = im[i] - rstart_orig;
222       for (j=0; j<n; j++) {
223         if (in[j] >= cstart_orig && in[j] < cend_orig) {
224           col = in[j] - cstart_orig;
225           if (roworiented) value = v[i*n+j];
226           else             value = v[i+j*m];
227           MatSetValues_SeqBAIJ_A_Private(row,col,value,addv);
228           /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
229         } else if (in[j] < 0) continue;
230 #if defined(PETSC_USE_DEBUG)
231         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);
232 #endif
233         else {
234           if (mat->was_assembled) {
235             if (!baij->colmap) {
236               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
237             }
238 #if defined(PETSC_USE_CTABLE)
239             ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr);
240             col  = col - 1;
241 #else
242             col = baij->colmap[in[j]/bs] - 1;
243 #endif
244             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
245               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
246               col  =  in[j];
247               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
248               B    = baij->B;
249               b    = (Mat_SeqBAIJ*)(B)->data;
250               bimax=b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
251               ba   =b->a;
252             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", im[i], in[j]);
253             else col += in[j]%bs;
254           } else col = in[j];
255           if (roworiented) value = v[i*n+j];
256           else             value = v[i+j*m];
257           MatSetValues_SeqBAIJ_B_Private(row,col,value,addv);
258           /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
259         }
260       }
261     } else {
262       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]);
263       if (!baij->donotstash) {
264         mat->assembled = PETSC_FALSE;
265         if (roworiented) {
266           ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr);
267         } else {
268           ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr);
269         }
270       }
271     }
272   }
273   PetscFunctionReturn(0);
274 }
275 
276 #undef __FUNCT__
277 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ"
278 PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
279 {
280   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
281   const PetscScalar *value;
282   MatScalar         *barray     = baij->barray;
283   PetscBool         roworiented = baij->roworiented;
284   PetscErrorCode    ierr;
285   PetscInt          i,j,ii,jj,row,col,rstart=baij->rstartbs;
286   PetscInt          rend=baij->rendbs,cstart=baij->cstartbs,stepval;
287   PetscInt          cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;
288 
289   PetscFunctionBegin;
290   if (!barray) {
291     ierr         = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr);
292     baij->barray = barray;
293   }
294 
295   if (roworiented) stepval = (n-1)*bs;
296   else stepval = (m-1)*bs;
297 
298   for (i=0; i<m; i++) {
299     if (im[i] < 0) continue;
300 #if defined(PETSC_USE_DEBUG)
301     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);
302 #endif
303     if (im[i] >= rstart && im[i] < rend) {
304       row = im[i] - rstart;
305       for (j=0; j<n; j++) {
306         /* If NumCol = 1 then a copy is not required */
307         if ((roworiented) && (n == 1)) {
308           barray = (MatScalar*)v + i*bs2;
309         } else if ((!roworiented) && (m == 1)) {
310           barray = (MatScalar*)v + j*bs2;
311         } else { /* Here a copy is required */
312           if (roworiented) {
313             value = v + (i*(stepval+bs) + j)*bs;
314           } else {
315             value = v + (j*(stepval+bs) + i)*bs;
316           }
317           for (ii=0; ii<bs; ii++,value+=bs+stepval) {
318             for (jj=0; jj<bs; jj++) barray[jj] = value[jj];
319             barray += bs;
320           }
321           barray -= bs2;
322         }
323 
324         if (in[j] >= cstart && in[j] < cend) {
325           col  = in[j] - cstart;
326           ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
327         } else if (in[j] < 0) continue;
328 #if defined(PETSC_USE_DEBUG)
329         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);
330 #endif
331         else {
332           if (mat->was_assembled) {
333             if (!baij->colmap) {
334               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
335             }
336 
337 #if defined(PETSC_USE_DEBUG)
338 #if defined(PETSC_USE_CTABLE)
339             { PetscInt data;
340               ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
341               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
342             }
343 #else
344             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
345 #endif
346 #endif
347 #if defined(PETSC_USE_CTABLE)
348             ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
349             col  = (col - 1)/bs;
350 #else
351             col = (baij->colmap[in[j]] - 1)/bs;
352 #endif
353             if (col < 0 && !((Mat_SeqBAIJ*)(baij->B->data))->nonew) {
354               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
355               col  =  in[j];
356             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", bs*im[i], bs*in[j]);
357           } else col = in[j];
358           ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
359         }
360       }
361     } else {
362       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]);
363       if (!baij->donotstash) {
364         if (roworiented) {
365           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
366         } else {
367           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
368         }
369       }
370     }
371   }
372   PetscFunctionReturn(0);
373 }
374 
375 #define HASH_KEY 0.6180339887
376 #define HASH(size,key,tmp) (tmp = (key)*HASH_KEY,(PetscInt)((size)*(tmp-(PetscInt)tmp)))
377 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
378 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
379 #undef __FUNCT__
380 #define __FUNCT__ "MatSetValues_MPIBAIJ_HT"
381 PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
382 {
383   Mat_MPIBAIJ    *baij       = (Mat_MPIBAIJ*)mat->data;
384   PetscBool      roworiented = baij->roworiented;
385   PetscErrorCode ierr;
386   PetscInt       i,j,row,col;
387   PetscInt       rstart_orig=mat->rmap->rstart;
388   PetscInt       rend_orig  =mat->rmap->rend,Nbs=baij->Nbs;
389   PetscInt       h1,key,size=baij->ht_size,bs=mat->rmap->bs,*HT=baij->ht,idx;
390   PetscReal      tmp;
391   MatScalar      **HD = baij->hd,value;
392 #if defined(PETSC_USE_DEBUG)
393   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
394 #endif
395 
396   PetscFunctionBegin;
397   if (v) PetscValidScalarPointer(v,6);
398   for (i=0; i<m; i++) {
399 #if defined(PETSC_USE_DEBUG)
400     if (im[i] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row");
401     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);
402 #endif
403     row = im[i];
404     if (row >= rstart_orig && row < rend_orig) {
405       for (j=0; j<n; j++) {
406         col = in[j];
407         if (roworiented) value = v[i*n+j];
408         else             value = v[i+j*m];
409         /* Look up PetscInto the Hash Table */
410         key = (row/bs)*Nbs+(col/bs)+1;
411         h1  = HASH(size,key,tmp);
412 
413 
414         idx = h1;
415 #if defined(PETSC_USE_DEBUG)
416         insert_ct++;
417         total_ct++;
418         if (HT[idx] != key) {
419           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
420           if (idx == size) {
421             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
422             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
423           }
424         }
425 #else
426         if (HT[idx] != key) {
427           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
428           if (idx == size) {
429             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
430             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
431           }
432         }
433 #endif
434         /* A HASH table entry is found, so insert the values at the correct address */
435         if (addv == ADD_VALUES) *(HD[idx]+ (col % bs)*bs + (row % bs)) += value;
436         else                    *(HD[idx]+ (col % bs)*bs + (row % bs))  = value;
437       }
438     } else if (!baij->donotstash) {
439       if (roworiented) {
440         ierr = MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,PETSC_FALSE);CHKERRQ(ierr);
441       } else {
442         ierr = MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,PETSC_FALSE);CHKERRQ(ierr);
443       }
444     }
445   }
446 #if defined(PETSC_USE_DEBUG)
447   baij->ht_total_ct  = total_ct;
448   baij->ht_insert_ct = insert_ct;
449 #endif
450   PetscFunctionReturn(0);
451 }
452 
453 #undef __FUNCT__
454 #define __FUNCT__ "MatSetValuesBlocked_MPIBAIJ_HT"
455 PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
456 {
457   Mat_MPIBAIJ       *baij       = (Mat_MPIBAIJ*)mat->data;
458   PetscBool         roworiented = baij->roworiented;
459   PetscErrorCode    ierr;
460   PetscInt          i,j,ii,jj,row,col;
461   PetscInt          rstart=baij->rstartbs;
462   PetscInt          rend  =mat->rmap->rend,stepval,bs=mat->rmap->bs,bs2=baij->bs2,nbs2=n*bs2;
463   PetscInt          h1,key,size=baij->ht_size,idx,*HT=baij->ht,Nbs=baij->Nbs;
464   PetscReal         tmp;
465   MatScalar         **HD = baij->hd,*baij_a;
466   const PetscScalar *v_t,*value;
467 #if defined(PETSC_USE_DEBUG)
468   PetscInt total_ct=baij->ht_total_ct,insert_ct=baij->ht_insert_ct;
469 #endif
470 
471   PetscFunctionBegin;
472   if (roworiented) stepval = (n-1)*bs;
473   else stepval = (m-1)*bs;
474 
475   for (i=0; i<m; i++) {
476 #if defined(PETSC_USE_DEBUG)
477     if (im[i] < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",im[i]);
478     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);
479 #endif
480     row = im[i];
481     v_t = v + i*nbs2;
482     if (row >= rstart && row < rend) {
483       for (j=0; j<n; j++) {
484         col = in[j];
485 
486         /* Look up into the Hash Table */
487         key = row*Nbs+col+1;
488         h1  = HASH(size,key,tmp);
489 
490         idx = h1;
491 #if defined(PETSC_USE_DEBUG)
492         total_ct++;
493         insert_ct++;
494         if (HT[idx] != key) {
495           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++,total_ct++) ;
496           if (idx == size) {
497             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++,total_ct++) ;
498             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
499           }
500         }
501 #else
502         if (HT[idx] != key) {
503           for (idx=h1; (idx<size) && (HT[idx]!=key); idx++) ;
504           if (idx == size) {
505             for (idx=0; (idx<h1) && (HT[idx]!=key); idx++) ;
506             if (idx == h1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"(%D,%D) has no entry in the hash table", row, col);
507           }
508         }
509 #endif
510         baij_a = HD[idx];
511         if (roworiented) {
512           /*value = v + i*(stepval+bs)*bs + j*bs;*/
513           /* value = v + (i*(stepval+bs)+j)*bs; */
514           value = v_t;
515           v_t  += bs;
516           if (addv == ADD_VALUES) {
517             for (ii=0; ii<bs; ii++,value+=stepval) {
518               for (jj=ii; jj<bs2; jj+=bs) {
519                 baij_a[jj] += *value++;
520               }
521             }
522           } else {
523             for (ii=0; ii<bs; ii++,value+=stepval) {
524               for (jj=ii; jj<bs2; jj+=bs) {
525                 baij_a[jj] = *value++;
526               }
527             }
528           }
529         } else {
530           value = v + j*(stepval+bs)*bs + i*bs;
531           if (addv == ADD_VALUES) {
532             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
533               for (jj=0; jj<bs; jj++) {
534                 baij_a[jj] += *value++;
535               }
536             }
537           } else {
538             for (ii=0; ii<bs; ii++,value+=stepval,baij_a+=bs) {
539               for (jj=0; jj<bs; jj++) {
540                 baij_a[jj] = *value++;
541               }
542             }
543           }
544         }
545       }
546     } else {
547       if (!baij->donotstash) {
548         if (roworiented) {
549           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
550         } else {
551           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
552         }
553       }
554     }
555   }
556 #if defined(PETSC_USE_DEBUG)
557   baij->ht_total_ct  = total_ct;
558   baij->ht_insert_ct = insert_ct;
559 #endif
560   PetscFunctionReturn(0);
561 }
562 
563 #undef __FUNCT__
564 #define __FUNCT__ "MatGetValues_MPIBAIJ"
565 PetscErrorCode MatGetValues_MPIBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
566 {
567   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
568   PetscErrorCode ierr;
569   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
570   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;
571 
572   PetscFunctionBegin;
573   for (i=0; i<m; i++) {
574     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
575     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);
576     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
577       row = idxm[i] - bsrstart;
578       for (j=0; j<n; j++) {
579         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
580         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);
581         if (idxn[j] >= bscstart && idxn[j] < bscend) {
582           col  = idxn[j] - bscstart;
583           ierr = MatGetValues_SeqBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
584         } else {
585           if (!baij->colmap) {
586             ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
587           }
588 #if defined(PETSC_USE_CTABLE)
589           ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr);
590           data--;
591 #else
592           data = baij->colmap[idxn[j]/bs]-1;
593 #endif
594           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
595           else {
596             col  = data + idxn[j]%bs;
597             ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
598           }
599         }
600       }
601     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
602   }
603   PetscFunctionReturn(0);
604 }
605 
606 #undef __FUNCT__
607 #define __FUNCT__ "MatNorm_MPIBAIJ"
608 PetscErrorCode MatNorm_MPIBAIJ(Mat mat,NormType type,PetscReal *nrm)
609 {
610   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
611   Mat_SeqBAIJ    *amat = (Mat_SeqBAIJ*)baij->A->data,*bmat = (Mat_SeqBAIJ*)baij->B->data;
612   PetscErrorCode ierr;
613   PetscInt       i,j,bs2=baij->bs2,bs=baij->A->rmap->bs,nz,row,col;
614   PetscReal      sum = 0.0;
615   MatScalar      *v;
616 
617   PetscFunctionBegin;
618   if (baij->size == 1) {
619     ierr =  MatNorm(baij->A,type,nrm);CHKERRQ(ierr);
620   } else {
621     if (type == NORM_FROBENIUS) {
622       v  = amat->a;
623       nz = amat->nz*bs2;
624       for (i=0; i<nz; i++) {
625         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
626       }
627       v  = bmat->a;
628       nz = bmat->nz*bs2;
629       for (i=0; i<nz; i++) {
630         sum += PetscRealPart(PetscConj(*v)*(*v)); v++;
631       }
632       ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
633       *nrm = PetscSqrtReal(*nrm);
634     } else if (type == NORM_1) { /* max column sum */
635       PetscReal *tmp,*tmp2;
636       PetscInt  *jj,*garray=baij->garray,cstart=baij->rstartbs;
637       ierr = PetscMalloc2(mat->cmap->N,PetscReal,&tmp,mat->cmap->N,PetscReal,&tmp2);CHKERRQ(ierr);
638       ierr = PetscMemzero(tmp,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr);
639       v    = amat->a; jj = amat->j;
640       for (i=0; i<amat->nz; i++) {
641         for (j=0; j<bs; j++) {
642           col = bs*(cstart + *jj) + j; /* column index */
643           for (row=0; row<bs; row++) {
644             tmp[col] += PetscAbsScalar(*v);  v++;
645           }
646         }
647         jj++;
648       }
649       v = bmat->a; jj = bmat->j;
650       for (i=0; i<bmat->nz; i++) {
651         for (j=0; j<bs; j++) {
652           col = bs*garray[*jj] + j;
653           for (row=0; row<bs; row++) {
654             tmp[col] += PetscAbsScalar(*v); v++;
655           }
656         }
657         jj++;
658       }
659       ierr = MPI_Allreduce(tmp,tmp2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
660       *nrm = 0.0;
661       for (j=0; j<mat->cmap->N; j++) {
662         if (tmp2[j] > *nrm) *nrm = tmp2[j];
663       }
664       ierr = PetscFree2(tmp,tmp2);CHKERRQ(ierr);
665     } else if (type == NORM_INFINITY) { /* max row sum */
666       PetscReal *sums;
667       ierr = PetscMalloc(bs*sizeof(PetscReal),&sums);CHKERRQ(ierr);
668       sum  = 0.0;
669       for (j=0; j<amat->mbs; j++) {
670         for (row=0; row<bs; row++) sums[row] = 0.0;
671         v  = amat->a + bs2*amat->i[j];
672         nz = amat->i[j+1]-amat->i[j];
673         for (i=0; i<nz; i++) {
674           for (col=0; col<bs; col++) {
675             for (row=0; row<bs; row++) {
676               sums[row] += PetscAbsScalar(*v); v++;
677             }
678           }
679         }
680         v  = bmat->a + bs2*bmat->i[j];
681         nz = bmat->i[j+1]-bmat->i[j];
682         for (i=0; i<nz; i++) {
683           for (col=0; col<bs; col++) {
684             for (row=0; row<bs; row++) {
685               sums[row] += PetscAbsScalar(*v); v++;
686             }
687           }
688         }
689         for (row=0; row<bs; row++) {
690           if (sums[row] > sum) sum = sums[row];
691         }
692       }
693       ierr = MPI_Allreduce(&sum,nrm,1,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
694       ierr = PetscFree(sums);CHKERRQ(ierr);
695     } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"No support for this norm yet");
696   }
697   PetscFunctionReturn(0);
698 }
699 
700 /*
701   Creates the hash table, and sets the table
702   This table is created only once.
703   If new entried need to be added to the matrix
704   then the hash table has to be destroyed and
705   recreated.
706 */
707 #undef __FUNCT__
708 #define __FUNCT__ "MatCreateHashTable_MPIBAIJ_Private"
709 PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat,PetscReal factor)
710 {
711   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
712   Mat            A     = baij->A,B=baij->B;
713   Mat_SeqBAIJ    *a    = (Mat_SeqBAIJ*)A->data,*b=(Mat_SeqBAIJ*)B->data;
714   PetscInt       i,j,k,nz=a->nz+b->nz,h1,*ai=a->i,*aj=a->j,*bi=b->i,*bj=b->j;
715   PetscErrorCode ierr;
716   PetscInt       ht_size,bs2=baij->bs2,rstart=baij->rstartbs;
717   PetscInt       cstart=baij->cstartbs,*garray=baij->garray,row,col,Nbs=baij->Nbs;
718   PetscInt       *HT,key;
719   MatScalar      **HD;
720   PetscReal      tmp;
721 #if defined(PETSC_USE_INFO)
722   PetscInt ct=0,max=0;
723 #endif
724 
725   PetscFunctionBegin;
726   if (baij->ht) PetscFunctionReturn(0);
727 
728   baij->ht_size = (PetscInt)(factor*nz);
729   ht_size       = baij->ht_size;
730 
731   /* Allocate Memory for Hash Table */
732   ierr = PetscMalloc2(ht_size,MatScalar*,&baij->hd,ht_size,PetscInt,&baij->ht);CHKERRQ(ierr);
733   ierr = PetscMemzero(baij->hd,ht_size*sizeof(MatScalar*));CHKERRQ(ierr);
734   ierr = PetscMemzero(baij->ht,ht_size*sizeof(PetscInt));CHKERRQ(ierr);
735   HD   = baij->hd;
736   HT   = baij->ht;
737 
738   /* Loop Over A */
739   for (i=0; i<a->mbs; i++) {
740     for (j=ai[i]; j<ai[i+1]; j++) {
741       row = i+rstart;
742       col = aj[j]+cstart;
743 
744       key = row*Nbs + col + 1;
745       h1  = HASH(ht_size,key,tmp);
746       for (k=0; k<ht_size; k++) {
747         if (!HT[(h1+k)%ht_size]) {
748           HT[(h1+k)%ht_size] = key;
749           HD[(h1+k)%ht_size] = a->a + j*bs2;
750           break;
751 #if defined(PETSC_USE_INFO)
752         } else {
753           ct++;
754 #endif
755         }
756       }
757 #if defined(PETSC_USE_INFO)
758       if (k> max) max = k;
759 #endif
760     }
761   }
762   /* Loop Over B */
763   for (i=0; i<b->mbs; i++) {
764     for (j=bi[i]; j<bi[i+1]; j++) {
765       row = i+rstart;
766       col = garray[bj[j]];
767       key = row*Nbs + col + 1;
768       h1  = HASH(ht_size,key,tmp);
769       for (k=0; k<ht_size; k++) {
770         if (!HT[(h1+k)%ht_size]) {
771           HT[(h1+k)%ht_size] = key;
772           HD[(h1+k)%ht_size] = b->a + j*bs2;
773           break;
774 #if defined(PETSC_USE_INFO)
775         } else {
776           ct++;
777 #endif
778         }
779       }
780 #if defined(PETSC_USE_INFO)
781       if (k> max) max = k;
782 #endif
783     }
784   }
785 
786   /* Print Summary */
787 #if defined(PETSC_USE_INFO)
788   for (i=0,j=0; i<ht_size; i++) {
789     if (HT[i]) j++;
790   }
791   ierr = PetscInfo2(mat,"Average Search = %5.2f,max search = %D\n",(!j)? 0.0:((PetscReal)(ct+j))/j,max);CHKERRQ(ierr);
792 #endif
793   PetscFunctionReturn(0);
794 }
795 
796 #undef __FUNCT__
797 #define __FUNCT__ "MatAssemblyBegin_MPIBAIJ"
798 PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat,MatAssemblyType mode)
799 {
800   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
801   PetscErrorCode ierr;
802   PetscInt       nstash,reallocs;
803   InsertMode     addv;
804 
805   PetscFunctionBegin;
806   if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0);
807 
808   /* make sure all processors are either in INSERTMODE or ADDMODE */
809   ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
810   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
811   mat->insertmode = addv; /* in case this processor had no cache */
812 
813   ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr);
814   ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr);
815   ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr);
816   ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr);
817   ierr = MatStashGetInfo_Private(&mat->bstash,&nstash,&reallocs);CHKERRQ(ierr);
818   ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr);
819   PetscFunctionReturn(0);
820 }
821 
822 #undef __FUNCT__
823 #define __FUNCT__ "MatAssemblyEnd_MPIBAIJ"
824 PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat,MatAssemblyType mode)
825 {
826   Mat_MPIBAIJ    *baij=(Mat_MPIBAIJ*)mat->data;
827   Mat_SeqBAIJ    *a   =(Mat_SeqBAIJ*)baij->A->data;
828   PetscErrorCode ierr;
829   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
830   PetscInt       *row,*col;
831   PetscBool      r1,r2,r3,other_disassembled;
832   MatScalar      *val;
833   InsertMode     addv = mat->insertmode;
834   PetscMPIInt    n;
835 
836   PetscFunctionBegin;
837   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
838   if (!baij->donotstash && !mat->nooffprocentries) {
839     while (1) {
840       ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
841       if (!flg) break;
842 
843       for (i=0; i<n;) {
844         /* Now identify the consecutive vals belonging to the same row */
845         for (j=i,rstart=row[j]; j<n; j++) {
846           if (row[j] != rstart) break;
847         }
848         if (j < n) ncols = j-i;
849         else       ncols = n-i;
850         /* Now assemble all these values with a single function call */
851         ierr = MatSetValues_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr);
852         i    = j;
853       }
854     }
855     ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr);
856     /* Now process the block-stash. Since the values are stashed column-oriented,
857        set the roworiented flag to column oriented, and after MatSetValues()
858        restore the original flags */
859     r1 = baij->roworiented;
860     r2 = a->roworiented;
861     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
862 
863     baij->roworiented = PETSC_FALSE;
864     a->roworiented    = PETSC_FALSE;
865 
866     (((Mat_SeqBAIJ*)baij->B->data))->roworiented = PETSC_FALSE; /* b->roworiented */
867     while (1) {
868       ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
869       if (!flg) break;
870 
871       for (i=0; i<n;) {
872         /* Now identify the consecutive vals belonging to the same row */
873         for (j=i,rstart=row[j]; j<n; j++) {
874           if (row[j] != rstart) break;
875         }
876         if (j < n) ncols = j-i;
877         else       ncols = n-i;
878         ierr = MatSetValuesBlocked_MPIBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr);
879         i    = j;
880       }
881     }
882     ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr);
883 
884     baij->roworiented = r1;
885     a->roworiented    = r2;
886 
887     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworiented */
888   }
889 
890   ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr);
891   ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr);
892 
893   /* determine if any processor has disassembled, if so we must
894      also disassemble ourselfs, in order that we may reassemble. */
895   /*
896      if nonzero structure of submatrix B cannot change then we know that
897      no processor disassembled thus we can skip this stuff
898   */
899   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
900     ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
901     if (mat->was_assembled && !other_disassembled) {
902       ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
903     }
904   }
905 
906   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
907     ierr = MatSetUpMultiply_MPIBAIJ(mat);CHKERRQ(ierr);
908   }
909   ierr = MatSetOption(baij->B,MAT_CHECK_COMPRESSED_ROW,PETSC_FALSE);CHKERRQ(ierr);
910   ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr);
911   ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr);
912 
913 #if defined(PETSC_USE_INFO)
914   if (baij->ht && mode== MAT_FINAL_ASSEMBLY) {
915     ierr = PetscInfo1(mat,"Average Hash Table Search in MatSetValues = %5.2f\n",((PetscReal)baij->ht_total_ct)/baij->ht_insert_ct);CHKERRQ(ierr);
916 
917     baij->ht_total_ct  = 0;
918     baij->ht_insert_ct = 0;
919   }
920 #endif
921   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
922     ierr = MatCreateHashTable_MPIBAIJ_Private(mat,baij->ht_fact);CHKERRQ(ierr);
923 
924     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
925     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
926   }
927 
928   ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr);
929 
930   baij->rowvalues = 0;
931   PetscFunctionReturn(0);
932 }
933 
934 #include <petscdraw.h>
935 #undef __FUNCT__
936 #define __FUNCT__ "MatView_MPIBAIJ_ASCIIorDraworSocket"
937 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
938 {
939   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ*)mat->data;
940   PetscErrorCode    ierr;
941   PetscMPIInt       size = baij->size,rank = baij->rank;
942   PetscInt          bs   = mat->rmap->bs;
943   PetscBool         iascii,isdraw;
944   PetscViewer       sviewer;
945   PetscViewerFormat format;
946 
947   PetscFunctionBegin;
948   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
949   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
950   if (iascii) {
951     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
952     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
953       MatInfo info;
954       ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr);
955       ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr);
956       ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr);
957       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",
958                                                 rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr);
959       ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr);
960       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr);
961       ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr);
962       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr);
963       ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
964       ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr);
965       ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr);
966       ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr);
967       PetscFunctionReturn(0);
968     } else if (format == PETSC_VIEWER_ASCII_INFO) {
969       ierr = PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);CHKERRQ(ierr);
970       PetscFunctionReturn(0);
971     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
972       PetscFunctionReturn(0);
973     }
974   }
975 
976   if (isdraw) {
977     PetscDraw draw;
978     PetscBool isnull;
979     ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
980     ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
981   }
982 
983   if (size == 1) {
984     ierr = PetscObjectSetName((PetscObject)baij->A,((PetscObject)mat)->name);CHKERRQ(ierr);
985     ierr = MatView(baij->A,viewer);CHKERRQ(ierr);
986   } else {
987     /* assemble the entire matrix onto first processor. */
988     Mat         A;
989     Mat_SeqBAIJ *Aloc;
990     PetscInt    M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
991     MatScalar   *a;
992 
993     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
994     /* Perhaps this should be the type of mat? */
995     ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr);
996     if (!rank) {
997       ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr);
998     } else {
999       ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr);
1000     }
1001     ierr = MatSetType(A,MATMPIBAIJ);CHKERRQ(ierr);
1002     ierr = MatMPIBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr);
1003     ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
1004     ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr);
1005 
1006     /* copy over the A part */
1007     Aloc = (Mat_SeqBAIJ*)baij->A->data;
1008     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1009     ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr);
1010 
1011     for (i=0; i<mbs; i++) {
1012       rvals[0] = bs*(baij->rstartbs + i);
1013       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1014       for (j=ai[i]; j<ai[i+1]; j++) {
1015         col = (baij->cstartbs+aj[j])*bs;
1016         for (k=0; k<bs; k++) {
1017           ierr      = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
1018           col++; a += bs;
1019         }
1020       }
1021     }
1022     /* copy over the B part */
1023     Aloc = (Mat_SeqBAIJ*)baij->B->data;
1024     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1025     for (i=0; i<mbs; i++) {
1026       rvals[0] = bs*(baij->rstartbs + i);
1027       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1028       for (j=ai[i]; j<ai[i+1]; j++) {
1029         col = baij->garray[aj[j]]*bs;
1030         for (k=0; k<bs; k++) {
1031           ierr      = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
1032           col++; a += bs;
1033         }
1034       }
1035     }
1036     ierr = PetscFree(rvals);CHKERRQ(ierr);
1037     ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1038     ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1039     /*
1040        Everyone has to call to draw the matrix since the graphics waits are
1041        synchronized across all processors that share the PetscDraw object
1042     */
1043     ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr);
1044     if (!rank) {
1045       ierr = PetscObjectSetName((PetscObject)((Mat_MPIBAIJ*)(A->data))->A,((PetscObject)mat)->name);CHKERRQ(ierr);
1046       /* Set the type name to MATMPIBAIJ so that the correct type can be printed out by PetscObjectPrintClassNamePrefixType() in MatView_SeqBAIJ_ASCII()*/
1047       PetscStrcpy(((PetscObject)((Mat_MPIBAIJ*)(A->data))->A)->type_name,MATMPIBAIJ);
1048       ierr = MatView(((Mat_MPIBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr);
1049     }
1050     ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr);
1051     ierr = MatDestroy(&A);CHKERRQ(ierr);
1052   }
1053   PetscFunctionReturn(0);
1054 }
1055 
1056 #undef __FUNCT__
1057 #define __FUNCT__ "MatView_MPIBAIJ_Binary"
1058 static PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat,PetscViewer viewer)
1059 {
1060   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)mat->data;
1061   Mat_SeqBAIJ    *A = (Mat_SeqBAIJ*)a->A->data;
1062   Mat_SeqBAIJ    *B = (Mat_SeqBAIJ*)a->B->data;
1063   PetscErrorCode ierr;
1064   PetscInt       i,*row_lens,*crow_lens,bs = mat->rmap->bs,j,k,bs2=a->bs2,header[4],nz,rlen;
1065   PetscInt       *range=0,nzmax,*column_indices,cnt,col,*garray = a->garray,cstart = mat->cmap->rstart/bs,len,pcnt,l,ll;
1066   int            fd;
1067   PetscScalar    *column_values;
1068   FILE           *file;
1069   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag;
1070   PetscInt       message_count,flowcontrolcount;
1071 
1072   PetscFunctionBegin;
1073   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr);
1074   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
1075   nz   = bs2*(A->nz + B->nz);
1076   rlen = mat->rmap->n;
1077   if (!rank) {
1078     header[0] = MAT_FILE_CLASSID;
1079     header[1] = mat->rmap->N;
1080     header[2] = mat->cmap->N;
1081 
1082     ierr = MPI_Reduce(&nz,&header[3],1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1083     ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
1084     ierr = PetscBinaryWrite(fd,header,4,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1085     /* get largest number of rows any processor has */
1086     range = mat->rmap->range;
1087     for (i=1; i<size; i++) {
1088       rlen = PetscMax(rlen,range[i+1] - range[i]);
1089     }
1090   } else {
1091     ierr = MPI_Reduce(&nz,0,1,MPIU_INT,MPI_SUM,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1092   }
1093 
1094   ierr = PetscMalloc((rlen/bs)*sizeof(PetscInt),&crow_lens);CHKERRQ(ierr);
1095   /* compute lengths of each row  */
1096   for (i=0; i<a->mbs; i++) {
1097     crow_lens[i] = A->i[i+1] - A->i[i] + B->i[i+1] - B->i[i];
1098   }
1099   /* store the row lengths to the file */
1100   ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr);
1101   if (!rank) {
1102     MPI_Status status;
1103     ierr = PetscMalloc(rlen*sizeof(PetscInt),&row_lens);CHKERRQ(ierr);
1104     rlen = (range[1] - range[0])/bs;
1105     for (i=0; i<rlen; i++) {
1106       for (j=0; j<bs; j++) {
1107         row_lens[i*bs+j] = bs*crow_lens[i];
1108       }
1109     }
1110     ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1111     for (i=1; i<size; i++) {
1112       rlen = (range[i+1] - range[i])/bs;
1113       ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr);
1114       ierr = MPI_Recv(crow_lens,rlen,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1115       for (k=0; k<rlen; k++) {
1116         for (j=0; j<bs; j++) {
1117           row_lens[k*bs+j] = bs*crow_lens[k];
1118         }
1119       }
1120       ierr = PetscBinaryWrite(fd,row_lens,bs*rlen,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1121     }
1122     ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr);
1123     ierr = PetscFree(row_lens);CHKERRQ(ierr);
1124   } else {
1125     ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr);
1126     ierr = MPI_Send(crow_lens,mat->rmap->n/bs,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1127     ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr);
1128   }
1129   ierr = PetscFree(crow_lens);CHKERRQ(ierr);
1130 
1131   /* load up the local column indices. Include for all rows not just one for each block row since process 0 does not have the
1132      information needed to make it for each row from a block row. This does require more communication but still not more than
1133      the communication needed for the nonzero values  */
1134   nzmax = nz; /*  space a largest processor needs */
1135   ierr  = MPI_Reduce(&nz,&nzmax,1,MPIU_INT,MPI_MAX,0,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1136   ierr  = PetscMalloc(nzmax*sizeof(PetscInt),&column_indices);CHKERRQ(ierr);
1137   cnt   = 0;
1138   for (i=0; i<a->mbs; i++) {
1139     pcnt = cnt;
1140     for (j=B->i[i]; j<B->i[i+1]; j++) {
1141       if ((col = garray[B->j[j]]) > cstart) break;
1142       for (l=0; l<bs; l++) {
1143         column_indices[cnt++] = bs*col+l;
1144       }
1145     }
1146     for (k=A->i[i]; k<A->i[i+1]; k++) {
1147       for (l=0; l<bs; l++) {
1148         column_indices[cnt++] = bs*(A->j[k] + cstart)+l;
1149       }
1150     }
1151     for (; j<B->i[i+1]; j++) {
1152       for (l=0; l<bs; l++) {
1153         column_indices[cnt++] = bs*garray[B->j[j]]+l;
1154       }
1155     }
1156     len = cnt - pcnt;
1157     for (k=1; k<bs; k++) {
1158       ierr = PetscMemcpy(&column_indices[cnt],&column_indices[pcnt],len*sizeof(PetscInt));CHKERRQ(ierr);
1159       cnt += len;
1160     }
1161   }
1162   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_LIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1163 
1164   /* store the columns to the file */
1165   ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr);
1166   if (!rank) {
1167     MPI_Status status;
1168     ierr = PetscBinaryWrite(fd,column_indices,nz,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1169     for (i=1; i<size; i++) {
1170       ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr);
1171       ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1172       ierr = MPI_Recv(column_indices,cnt,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1173       ierr = PetscBinaryWrite(fd,column_indices,cnt,PETSC_INT,PETSC_TRUE);CHKERRQ(ierr);
1174     }
1175     ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr);
1176   } else {
1177     ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr);
1178     ierr = MPI_Send(&cnt,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1179     ierr = MPI_Send(column_indices,cnt,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1180     ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr);
1181   }
1182   ierr = PetscFree(column_indices);CHKERRQ(ierr);
1183 
1184   /* load up the numerical values */
1185   ierr = PetscMalloc(nzmax*sizeof(PetscScalar),&column_values);CHKERRQ(ierr);
1186   cnt  = 0;
1187   for (i=0; i<a->mbs; i++) {
1188     rlen = bs*(B->i[i+1] - B->i[i] + A->i[i+1] - A->i[i]);
1189     for (j=B->i[i]; j<B->i[i+1]; j++) {
1190       if (garray[B->j[j]] > cstart) break;
1191       for (l=0; l<bs; l++) {
1192         for (ll=0; ll<bs; ll++) {
1193           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1194         }
1195       }
1196       cnt += bs;
1197     }
1198     for (k=A->i[i]; k<A->i[i+1]; k++) {
1199       for (l=0; l<bs; l++) {
1200         for (ll=0; ll<bs; ll++) {
1201           column_values[cnt + l*rlen + ll] = A->a[bs2*k+l+bs*ll];
1202         }
1203       }
1204       cnt += bs;
1205     }
1206     for (; j<B->i[i+1]; j++) {
1207       for (l=0; l<bs; l++) {
1208         for (ll=0; ll<bs; ll++) {
1209           column_values[cnt + l*rlen + ll] = B->a[bs2*j+l+bs*ll];
1210         }
1211       }
1212       cnt += bs;
1213     }
1214     cnt += (bs-1)*rlen;
1215   }
1216   if (cnt != nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal PETSc error: cnt = %D nz = %D",cnt,nz);
1217 
1218   /* store the column values to the file */
1219   ierr = PetscViewerFlowControlStart(viewer,&message_count,&flowcontrolcount);CHKERRQ(ierr);
1220   if (!rank) {
1221     MPI_Status status;
1222     ierr = PetscBinaryWrite(fd,column_values,nz,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr);
1223     for (i=1; i<size; i++) {
1224       ierr = PetscViewerFlowControlStepMaster(viewer,i,&message_count,flowcontrolcount);CHKERRQ(ierr);
1225       ierr = MPI_Recv(&cnt,1,MPIU_INT,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1226       ierr = MPI_Recv(column_values,cnt,MPIU_SCALAR,i,tag,PetscObjectComm((PetscObject)mat),&status);CHKERRQ(ierr);
1227       ierr = PetscBinaryWrite(fd,column_values,cnt,PETSC_SCALAR,PETSC_TRUE);CHKERRQ(ierr);
1228     }
1229     ierr = PetscViewerFlowControlEndMaster(viewer,&message_count);CHKERRQ(ierr);
1230   } else {
1231     ierr = PetscViewerFlowControlStepWorker(viewer,rank,&message_count);CHKERRQ(ierr);
1232     ierr = MPI_Send(&nz,1,MPIU_INT,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1233     ierr = MPI_Send(column_values,nz,MPIU_SCALAR,0,tag,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
1234     ierr = PetscViewerFlowControlEndWorker(viewer,&message_count);CHKERRQ(ierr);
1235   }
1236   ierr = PetscFree(column_values);CHKERRQ(ierr);
1237 
1238   ierr = PetscViewerBinaryGetInfoPointer(viewer,&file);CHKERRQ(ierr);
1239   if (file) {
1240     fprintf(file,"-matload_block_size %d\n",(int)mat->rmap->bs);
1241   }
1242   PetscFunctionReturn(0);
1243 }
1244 
1245 #undef __FUNCT__
1246 #define __FUNCT__ "MatView_MPIBAIJ"
1247 PetscErrorCode MatView_MPIBAIJ(Mat mat,PetscViewer viewer)
1248 {
1249   PetscErrorCode ierr;
1250   PetscBool      iascii,isdraw,issocket,isbinary;
1251 
1252   PetscFunctionBegin;
1253   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
1254   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
1255   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr);
1256   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
1257   if (iascii || isdraw || issocket) {
1258     ierr = MatView_MPIBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr);
1259   } else if (isbinary) {
1260     ierr = MatView_MPIBAIJ_Binary(mat,viewer);CHKERRQ(ierr);
1261   }
1262   PetscFunctionReturn(0);
1263 }
1264 
1265 #undef __FUNCT__
1266 #define __FUNCT__ "MatDestroy_MPIBAIJ"
1267 PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
1268 {
1269   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
1270   PetscErrorCode ierr;
1271 
1272   PetscFunctionBegin;
1273 #if defined(PETSC_USE_LOG)
1274   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
1275 #endif
1276   ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr);
1277   ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr);
1278   ierr = MatDestroy(&baij->A);CHKERRQ(ierr);
1279   ierr = MatDestroy(&baij->B);CHKERRQ(ierr);
1280 #if defined(PETSC_USE_CTABLE)
1281   ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr);
1282 #else
1283   ierr = PetscFree(baij->colmap);CHKERRQ(ierr);
1284 #endif
1285   ierr = PetscFree(baij->garray);CHKERRQ(ierr);
1286   ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr);
1287   ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr);
1288   ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr);
1289   ierr = PetscFree(baij->barray);CHKERRQ(ierr);
1290   ierr = PetscFree2(baij->hd,baij->ht);CHKERRQ(ierr);
1291   ierr = PetscFree(baij->rangebs);CHKERRQ(ierr);
1292   ierr = PetscFree(mat->data);CHKERRQ(ierr);
1293 
1294   ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr);
1295   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr);
1296   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr);
1297   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr);
1298   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocation_C",NULL);CHKERRQ(ierr);
1299   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPIBAIJSetPreallocationCSR_C",NULL);CHKERRQ(ierr);
1300   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);CHKERRQ(ierr);
1301   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatSetHashTableFactor_C",NULL);CHKERRQ(ierr);
1302   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpisbaij_C",NULL);CHKERRQ(ierr);
1303   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpibaij_mpibstrm_C",NULL);CHKERRQ(ierr);
1304   PetscFunctionReturn(0);
1305 }
1306 
1307 #undef __FUNCT__
1308 #define __FUNCT__ "MatMult_MPIBAIJ"
1309 PetscErrorCode MatMult_MPIBAIJ(Mat A,Vec xx,Vec yy)
1310 {
1311   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1312   PetscErrorCode ierr;
1313   PetscInt       nt;
1314 
1315   PetscFunctionBegin;
1316   ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr);
1317   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
1318   ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr);
1319   if (nt != A->rmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
1320   ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1321   ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr);
1322   ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1323   ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr);
1324   PetscFunctionReturn(0);
1325 }
1326 
1327 #undef __FUNCT__
1328 #define __FUNCT__ "MatMultAdd_MPIBAIJ"
1329 PetscErrorCode MatMultAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1330 {
1331   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1332   PetscErrorCode ierr;
1333 
1334   PetscFunctionBegin;
1335   ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1336   ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr);
1337   ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1338   ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr);
1339   PetscFunctionReturn(0);
1340 }
1341 
1342 #undef __FUNCT__
1343 #define __FUNCT__ "MatMultTranspose_MPIBAIJ"
1344 PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A,Vec xx,Vec yy)
1345 {
1346   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1347   PetscErrorCode ierr;
1348   PetscBool      merged;
1349 
1350   PetscFunctionBegin;
1351   ierr = VecScatterGetMerged(a->Mvctx,&merged);CHKERRQ(ierr);
1352   /* do nondiagonal part */
1353   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr);
1354   if (!merged) {
1355     /* send it on its way */
1356     ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1357     /* do local part */
1358     ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr);
1359     /* receive remote parts: note this assumes the values are not actually */
1360     /* inserted in yy until the next line */
1361     ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1362   } else {
1363     /* do local part */
1364     ierr = (*a->A->ops->multtranspose)(a->A,xx,yy);CHKERRQ(ierr);
1365     /* send it on its way */
1366     ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1367     /* values actually were received in the Begin() but we need to call this nop */
1368     ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1369   }
1370   PetscFunctionReturn(0);
1371 }
1372 
1373 #undef __FUNCT__
1374 #define __FUNCT__ "MatMultTransposeAdd_MPIBAIJ"
1375 PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
1376 {
1377   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1378   PetscErrorCode ierr;
1379 
1380   PetscFunctionBegin;
1381   /* do nondiagonal part */
1382   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr);
1383   /* send it on its way */
1384   ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1385   /* do local part */
1386   ierr = (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);CHKERRQ(ierr);
1387   /* receive remote parts: note this assumes the values are not actually */
1388   /* inserted in yy until the next line, which is true for my implementation*/
1389   /* but is not perhaps always true. */
1390   ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
1391   PetscFunctionReturn(0);
1392 }
1393 
1394 /*
1395   This only works correctly for square matrices where the subblock A->A is the
1396    diagonal block
1397 */
1398 #undef __FUNCT__
1399 #define __FUNCT__ "MatGetDiagonal_MPIBAIJ"
1400 PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A,Vec v)
1401 {
1402   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1403   PetscErrorCode ierr;
1404 
1405   PetscFunctionBegin;
1406   if (A->rmap->N != A->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
1407   ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr);
1408   PetscFunctionReturn(0);
1409 }
1410 
1411 #undef __FUNCT__
1412 #define __FUNCT__ "MatScale_MPIBAIJ"
1413 PetscErrorCode MatScale_MPIBAIJ(Mat A,PetscScalar aa)
1414 {
1415   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1416   PetscErrorCode ierr;
1417 
1418   PetscFunctionBegin;
1419   ierr = MatScale(a->A,aa);CHKERRQ(ierr);
1420   ierr = MatScale(a->B,aa);CHKERRQ(ierr);
1421   PetscFunctionReturn(0);
1422 }
1423 
1424 #undef __FUNCT__
1425 #define __FUNCT__ "MatGetRow_MPIBAIJ"
1426 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1427 {
1428   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
1429   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
1430   PetscErrorCode ierr;
1431   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
1432   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
1433   PetscInt       *cmap,*idx_p,cstart = mat->cstartbs;
1434 
1435   PetscFunctionBegin;
1436   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1437   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
1438   mat->getrowactive = PETSC_TRUE;
1439 
1440   if (!mat->rowvalues && (idx || v)) {
1441     /*
1442         allocate enough space to hold information from the longest row.
1443     */
1444     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ*)mat->A->data,*Ba = (Mat_SeqBAIJ*)mat->B->data;
1445     PetscInt    max = 1,mbs = mat->mbs,tmp;
1446     for (i=0; i<mbs; i++) {
1447       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i];
1448       if (max < tmp) max = tmp;
1449     }
1450     ierr = PetscMalloc2(max*bs2,PetscScalar,&mat->rowvalues,max*bs2,PetscInt,&mat->rowindices);CHKERRQ(ierr);
1451   }
1452   lrow = row - brstart;
1453 
1454   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1455   if (!v)   {pvA = 0; pvB = 0;}
1456   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1457   ierr  = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr);
1458   ierr  = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr);
1459   nztot = nzA + nzB;
1460 
1461   cmap = mat->garray;
1462   if (v  || idx) {
1463     if (nztot) {
1464       /* Sort by increasing column numbers, assuming A and B already sorted */
1465       PetscInt imark = -1;
1466       if (v) {
1467         *v = v_p = mat->rowvalues;
1468         for (i=0; i<nzB; i++) {
1469           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1470           else break;
1471         }
1472         imark = i;
1473         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1474         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1475       }
1476       if (idx) {
1477         *idx = idx_p = mat->rowindices;
1478         if (imark > -1) {
1479           for (i=0; i<imark; i++) {
1480             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1481           }
1482         } else {
1483           for (i=0; i<nzB; i++) {
1484             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1485             else break;
1486           }
1487           imark = i;
1488         }
1489         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1490         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1491       }
1492     } else {
1493       if (idx) *idx = 0;
1494       if (v)   *v   = 0;
1495     }
1496   }
1497   *nz  = nztot;
1498   ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr);
1499   ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr);
1500   PetscFunctionReturn(0);
1501 }
1502 
1503 #undef __FUNCT__
1504 #define __FUNCT__ "MatRestoreRow_MPIBAIJ"
1505 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1506 {
1507   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*)mat->data;
1508 
1509   PetscFunctionBegin;
1510   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow not called");
1511   baij->getrowactive = PETSC_FALSE;
1512   PetscFunctionReturn(0);
1513 }
1514 
1515 #undef __FUNCT__
1516 #define __FUNCT__ "MatZeroEntries_MPIBAIJ"
1517 PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
1518 {
1519   Mat_MPIBAIJ    *l = (Mat_MPIBAIJ*)A->data;
1520   PetscErrorCode ierr;
1521 
1522   PetscFunctionBegin;
1523   ierr = MatZeroEntries(l->A);CHKERRQ(ierr);
1524   ierr = MatZeroEntries(l->B);CHKERRQ(ierr);
1525   PetscFunctionReturn(0);
1526 }
1527 
1528 #undef __FUNCT__
1529 #define __FUNCT__ "MatGetInfo_MPIBAIJ"
1530 PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1531 {
1532   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)matin->data;
1533   Mat            A  = a->A,B = a->B;
1534   PetscErrorCode ierr;
1535   PetscReal      isend[5],irecv[5];
1536 
1537   PetscFunctionBegin;
1538   info->block_size = (PetscReal)matin->rmap->bs;
1539 
1540   ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr);
1541 
1542   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1543   isend[3] = info->memory;  isend[4] = info->mallocs;
1544 
1545   ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr);
1546 
1547   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1548   isend[3] += info->memory;  isend[4] += info->mallocs;
1549 
1550   if (flag == MAT_LOCAL) {
1551     info->nz_used      = isend[0];
1552     info->nz_allocated = isend[1];
1553     info->nz_unneeded  = isend[2];
1554     info->memory       = isend[3];
1555     info->mallocs      = isend[4];
1556   } else if (flag == MAT_GLOBAL_MAX) {
1557     ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr);
1558 
1559     info->nz_used      = irecv[0];
1560     info->nz_allocated = irecv[1];
1561     info->nz_unneeded  = irecv[2];
1562     info->memory       = irecv[3];
1563     info->mallocs      = irecv[4];
1564   } else if (flag == MAT_GLOBAL_SUM) {
1565     ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr);
1566 
1567     info->nz_used      = irecv[0];
1568     info->nz_allocated = irecv[1];
1569     info->nz_unneeded  = irecv[2];
1570     info->memory       = irecv[3];
1571     info->mallocs      = irecv[4];
1572   } else SETERRQ1(PetscObjectComm((PetscObject)matin),PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1573   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1574   info->fill_ratio_needed = 0;
1575   info->factor_mallocs    = 0;
1576   PetscFunctionReturn(0);
1577 }
1578 
1579 #undef __FUNCT__
1580 #define __FUNCT__ "MatSetOption_MPIBAIJ"
1581 PetscErrorCode MatSetOption_MPIBAIJ(Mat A,MatOption op,PetscBool flg)
1582 {
1583   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1584   PetscErrorCode ierr;
1585 
1586   PetscFunctionBegin;
1587   switch (op) {
1588   case MAT_NEW_NONZERO_LOCATIONS:
1589   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1590   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1591   case MAT_KEEP_NONZERO_PATTERN:
1592   case MAT_NEW_NONZERO_LOCATION_ERR:
1593     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1594     ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr);
1595     break;
1596   case MAT_ROW_ORIENTED:
1597     a->roworiented = flg;
1598 
1599     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1600     ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr);
1601     break;
1602   case MAT_NEW_DIAGONALS:
1603     ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr);
1604     break;
1605   case MAT_IGNORE_OFF_PROC_ENTRIES:
1606     a->donotstash = flg;
1607     break;
1608   case MAT_USE_HASH_TABLE:
1609     a->ht_flag = flg;
1610     break;
1611   case MAT_SYMMETRIC:
1612   case MAT_STRUCTURALLY_SYMMETRIC:
1613   case MAT_HERMITIAN:
1614   case MAT_SYMMETRY_ETERNAL:
1615     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1616     break;
1617   default:
1618     SETERRQ1(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"unknown option %d",op);
1619   }
1620   PetscFunctionReturn(0);
1621 }
1622 
1623 #undef __FUNCT__
1624 #define __FUNCT__ "MatTranspose_MPIBAIJ"
1625 PetscErrorCode MatTranspose_MPIBAIJ(Mat A,MatReuse reuse,Mat *matout)
1626 {
1627   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)A->data;
1628   Mat_SeqBAIJ    *Aloc;
1629   Mat            B;
1630   PetscErrorCode ierr;
1631   PetscInt       M =A->rmap->N,N=A->cmap->N,*ai,*aj,i,*rvals,j,k,col;
1632   PetscInt       bs=A->rmap->bs,mbs=baij->mbs;
1633   MatScalar      *a;
1634 
1635   PetscFunctionBegin;
1636   if (reuse == MAT_REUSE_MATRIX && A == *matout && M != N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_SIZ,"Square matrix only for in-place");
1637   if (reuse == MAT_INITIAL_MATRIX || *matout == A) {
1638     ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
1639     ierr = MatSetSizes(B,A->cmap->n,A->rmap->n,N,M);CHKERRQ(ierr);
1640     ierr = MatSetType(B,((PetscObject)A)->type_name);CHKERRQ(ierr);
1641     /* Do not know preallocation information, but must set block size */
1642     ierr = MatMPIBAIJSetPreallocation(B,A->rmap->bs,PETSC_DECIDE,NULL,PETSC_DECIDE,NULL);CHKERRQ(ierr);
1643   } else {
1644     B = *matout;
1645   }
1646 
1647   /* copy over the A part */
1648   Aloc = (Mat_SeqBAIJ*)baij->A->data;
1649   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1650   ierr = PetscMalloc(bs*sizeof(PetscInt),&rvals);CHKERRQ(ierr);
1651 
1652   for (i=0; i<mbs; i++) {
1653     rvals[0] = bs*(baij->rstartbs + i);
1654     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1655     for (j=ai[i]; j<ai[i+1]; j++) {
1656       col = (baij->cstartbs+aj[j])*bs;
1657       for (k=0; k<bs; k++) {
1658         ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
1659 
1660         col++; a += bs;
1661       }
1662     }
1663   }
1664   /* copy over the B part */
1665   Aloc = (Mat_SeqBAIJ*)baij->B->data;
1666   ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
1667   for (i=0; i<mbs; i++) {
1668     rvals[0] = bs*(baij->rstartbs + i);
1669     for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
1670     for (j=ai[i]; j<ai[i+1]; j++) {
1671       col = baij->garray[aj[j]]*bs;
1672       for (k=0; k<bs; k++) {
1673         ierr = MatSetValues_MPIBAIJ(B,1,&col,bs,rvals,a,INSERT_VALUES);CHKERRQ(ierr);
1674         col++;
1675         a += bs;
1676       }
1677     }
1678   }
1679   ierr = PetscFree(rvals);CHKERRQ(ierr);
1680   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1681   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1682 
1683   if (reuse == MAT_INITIAL_MATRIX || *matout != A) *matout = B;
1684   else {
1685     ierr = MatHeaderMerge(A,B);CHKERRQ(ierr);
1686   }
1687   PetscFunctionReturn(0);
1688 }
1689 
1690 #undef __FUNCT__
1691 #define __FUNCT__ "MatDiagonalScale_MPIBAIJ"
1692 PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat,Vec ll,Vec rr)
1693 {
1694   Mat_MPIBAIJ    *baij = (Mat_MPIBAIJ*)mat->data;
1695   Mat            a     = baij->A,b = baij->B;
1696   PetscErrorCode ierr;
1697   PetscInt       s1,s2,s3;
1698 
1699   PetscFunctionBegin;
1700   ierr = MatGetLocalSize(mat,&s2,&s3);CHKERRQ(ierr);
1701   if (rr) {
1702     ierr = VecGetLocalSize(rr,&s1);CHKERRQ(ierr);
1703     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
1704     /* Overlap communication with computation. */
1705     ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1706   }
1707   if (ll) {
1708     ierr = VecGetLocalSize(ll,&s1);CHKERRQ(ierr);
1709     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
1710     ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr);
1711   }
1712   /* scale  the diagonal block */
1713   ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr);
1714 
1715   if (rr) {
1716     /* Do a scatter end and then right scale the off-diagonal block */
1717     ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1718     ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr);
1719   }
1720   PetscFunctionReturn(0);
1721 }
1722 
1723 #undef __FUNCT__
1724 #define __FUNCT__ "MatZeroRows_MPIBAIJ"
1725 PetscErrorCode MatZeroRows_MPIBAIJ(Mat A,PetscInt N,const PetscInt rows[],PetscScalar diag,Vec x,Vec b)
1726 {
1727   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ*)A->data;
1728   PetscErrorCode    ierr;
1729   PetscMPIInt       imdex,size = l->size,n,rank = l->rank;
1730   PetscInt          i,*owners = A->rmap->range;
1731   PetscInt          *nprocs,j,idx,nsends,row;
1732   PetscInt          nmax,*svalues,*starts,*owner,nrecvs;
1733   PetscInt          *rvalues,tag = ((PetscObject)A)->tag,count,base,slen,*source,lastidx = -1;
1734   PetscInt          *lens,*lrows,*values,rstart_bs=A->rmap->rstart;
1735   MPI_Comm          comm;
1736   MPI_Request       *send_waits,*recv_waits;
1737   MPI_Status        recv_status,*send_status;
1738   const PetscScalar *xx;
1739   PetscScalar       *bb;
1740 #if defined(PETSC_DEBUG)
1741   PetscBool         found = PETSC_FALSE;
1742 #endif
1743 
1744   PetscFunctionBegin;
1745   ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr);
1746   /*  first count number of contributors to each processor */
1747   ierr = PetscMalloc(2*size*sizeof(PetscInt),&nprocs);CHKERRQ(ierr);
1748   ierr = PetscMemzero(nprocs,2*size*sizeof(PetscInt));CHKERRQ(ierr);
1749   ierr = PetscMalloc((N+1)*sizeof(PetscInt),&owner);CHKERRQ(ierr);  /* see note*/
1750   j    = 0;
1751   for (i=0; i<N; i++) {
1752     if (lastidx > (idx = rows[i])) j = 0;
1753     lastidx = idx;
1754     for (; j<size; j++) {
1755       if (idx >= owners[j] && idx < owners[j+1]) {
1756         nprocs[2*j]++;
1757         nprocs[2*j+1] = 1;
1758         owner[i]      = j;
1759 #if defined(PETSC_DEBUG)
1760         found = PETSC_TRUE;
1761 #endif
1762         break;
1763       }
1764     }
1765 #if defined(PETSC_DEBUG)
1766     if (!found) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Index out of range");
1767     found = PETSC_FALSE;
1768 #endif
1769   }
1770   nsends = 0;  for (i=0; i<size; i++) nsends += nprocs[2*i+1];
1771 
1772   if (A->nooffproczerorows) {
1773     if (nsends > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"You called MatSetOption(,MAT_NO_OFF_PROC_ZERO_ROWS,PETSC_TRUE) but set an off process zero row");
1774     nrecvs = nsends;
1775     nmax   = N;
1776   } else {
1777     /* inform other processors of number of messages and max length*/
1778     ierr = PetscMaxSum(comm,nprocs,&nmax,&nrecvs);CHKERRQ(ierr);
1779   }
1780 
1781   /* post receives:   */
1782   ierr = PetscMalloc((nrecvs+1)*(nmax+1)*sizeof(PetscInt),&rvalues);CHKERRQ(ierr);
1783   ierr = PetscMalloc((nrecvs+1)*sizeof(MPI_Request),&recv_waits);CHKERRQ(ierr);
1784   for (i=0; i<nrecvs; i++) {
1785     ierr = MPI_Irecv(rvalues+nmax*i,nmax,MPIU_INT,MPI_ANY_SOURCE,tag,comm,recv_waits+i);CHKERRQ(ierr);
1786   }
1787 
1788   /* do sends:
1789      1) starts[i] gives the starting index in svalues for stuff going to
1790      the ith processor
1791   */
1792   ierr      = PetscMalloc((N+1)*sizeof(PetscInt),&svalues);CHKERRQ(ierr);
1793   ierr      = PetscMalloc((nsends+1)*sizeof(MPI_Request),&send_waits);CHKERRQ(ierr);
1794   ierr      = PetscMalloc((size+1)*sizeof(PetscInt),&starts);CHKERRQ(ierr);
1795   starts[0] = 0;
1796   for (i=1; i<size; i++) starts[i] = starts[i-1] + nprocs[2*i-2];
1797   for (i=0; i<N; i++) {
1798     svalues[starts[owner[i]]++] = rows[i];
1799   }
1800 
1801   starts[0] = 0;
1802   for (i=1; i<size+1; i++) starts[i] = starts[i-1] + nprocs[2*i-2];
1803   count = 0;
1804   for (i=0; i<size; i++) {
1805     if (nprocs[2*i+1]) {
1806       ierr = MPI_Isend(svalues+starts[i],nprocs[2*i],MPIU_INT,i,tag,comm,send_waits+count++);CHKERRQ(ierr);
1807     }
1808   }
1809   ierr = PetscFree(starts);CHKERRQ(ierr);
1810 
1811   base = owners[rank];
1812 
1813   /*  wait on receives */
1814   ierr  = PetscMalloc2(nrecvs+1,PetscInt,&lens,nrecvs+1,PetscInt,&source);CHKERRQ(ierr);
1815   count = nrecvs;
1816   slen  = 0;
1817   while (count) {
1818     ierr = MPI_Waitany(nrecvs,recv_waits,&imdex,&recv_status);CHKERRQ(ierr);
1819     /* unpack receives into our local space */
1820     ierr = MPI_Get_count(&recv_status,MPIU_INT,&n);CHKERRQ(ierr);
1821 
1822     source[imdex] = recv_status.MPI_SOURCE;
1823     lens[imdex]   = n;
1824     slen         += n;
1825     count--;
1826   }
1827   ierr = PetscFree(recv_waits);CHKERRQ(ierr);
1828 
1829   /* move the data into the send scatter */
1830   ierr  = PetscMalloc((slen+1)*sizeof(PetscInt),&lrows);CHKERRQ(ierr);
1831   count = 0;
1832   for (i=0; i<nrecvs; i++) {
1833     values = rvalues + i*nmax;
1834     for (j=0; j<lens[i]; j++) {
1835       lrows[count++] = values[j] - base;
1836     }
1837   }
1838   ierr = PetscFree(rvalues);CHKERRQ(ierr);
1839   ierr = PetscFree2(lens,source);CHKERRQ(ierr);
1840   ierr = PetscFree(owner);CHKERRQ(ierr);
1841   ierr = PetscFree(nprocs);CHKERRQ(ierr);
1842 
1843   /* fix right hand side if needed */
1844   if (x && b) {
1845     ierr = VecGetArrayRead(x,&xx);CHKERRQ(ierr);
1846     ierr = VecGetArray(b,&bb);CHKERRQ(ierr);
1847     for (i=0; i<slen; i++) {
1848       bb[lrows[i]] = diag*xx[lrows[i]];
1849     }
1850     ierr = VecRestoreArrayRead(x,&xx);CHKERRQ(ierr);
1851     ierr = VecRestoreArray(b,&bb);CHKERRQ(ierr);
1852   }
1853 
1854   /* actually zap the local rows */
1855   /*
1856         Zero the required rows. If the "diagonal block" of the matrix
1857      is square and the user wishes to set the diagonal we use separate
1858      code so that MatSetValues() is not called for each diagonal allocating
1859      new memory, thus calling lots of mallocs and slowing things down.
1860 
1861   */
1862   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
1863   ierr = MatZeroRows_SeqBAIJ(l->B,slen,lrows,0.0,0,0);CHKERRQ(ierr);
1864   if ((diag != 0.0) && (l->A->rmap->N == l->A->cmap->N)) {
1865     ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,diag,0,0);CHKERRQ(ierr);
1866   } else if (diag != 0.0) {
1867     ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr);
1868     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\
1869        MAT_NEW_NONZERO_LOCATIONS,MAT_NEW_NONZERO_LOCATION_ERR,MAT_NEW_NONZERO_ALLOCATION_ERR");
1870     for (i=0; i<slen; i++) {
1871       row  = lrows[i] + rstart_bs;
1872       ierr = MatSetValues(A,1,&row,1,&row,&diag,INSERT_VALUES);CHKERRQ(ierr);
1873     }
1874     ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1875     ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1876   } else {
1877     ierr = MatZeroRows_SeqBAIJ(l->A,slen,lrows,0.0,0,0);CHKERRQ(ierr);
1878   }
1879 
1880   ierr = PetscFree(lrows);CHKERRQ(ierr);
1881 
1882   /* wait on sends */
1883   if (nsends) {
1884     ierr = PetscMalloc(nsends*sizeof(MPI_Status),&send_status);CHKERRQ(ierr);
1885     ierr = MPI_Waitall(nsends,send_waits,send_status);CHKERRQ(ierr);
1886     ierr = PetscFree(send_status);CHKERRQ(ierr);
1887   }
1888   ierr = PetscFree(send_waits);CHKERRQ(ierr);
1889   ierr = PetscFree(svalues);CHKERRQ(ierr);
1890   PetscFunctionReturn(0);
1891 }
1892 
1893 #undef __FUNCT__
1894 #define __FUNCT__ "MatSetUnfactored_MPIBAIJ"
1895 PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
1896 {
1897   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1898   PetscErrorCode ierr;
1899 
1900   PetscFunctionBegin;
1901   ierr = MatSetUnfactored(a->A);CHKERRQ(ierr);
1902   PetscFunctionReturn(0);
1903 }
1904 
1905 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat,MatDuplicateOption,Mat*);
1906 
1907 #undef __FUNCT__
1908 #define __FUNCT__ "MatEqual_MPIBAIJ"
1909 PetscErrorCode MatEqual_MPIBAIJ(Mat A,Mat B,PetscBool  *flag)
1910 {
1911   Mat_MPIBAIJ    *matB = (Mat_MPIBAIJ*)B->data,*matA = (Mat_MPIBAIJ*)A->data;
1912   Mat            a,b,c,d;
1913   PetscBool      flg;
1914   PetscErrorCode ierr;
1915 
1916   PetscFunctionBegin;
1917   a = matA->A; b = matA->B;
1918   c = matB->A; d = matB->B;
1919 
1920   ierr = MatEqual(a,c,&flg);CHKERRQ(ierr);
1921   if (flg) {
1922     ierr = MatEqual(b,d,&flg);CHKERRQ(ierr);
1923   }
1924   ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
1925   PetscFunctionReturn(0);
1926 }
1927 
1928 #undef __FUNCT__
1929 #define __FUNCT__ "MatCopy_MPIBAIJ"
1930 PetscErrorCode MatCopy_MPIBAIJ(Mat A,Mat B,MatStructure str)
1931 {
1932   PetscErrorCode ierr;
1933   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1934   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
1935 
1936   PetscFunctionBegin;
1937   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1938   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1939     ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr);
1940   } else {
1941     ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr);
1942     ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr);
1943   }
1944   PetscFunctionReturn(0);
1945 }
1946 
1947 #undef __FUNCT__
1948 #define __FUNCT__ "MatSetUp_MPIBAIJ"
1949 PetscErrorCode MatSetUp_MPIBAIJ(Mat A)
1950 {
1951   PetscErrorCode ierr;
1952 
1953   PetscFunctionBegin;
1954   ierr =  MatMPIBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr);
1955   PetscFunctionReturn(0);
1956 }
1957 
1958 #undef __FUNCT__
1959 #define __FUNCT__ "MatAXPY_MPIBAIJ"
1960 PetscErrorCode MatAXPY_MPIBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1961 {
1962   PetscErrorCode ierr;
1963   Mat_MPIBAIJ    *xx=(Mat_MPIBAIJ*)X->data,*yy=(Mat_MPIBAIJ*)Y->data;
1964   PetscBLASInt   bnz,one=1;
1965   Mat_SeqBAIJ    *x,*y;
1966 
1967   PetscFunctionBegin;
1968   if (str == SAME_NONZERO_PATTERN) {
1969     PetscScalar alpha = a;
1970     x    = (Mat_SeqBAIJ*)xx->A->data;
1971     y    = (Mat_SeqBAIJ*)yy->A->data;
1972     ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr);
1973     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
1974     x    = (Mat_SeqBAIJ*)xx->B->data;
1975     y    = (Mat_SeqBAIJ*)yy->B->data;
1976     ierr = PetscBLASIntCast(x->nz,&bnz);CHKERRQ(ierr);
1977     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
1978   } else {
1979     ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr);
1980   }
1981   PetscFunctionReturn(0);
1982 }
1983 
1984 #undef __FUNCT__
1985 #define __FUNCT__ "MatRealPart_MPIBAIJ"
1986 PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
1987 {
1988   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
1989   PetscErrorCode ierr;
1990 
1991   PetscFunctionBegin;
1992   ierr = MatRealPart(a->A);CHKERRQ(ierr);
1993   ierr = MatRealPart(a->B);CHKERRQ(ierr);
1994   PetscFunctionReturn(0);
1995 }
1996 
1997 #undef __FUNCT__
1998 #define __FUNCT__ "MatImaginaryPart_MPIBAIJ"
1999 PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
2000 {
2001   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2002   PetscErrorCode ierr;
2003 
2004   PetscFunctionBegin;
2005   ierr = MatImaginaryPart(a->A);CHKERRQ(ierr);
2006   ierr = MatImaginaryPart(a->B);CHKERRQ(ierr);
2007   PetscFunctionReturn(0);
2008 }
2009 
2010 #undef __FUNCT__
2011 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ"
2012 PetscErrorCode MatGetSubMatrix_MPIBAIJ(Mat mat,IS isrow,IS iscol,MatReuse call,Mat *newmat)
2013 {
2014   PetscErrorCode ierr;
2015   IS             iscol_local;
2016   PetscInt       csize;
2017 
2018   PetscFunctionBegin;
2019   ierr = ISGetLocalSize(iscol,&csize);CHKERRQ(ierr);
2020   if (call == MAT_REUSE_MATRIX) {
2021     ierr = PetscObjectQuery((PetscObject)*newmat,"ISAllGather",(PetscObject*)&iscol_local);CHKERRQ(ierr);
2022     if (!iscol_local) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2023   } else {
2024     ierr = ISAllGather(iscol,&iscol_local);CHKERRQ(ierr);
2025   }
2026   ierr = MatGetSubMatrix_MPIBAIJ_Private(mat,isrow,iscol_local,csize,call,newmat);CHKERRQ(ierr);
2027   if (call == MAT_INITIAL_MATRIX) {
2028     ierr = PetscObjectCompose((PetscObject)*newmat,"ISAllGather",(PetscObject)iscol_local);CHKERRQ(ierr);
2029     ierr = ISDestroy(&iscol_local);CHKERRQ(ierr);
2030   }
2031   PetscFunctionReturn(0);
2032 }
2033 extern PetscErrorCode MatGetSubMatrices_MPIBAIJ_local(Mat,PetscInt,const IS[],const IS[],MatReuse,PetscBool*,PetscBool*,Mat*);
2034 #undef __FUNCT__
2035 #define __FUNCT__ "MatGetSubMatrix_MPIBAIJ_Private"
2036 /*
2037   Not great since it makes two copies of the submatrix, first an SeqBAIJ
2038   in local and then by concatenating the local matrices the end result.
2039   Writing it directly would be much like MatGetSubMatrices_MPIBAIJ()
2040 */
2041 PetscErrorCode MatGetSubMatrix_MPIBAIJ_Private(Mat mat,IS isrow,IS iscol,PetscInt csize,MatReuse call,Mat *newmat)
2042 {
2043   PetscErrorCode ierr;
2044   PetscMPIInt    rank,size;
2045   PetscInt       i,m,n,rstart,row,rend,nz,*cwork,j,bs;
2046   PetscInt       *ii,*jj,nlocal,*dlens,*olens,dlen,olen,jend,mglobal,ncol,nrow;
2047   Mat            M,Mreuse;
2048   MatScalar      *vwork,*aa;
2049   MPI_Comm       comm;
2050   IS             isrow_new, iscol_new;
2051   PetscBool      idflag,allrows, allcols;
2052   Mat_SeqBAIJ    *aij;
2053 
2054   PetscFunctionBegin;
2055   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
2056   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
2057   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
2058   /* The compression and expansion should be avoided. Doesn't point
2059      out errors, might change the indices, hence buggey */
2060   ierr = ISCompressIndicesGeneral(mat->rmap->N,mat->rmap->n,mat->rmap->bs,1,&isrow,&isrow_new);CHKERRQ(ierr);
2061   ierr = ISCompressIndicesGeneral(mat->cmap->N,mat->cmap->n,mat->cmap->bs,1,&iscol,&iscol_new);CHKERRQ(ierr);
2062 
2063   /* Check for special case: each processor gets entire matrix columns */
2064   ierr = ISIdentity(iscol,&idflag);CHKERRQ(ierr);
2065   ierr = ISGetLocalSize(iscol,&ncol);CHKERRQ(ierr);
2066   if (idflag && ncol == mat->cmap->N) allcols = PETSC_TRUE;
2067   else allcols = PETSC_FALSE;
2068 
2069   ierr = ISIdentity(isrow,&idflag);CHKERRQ(ierr);
2070   ierr = ISGetLocalSize(isrow,&nrow);CHKERRQ(ierr);
2071   if (idflag && nrow == mat->rmap->N) allrows = PETSC_TRUE;
2072   else allrows = PETSC_FALSE;
2073 
2074   if (call ==  MAT_REUSE_MATRIX) {
2075     ierr = PetscObjectQuery((PetscObject)*newmat,"SubMatrix",(PetscObject*)&Mreuse);CHKERRQ(ierr);
2076     if (!Mreuse) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Submatrix passed in was not used before, cannot reuse");
2077     ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_REUSE_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr);
2078   } else {
2079     ierr = MatGetSubMatrices_MPIBAIJ_local(mat,1,&isrow_new,&iscol_new,MAT_INITIAL_MATRIX,&allrows,&allcols,&Mreuse);CHKERRQ(ierr);
2080   }
2081   ierr = ISDestroy(&isrow_new);CHKERRQ(ierr);
2082   ierr = ISDestroy(&iscol_new);CHKERRQ(ierr);
2083   /*
2084       m - number of local rows
2085       n - number of columns (same on all processors)
2086       rstart - first row in new global matrix generated
2087   */
2088   ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr);
2089   ierr = MatGetSize(Mreuse,&m,&n);CHKERRQ(ierr);
2090   m    = m/bs;
2091   n    = n/bs;
2092 
2093   if (call == MAT_INITIAL_MATRIX) {
2094     aij = (Mat_SeqBAIJ*)(Mreuse)->data;
2095     ii  = aij->i;
2096     jj  = aij->j;
2097 
2098     /*
2099         Determine the number of non-zeros in the diagonal and off-diagonal
2100         portions of the matrix in order to do correct preallocation
2101     */
2102 
2103     /* first get start and end of "diagonal" columns */
2104     if (csize == PETSC_DECIDE) {
2105       ierr = ISGetSize(isrow,&mglobal);CHKERRQ(ierr);
2106       if (mglobal == n*bs) { /* square matrix */
2107         nlocal = m;
2108       } else {
2109         nlocal = n/size + ((n % size) > rank);
2110       }
2111     } else {
2112       nlocal = csize/bs;
2113     }
2114     ierr   = MPI_Scan(&nlocal,&rend,1,MPIU_INT,MPI_SUM,comm);CHKERRQ(ierr);
2115     rstart = rend - nlocal;
2116     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);
2117 
2118     /* next, compute all the lengths */
2119     ierr  = PetscMalloc2(m+1,PetscInt,&dlens,m+1,PetscInt,&olens);CHKERRQ(ierr);
2120     for (i=0; i<m; i++) {
2121       jend = ii[i+1] - ii[i];
2122       olen = 0;
2123       dlen = 0;
2124       for (j=0; j<jend; j++) {
2125         if (*jj < rstart || *jj >= rend) olen++;
2126         else dlen++;
2127         jj++;
2128       }
2129       olens[i] = olen;
2130       dlens[i] = dlen;
2131     }
2132     ierr = MatCreate(comm,&M);CHKERRQ(ierr);
2133     ierr = MatSetSizes(M,bs*m,bs*nlocal,PETSC_DECIDE,bs*n);CHKERRQ(ierr);
2134     ierr = MatSetType(M,((PetscObject)mat)->type_name);CHKERRQ(ierr);
2135     ierr = MatMPIBAIJSetPreallocation(M,bs,0,dlens,0,olens);CHKERRQ(ierr);
2136     ierr = PetscFree2(dlens,olens);CHKERRQ(ierr);
2137   } else {
2138     PetscInt ml,nl;
2139 
2140     M    = *newmat;
2141     ierr = MatGetLocalSize(M,&ml,&nl);CHKERRQ(ierr);
2142     if (ml != m) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Previous matrix must be same size/layout as request");
2143     ierr = MatZeroEntries(M);CHKERRQ(ierr);
2144     /*
2145          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
2146        rather than the slower MatSetValues().
2147     */
2148     M->was_assembled = PETSC_TRUE;
2149     M->assembled     = PETSC_FALSE;
2150   }
2151   ierr = MatSetOption(M,MAT_ROW_ORIENTED,PETSC_FALSE);CHKERRQ(ierr);
2152   ierr = MatGetOwnershipRange(M,&rstart,&rend);CHKERRQ(ierr);
2153   aij  = (Mat_SeqBAIJ*)(Mreuse)->data;
2154   ii   = aij->i;
2155   jj   = aij->j;
2156   aa   = aij->a;
2157   for (i=0; i<m; i++) {
2158     row   = rstart/bs + i;
2159     nz    = ii[i+1] - ii[i];
2160     cwork = jj;     jj += nz;
2161     vwork = aa;     aa += nz*bs*bs;
2162     ierr  = MatSetValuesBlocked_MPIBAIJ(M,1,&row,nz,cwork,vwork,INSERT_VALUES);CHKERRQ(ierr);
2163   }
2164 
2165   ierr    = MatAssemblyBegin(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2166   ierr    = MatAssemblyEnd(M,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2167   *newmat = M;
2168 
2169   /* save submatrix used in processor for next request */
2170   if (call ==  MAT_INITIAL_MATRIX) {
2171     ierr = PetscObjectCompose((PetscObject)M,"SubMatrix",(PetscObject)Mreuse);CHKERRQ(ierr);
2172     ierr = PetscObjectDereference((PetscObject)Mreuse);CHKERRQ(ierr);
2173   }
2174   PetscFunctionReturn(0);
2175 }
2176 
2177 #undef __FUNCT__
2178 #define __FUNCT__ "MatPermute_MPIBAIJ"
2179 PetscErrorCode MatPermute_MPIBAIJ(Mat A,IS rowp,IS colp,Mat *B)
2180 {
2181   MPI_Comm       comm,pcomm;
2182   PetscInt       first,rlocal_size,clocal_size,nrows;
2183   const PetscInt *rows;
2184   PetscMPIInt    size;
2185   IS             crowp,growp,irowp,lrowp,lcolp;
2186   PetscErrorCode ierr;
2187 
2188   PetscFunctionBegin;
2189   ierr = PetscObjectGetComm((PetscObject)A,&comm);CHKERRQ(ierr);
2190   /* make a collective version of 'rowp' */
2191   ierr = PetscObjectGetComm((PetscObject)rowp,&pcomm);CHKERRQ(ierr);
2192   if (pcomm==comm) {
2193     crowp = rowp;
2194   } else {
2195     ierr = ISGetSize(rowp,&nrows);CHKERRQ(ierr);
2196     ierr = ISGetIndices(rowp,&rows);CHKERRQ(ierr);
2197     ierr = ISCreateGeneral(comm,nrows,rows,PETSC_COPY_VALUES,&crowp);CHKERRQ(ierr);
2198     ierr = ISRestoreIndices(rowp,&rows);CHKERRQ(ierr);
2199   }
2200   /* collect the global row permutation and invert it */
2201   ierr = ISAllGather(crowp,&growp);CHKERRQ(ierr);
2202   ierr = ISSetPermutation(growp);CHKERRQ(ierr);
2203   if (pcomm!=comm) {
2204     ierr = ISDestroy(&crowp);CHKERRQ(ierr);
2205   }
2206   ierr = ISInvertPermutation(growp,PETSC_DECIDE,&irowp);CHKERRQ(ierr);
2207   ierr = ISDestroy(&growp);CHKERRQ(ierr);
2208   /* get the local target indices */
2209   ierr = MatGetOwnershipRange(A,&first,NULL);CHKERRQ(ierr);
2210   ierr = MatGetLocalSize(A,&rlocal_size,&clocal_size);CHKERRQ(ierr);
2211   ierr = ISGetIndices(irowp,&rows);CHKERRQ(ierr);
2212   ierr = ISCreateGeneral(MPI_COMM_SELF,rlocal_size,rows+first,PETSC_COPY_VALUES,&lrowp);CHKERRQ(ierr);
2213   ierr = ISRestoreIndices(irowp,&rows);CHKERRQ(ierr);
2214   ierr = ISDestroy(&irowp);CHKERRQ(ierr);
2215   /* the column permutation is so much easier;
2216      make a local version of 'colp' and invert it */
2217   ierr = PetscObjectGetComm((PetscObject)colp,&pcomm);CHKERRQ(ierr);
2218   ierr = MPI_Comm_size(pcomm,&size);CHKERRQ(ierr);
2219   if (size==1) {
2220     lcolp = colp;
2221   } else {
2222     ierr = ISAllGather(colp,&lcolp);CHKERRQ(ierr);
2223   }
2224   ierr = ISSetPermutation(lcolp);CHKERRQ(ierr);
2225   /* now we just get the submatrix */
2226   ierr = MatGetSubMatrix_MPIBAIJ_Private(A,lrowp,lcolp,clocal_size,MAT_INITIAL_MATRIX,B);CHKERRQ(ierr);
2227   if (size>1) {
2228     ierr = ISDestroy(&lcolp);CHKERRQ(ierr);
2229   }
2230   /* clean up */
2231   ierr = ISDestroy(&lrowp);CHKERRQ(ierr);
2232   PetscFunctionReturn(0);
2233 }
2234 
2235 #undef __FUNCT__
2236 #define __FUNCT__ "MatGetGhosts_MPIBAIJ"
2237 PetscErrorCode  MatGetGhosts_MPIBAIJ(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
2238 {
2239   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ*) mat->data;
2240   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ*)baij->B->data;
2241 
2242   PetscFunctionBegin;
2243   if (nghosts) *nghosts = B->nbs;
2244   if (ghosts) *ghosts = baij->garray;
2245   PetscFunctionReturn(0);
2246 }
2247 
2248 extern PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat);
2249 
2250 #undef __FUNCT__
2251 #define __FUNCT__ "MatFDColoringCreate_MPIBAIJ"
2252 /*
2253     This routine is almost identical to MatFDColoringCreate_MPIBAIJ()!
2254 */
2255 PetscErrorCode MatFDColoringCreate_MPIBAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
2256 {
2257   Mat_MPIBAIJ            *baij = (Mat_MPIBAIJ*)mat->data;
2258   PetscErrorCode         ierr;
2259   PetscMPIInt            size,*ncolsonproc,*disp,nn;
2260   PetscInt               bs,i,n,nrows,j,k,m,ncols,col;
2261   const PetscInt         *is,*rows = 0,*A_ci,*A_cj,*B_ci,*B_cj,*ltog;
2262   PetscInt               nis = iscoloring->n,nctot,*cols;
2263   PetscInt               *rowhit,M,cstart,cend,colb;
2264   PetscInt               *columnsforrow,l;
2265   IS                     *isa;
2266   PetscBool              done,flg;
2267   ISLocalToGlobalMapping map = mat->cmap->bmapping;
2268   PetscInt               ctype=c->ctype;
2269 
2270   PetscFunctionBegin;
2271   if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMappingBlock");
2272 
2273   if (map) {ierr = ISLocalToGlobalMappingGetIndices(map,&ltog);CHKERRQ(ierr);}
2274   else     ltog = NULL;
2275   ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr);
2276   ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr);
2277 
2278   M         = mat->rmap->n/bs;
2279   cstart    = mat->cmap->rstart/bs;
2280   cend      = mat->cmap->rend/bs;
2281   c->M      = mat->rmap->N/bs;         /* set the global rows and columns and local rows */
2282   c->N      = mat->cmap->N/bs;
2283   c->m      = mat->rmap->n/bs;
2284   c->rstart = mat->rmap->rstart/bs;
2285 
2286   c->ncolors = nis;
2287   ierr       = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr);
2288   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr);
2289   ierr       = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr);
2290   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr);
2291   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr);
2292   ierr       = PetscLogObjectMemory((PetscObject)c,5*nis*sizeof(PetscInt));CHKERRQ(ierr);
2293 
2294   /* Allow access to data structures of local part of matrix */
2295   if (!baij->colmap) {
2296     ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
2297   }
2298   ierr = MatGetColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr);
2299   ierr = MatGetColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr);
2300 
2301   ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);CHKERRQ(ierr);
2302   ierr = PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);CHKERRQ(ierr);
2303 
2304   for (i=0; i<nis; i++) {
2305     ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr);
2306     ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr);
2307 
2308     c->ncolumns[i] = n;
2309     if (n) {
2310       ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr);
2311       ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr);
2312       ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr);
2313     } else {
2314       c->columns[i] = 0;
2315     }
2316 
2317     if (ctype == IS_COLORING_GLOBAL) {
2318       /* Determine the total (parallel) number of columns of this color */
2319       ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
2320       ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr);
2321 
2322       ierr  = PetscMPIIntCast(n,&nn);CHKERRQ(ierr);
2323       ierr  = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
2324       nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j];
2325       if (!nctot) {
2326         ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr);
2327       }
2328 
2329       disp[0] = 0;
2330       for (j=1; j<size; j++) {
2331         disp[j] = disp[j-1] + ncolsonproc[j-1];
2332       }
2333 
2334       /* Get complete list of columns for color on each processor */
2335       ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr);
2336       ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
2337       ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr);
2338     } else if (ctype == IS_COLORING_GHOSTED) {
2339       /* Determine local number of columns of this color on this process, including ghost points */
2340       nctot = n;
2341       ierr  = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr);
2342       ierr  = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr);
2343     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type");
2344 
2345     /*
2346        Mark all rows affect by these columns
2347     */
2348     /* Temporary option to allow for debugging/testing */
2349     flg  = PETSC_FALSE;
2350     ierr = PetscOptionsGetBool(NULL,"-matfdcoloring_slow",&flg,NULL);CHKERRQ(ierr);
2351     if (!flg) { /*-----------------------------------------------------------------------------*/
2352       /* crude, fast version */
2353       ierr = PetscMemzero(rowhit,M*sizeof(PetscInt));CHKERRQ(ierr);
2354       /* loop over columns*/
2355       for (j=0; j<nctot; j++) {
2356         if (ctype == IS_COLORING_GHOSTED) {
2357           col = ltog[cols[j]];
2358         } else {
2359           col = cols[j];
2360         }
2361         if (col >= cstart && col < cend) {
2362           /* column is in diagonal block of matrix */
2363           rows = A_cj + A_ci[col-cstart];
2364           m    = A_ci[col-cstart+1] - A_ci[col-cstart];
2365         } else {
2366 #if defined(PETSC_USE_CTABLE)
2367           ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr);
2368           colb--;
2369 #else
2370           colb = baij->colmap[col] - 1;
2371 #endif
2372           if (colb == -1) {
2373             m = 0;
2374           } else {
2375             colb = colb/bs;
2376             rows = B_cj + B_ci[colb];
2377             m    = B_ci[colb+1] - B_ci[colb];
2378           }
2379         }
2380         /* loop over columns marking them in rowhit */
2381         for (k=0; k<m; k++) {
2382           rowhit[*rows++] = col + 1;
2383         }
2384       }
2385 
2386       /* count the number of hits */
2387       nrows = 0;
2388       for (j=0; j<M; j++) {
2389         if (rowhit[j]) nrows++;
2390       }
2391       c->nrows[i] = nrows;
2392       ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr);
2393       ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr);
2394       ierr        = PetscLogObjectMemory((PetscObject)c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr);
2395       nrows       = 0;
2396       for (j=0; j<M; j++) {
2397         if (rowhit[j]) {
2398           c->rows[i][nrows]          = j;
2399           c->columnsforrow[i][nrows] = rowhit[j] - 1;
2400           nrows++;
2401         }
2402       }
2403     } else { /*-------------------------------------------------------------------------------*/
2404       /* slow version, using rowhit as a linked list */
2405       PetscInt currentcol,fm,mfm;
2406       rowhit[M] = M;
2407       nrows     = 0;
2408       /* loop over columns*/
2409       for (j=0; j<nctot; j++) {
2410         if (ctype == IS_COLORING_GHOSTED) {
2411           col = ltog[cols[j]];
2412         } else {
2413           col = cols[j];
2414         }
2415         if (col >= cstart && col < cend) {
2416           /* column is in diagonal block of matrix */
2417           rows = A_cj + A_ci[col-cstart];
2418           m    = A_ci[col-cstart+1] - A_ci[col-cstart];
2419         } else {
2420 #if defined(PETSC_USE_CTABLE)
2421           ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr);
2422           colb--;
2423 #else
2424           colb = baij->colmap[col] - 1;
2425 #endif
2426           if (colb == -1) {
2427             m = 0;
2428           } else {
2429             colb = colb/bs;
2430             rows = B_cj + B_ci[colb];
2431             m    = B_ci[colb+1] - B_ci[colb];
2432           }
2433         }
2434 
2435         /* loop over columns marking them in rowhit */
2436         fm = M;    /* fm points to first entry in linked list */
2437         for (k=0; k<m; k++) {
2438           currentcol = *rows++;
2439           /* is it already in the list? */
2440           do {
2441             mfm = fm;
2442             fm  = rowhit[fm];
2443           } while (fm < currentcol);
2444           /* not in list so add it */
2445           if (fm != currentcol) {
2446             nrows++;
2447             columnsforrow[currentcol] = col;
2448             /* next three lines insert new entry into linked list */
2449             rowhit[mfm]        = currentcol;
2450             rowhit[currentcol] = fm;
2451             fm                 = currentcol;
2452             /* fm points to present position in list since we know the columns are sorted */
2453           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected");
2454         }
2455       }
2456       c->nrows[i] = nrows;
2457       ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr);
2458       ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr);
2459       ierr        = PetscLogObjectMemory((PetscObject)c,(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr);
2460       /* now store the linked list of rows into c->rows[i] */
2461       nrows = 0;
2462       fm    = rowhit[M];
2463       do {
2464         c->rows[i][nrows]            = fm;
2465         c->columnsforrow[i][nrows++] = columnsforrow[fm];
2466         fm                           = rowhit[fm];
2467       } while (fm < M);
2468     } /* ---------------------------------------------------------------------------------------*/
2469     ierr = PetscFree(cols);CHKERRQ(ierr);
2470   }
2471 
2472   /* Optimize by adding the vscale, and scaleforrow[][] fields */
2473   /*
2474        vscale will contain the "diagonal" on processor scalings followed by the off processor
2475   */
2476   if (ctype == IS_COLORING_GLOBAL) {
2477     PetscInt *garray;
2478     ierr = PetscMalloc(baij->B->cmap->n*sizeof(PetscInt),&garray);CHKERRQ(ierr);
2479     for (i=0; i<baij->B->cmap->n/bs; i++) {
2480       for (j=0; j<bs; j++) {
2481         garray[i*bs+j] = bs*baij->garray[i]+j;
2482       }
2483     }
2484     ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),baij->A->rmap->n,PETSC_DETERMINE,baij->B->cmap->n,garray,&c->vscale);CHKERRQ(ierr);
2485     ierr = PetscFree(garray);CHKERRQ(ierr);
2486     ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr);
2487     for (k=0; k<c->ncolors; k++) {
2488       ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr);
2489       for (l=0; l<c->nrows[k]; l++) {
2490         col = c->columnsforrow[k][l];
2491         if (col >= cstart && col < cend) {
2492           /* column is in diagonal block of matrix */
2493           colb = col - cstart;
2494         } else {
2495           /* column  is in "off-processor" part */
2496 #if defined(PETSC_USE_CTABLE)
2497           ierr = PetscTableFind(baij->colmap,col+1,&colb);CHKERRQ(ierr);
2498           colb--;
2499 #else
2500           colb = baij->colmap[col] - 1;
2501 #endif
2502           colb  = colb/bs;
2503           colb += cend - cstart;
2504         }
2505         c->vscaleforrow[k][l] = colb;
2506       }
2507     }
2508   } else if (ctype == IS_COLORING_GHOSTED) {
2509     /* Get gtol mapping */
2510     PetscInt N = mat->cmap->N,nlocal,*gtol;
2511     ierr = PetscMalloc((N+1)*sizeof(PetscInt),&gtol);CHKERRQ(ierr);
2512     for (i=0; i<N; i++) gtol[i] = -1;
2513     ierr = ISLocalToGlobalMappingGetSize(map,&nlocal);CHKERRQ(ierr);
2514     for (i=0; i<nlocal; i++) gtol[ltog[i]] = i;
2515 
2516     c->vscale = 0; /* will be created in MatFDColoringApply() */
2517     ierr      = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr);
2518     for (k=0; k<c->ncolors; k++) {
2519       ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr);
2520       for (l=0; l<c->nrows[k]; l++) {
2521         col = c->columnsforrow[k][l];      /* global column index */
2522 
2523         c->vscaleforrow[k][l] = gtol[col]; /* local column index */
2524       }
2525     }
2526     ierr = PetscFree(gtol);CHKERRQ(ierr);
2527   }
2528   ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr);
2529 
2530   ierr = PetscFree(rowhit);CHKERRQ(ierr);
2531   ierr = PetscFree(columnsforrow);CHKERRQ(ierr);
2532   ierr = MatRestoreColumnIJ(baij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr);
2533   ierr = MatRestoreColumnIJ(baij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr);
2534   if (map) {ierr = ISLocalToGlobalMappingRestoreIndices(map,&ltog);CHKERRQ(ierr);}
2535   PetscFunctionReturn(0);
2536 }
2537 
2538 #undef __FUNCT__
2539 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ"
2540 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
2541 {
2542   Mat            B;
2543   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
2544   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
2545   Mat_SeqAIJ     *b;
2546   PetscErrorCode ierr;
2547   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
2548   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
2549   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;
2550 
2551   PetscFunctionBegin;
2552   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr);
2553   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr);
2554 
2555   /* ----------------------------------------------------------------
2556      Tell every processor the number of nonzeros per row
2557   */
2558   ierr = PetscMalloc((A->rmap->N/bs)*sizeof(PetscInt),&lens);CHKERRQ(ierr);
2559   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
2560     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];
2561   }
2562   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
2563   ierr      = PetscMalloc(2*size*sizeof(PetscMPIInt),&recvcounts);CHKERRQ(ierr);
2564   displs    = recvcounts + size;
2565   for (i=0; i<size; i++) {
2566     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
2567     displs[i]     = A->rmap->range[i]/bs;
2568   }
2569 #if defined(PETSC_HAVE_MPI_IN_PLACE)
2570   ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2571 #else
2572   ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2573 #endif
2574   /* ---------------------------------------------------------------
2575      Create the sequential matrix of the same type as the local block diagonal
2576   */
2577   ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr);
2578   ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr);
2579   ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr);
2580   ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr);
2581   b    = (Mat_SeqAIJ*)B->data;
2582 
2583   /*--------------------------------------------------------------------
2584     Copy my part of matrix column indices over
2585   */
2586   sendcount  = ad->nz + bd->nz;
2587   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
2588   a_jsendbuf = ad->j;
2589   b_jsendbuf = bd->j;
2590   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
2591   cnt        = 0;
2592   for (i=0; i<n; i++) {
2593 
2594     /* put in lower diagonal portion */
2595     m = bd->i[i+1] - bd->i[i];
2596     while (m > 0) {
2597       /* is it above diagonal (in bd (compressed) numbering) */
2598       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
2599       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2600       m--;
2601     }
2602 
2603     /* put in diagonal portion */
2604     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
2605       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
2606     }
2607 
2608     /* put in upper diagonal portion */
2609     while (m-- > 0) {
2610       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2611     }
2612   }
2613   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);
2614 
2615   /*--------------------------------------------------------------------
2616     Gather all column indices to all processors
2617   */
2618   for (i=0; i<size; i++) {
2619     recvcounts[i] = 0;
2620     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
2621       recvcounts[i] += lens[j];
2622     }
2623   }
2624   displs[0] = 0;
2625   for (i=1; i<size; i++) {
2626     displs[i] = displs[i-1] + recvcounts[i-1];
2627   }
2628 #if defined(PETSC_HAVE_MPI_IN_PLACE)
2629   ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2630 #else
2631   ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2632 #endif
2633   /*--------------------------------------------------------------------
2634     Assemble the matrix into useable form (note numerical values not yet set)
2635   */
2636   /* set the b->ilen (length of each row) values */
2637   ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr);
2638   /* set the b->i indices */
2639   b->i[0] = 0;
2640   for (i=1; i<=A->rmap->N/bs; i++) {
2641     b->i[i] = b->i[i-1] + lens[i-1];
2642   }
2643   ierr = PetscFree(lens);CHKERRQ(ierr);
2644   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2645   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2646   ierr = PetscFree(recvcounts);CHKERRQ(ierr);
2647 
2648   if (A->symmetric) {
2649     ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
2650   } else if (A->hermitian) {
2651     ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr);
2652   } else if (A->structurally_symmetric) {
2653     ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
2654   }
2655   *newmat = B;
2656   PetscFunctionReturn(0);
2657 }
2658 
2659 #undef __FUNCT__
2660 #define __FUNCT__ "MatSOR_MPIBAIJ"
2661 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2662 {
2663   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
2664   PetscErrorCode ierr;
2665   Vec            bb1 = 0;
2666 
2667   PetscFunctionBegin;
2668   if (flag == SOR_APPLY_UPPER) {
2669     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2670     PetscFunctionReturn(0);
2671   }
2672 
2673   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
2674     ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr);
2675   }
2676 
2677   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2678     if (flag & SOR_ZERO_INITIAL_GUESS) {
2679       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2680       its--;
2681     }
2682 
2683     while (its--) {
2684       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2685       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2686 
2687       /* update rhs: bb1 = bb - B*x */
2688       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2689       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2690 
2691       /* local sweep */
2692       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2693     }
2694   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
2695     if (flag & SOR_ZERO_INITIAL_GUESS) {
2696       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2697       its--;
2698     }
2699     while (its--) {
2700       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2701       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2702 
2703       /* update rhs: bb1 = bb - B*x */
2704       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2705       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2706 
2707       /* local sweep */
2708       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2709     }
2710   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
2711     if (flag & SOR_ZERO_INITIAL_GUESS) {
2712       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2713       its--;
2714     }
2715     while (its--) {
2716       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2717       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2718 
2719       /* update rhs: bb1 = bb - B*x */
2720       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2721       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2722 
2723       /* local sweep */
2724       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2725     }
2726   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");
2727 
2728   ierr = VecDestroy(&bb1);CHKERRQ(ierr);
2729   PetscFunctionReturn(0);
2730 }
2731 
2732 extern PetscErrorCode  MatFDColoringApply_BAIJ(Mat,MatFDColoring,Vec,MatStructure*,void*);
2733 
2734 #undef __FUNCT__
2735 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ"
2736 PetscErrorCode  MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
2737 {
2738   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;
2739   PetscErrorCode ierr;
2740 
2741   PetscFunctionBegin;
2742   ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr);
2743   PetscFunctionReturn(0);
2744 }
2745 
2746 
2747 /* -------------------------------------------------------------------*/
2748 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
2749                                        MatGetRow_MPIBAIJ,
2750                                        MatRestoreRow_MPIBAIJ,
2751                                        MatMult_MPIBAIJ,
2752                                 /* 4*/ MatMultAdd_MPIBAIJ,
2753                                        MatMultTranspose_MPIBAIJ,
2754                                        MatMultTransposeAdd_MPIBAIJ,
2755                                        0,
2756                                        0,
2757                                        0,
2758                                 /*10*/ 0,
2759                                        0,
2760                                        0,
2761                                        MatSOR_MPIBAIJ,
2762                                        MatTranspose_MPIBAIJ,
2763                                 /*15*/ MatGetInfo_MPIBAIJ,
2764                                        MatEqual_MPIBAIJ,
2765                                        MatGetDiagonal_MPIBAIJ,
2766                                        MatDiagonalScale_MPIBAIJ,
2767                                        MatNorm_MPIBAIJ,
2768                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
2769                                        MatAssemblyEnd_MPIBAIJ,
2770                                        MatSetOption_MPIBAIJ,
2771                                        MatZeroEntries_MPIBAIJ,
2772                                 /*24*/ MatZeroRows_MPIBAIJ,
2773                                        0,
2774                                        0,
2775                                        0,
2776                                        0,
2777                                 /*29*/ MatSetUp_MPIBAIJ,
2778                                        0,
2779                                        0,
2780                                        0,
2781                                        0,
2782                                 /*34*/ MatDuplicate_MPIBAIJ,
2783                                        0,
2784                                        0,
2785                                        0,
2786                                        0,
2787                                 /*39*/ MatAXPY_MPIBAIJ,
2788                                        MatGetSubMatrices_MPIBAIJ,
2789                                        MatIncreaseOverlap_MPIBAIJ,
2790                                        MatGetValues_MPIBAIJ,
2791                                        MatCopy_MPIBAIJ,
2792                                 /*44*/ 0,
2793                                        MatScale_MPIBAIJ,
2794                                        0,
2795                                        0,
2796                                        0,
2797                                 /*49*/ 0,
2798                                        0,
2799                                        0,
2800                                        0,
2801                                        0,
2802                                 /*54*/ MatFDColoringCreate_MPIBAIJ,
2803                                        0,
2804                                        MatSetUnfactored_MPIBAIJ,
2805                                        MatPermute_MPIBAIJ,
2806                                        MatSetValuesBlocked_MPIBAIJ,
2807                                 /*59*/ MatGetSubMatrix_MPIBAIJ,
2808                                        MatDestroy_MPIBAIJ,
2809                                        MatView_MPIBAIJ,
2810                                        0,
2811                                        0,
2812                                 /*64*/ 0,
2813                                        0,
2814                                        0,
2815                                        0,
2816                                        0,
2817                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
2818                                        0,
2819                                        0,
2820                                        0,
2821                                        0,
2822                                 /*74*/ 0,
2823                                        MatFDColoringApply_BAIJ,
2824                                        0,
2825                                        0,
2826                                        0,
2827                                 /*79*/ 0,
2828                                        0,
2829                                        0,
2830                                        0,
2831                                        MatLoad_MPIBAIJ,
2832                                 /*84*/ 0,
2833                                        0,
2834                                        0,
2835                                        0,
2836                                        0,
2837                                 /*89*/ 0,
2838                                        0,
2839                                        0,
2840                                        0,
2841                                        0,
2842                                 /*94*/ 0,
2843                                        0,
2844                                        0,
2845                                        0,
2846                                        0,
2847                                 /*99*/ 0,
2848                                        0,
2849                                        0,
2850                                        0,
2851                                        0,
2852                                 /*104*/0,
2853                                        MatRealPart_MPIBAIJ,
2854                                        MatImaginaryPart_MPIBAIJ,
2855                                        0,
2856                                        0,
2857                                 /*109*/0,
2858                                        0,
2859                                        0,
2860                                        0,
2861                                        0,
2862                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
2863                                        0,
2864                                        MatGetGhosts_MPIBAIJ,
2865                                        0,
2866                                        0,
2867                                 /*119*/0,
2868                                        0,
2869                                        0,
2870                                        0,
2871                                        MatGetMultiProcBlock_MPIBAIJ,
2872                                 /*124*/0,
2873                                        0,
2874                                        MatInvertBlockDiagonal_MPIBAIJ,
2875                                        0,
2876                                        0,
2877                                /*129*/ 0,
2878                                        0,
2879                                        0,
2880                                        0,
2881                                        0,
2882                                /*134*/ 0,
2883                                        0,
2884                                        0,
2885                                        0,
2886                                        0,
2887                                /*139*/ 0,
2888                                        0
2889 };
2890 
2891 #undef __FUNCT__
2892 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ"
2893 PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
2894 {
2895   PetscFunctionBegin;
2896   *a = ((Mat_MPIBAIJ*)A->data)->A;
2897   PetscFunctionReturn(0);
2898 }
2899 
2900 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*);
2901 
2902 #undef __FUNCT__
2903 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ"
2904 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2905 {
2906   PetscInt       m,rstart,cstart,cend;
2907   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2908   const PetscInt *JJ    =0;
2909   PetscScalar    *values=0;
2910   PetscErrorCode ierr;
2911 
2912   PetscFunctionBegin;
2913   ierr   = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr);
2914   ierr   = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr);
2915   ierr   = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
2916   ierr   = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
2917   ierr   = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
2918   m      = B->rmap->n/bs;
2919   rstart = B->rmap->rstart/bs;
2920   cstart = B->cmap->rstart/bs;
2921   cend   = B->cmap->rend/bs;
2922 
2923   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2924   ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr);
2925   for (i=0; i<m; i++) {
2926     nz = ii[i+1] - ii[i];
2927     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2928     nz_max = PetscMax(nz_max,nz);
2929     JJ     = jj + ii[i];
2930     for (j=0; j<nz; j++) {
2931       if (*JJ >= cstart) break;
2932       JJ++;
2933     }
2934     d = 0;
2935     for (; j<nz; j++) {
2936       if (*JJ++ >= cend) break;
2937       d++;
2938     }
2939     d_nnz[i] = d;
2940     o_nnz[i] = nz - d;
2941   }
2942   ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr);
2943   ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr);
2944 
2945   values = (PetscScalar*)V;
2946   if (!values) {
2947     ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr);
2948     ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr);
2949   }
2950   for (i=0; i<m; i++) {
2951     PetscInt          row    = i + rstart;
2952     PetscInt          ncols  = ii[i+1] - ii[i];
2953     const PetscInt    *icols = jj + ii[i];
2954     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2955     ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr);
2956   }
2957 
2958   if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); }
2959   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2960   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2961   ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);
2962   PetscFunctionReturn(0);
2963 }
2964 
2965 #undef __FUNCT__
2966 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR"
2967 /*@C
2968    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2969    (the default parallel PETSc format).
2970 
2971    Collective on MPI_Comm
2972 
2973    Input Parameters:
2974 +  A - the matrix
2975 .  bs - the block size
2976 .  i - the indices into j for the start of each local row (starts with zero)
2977 .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2978 -  v - optional values in the matrix
2979 
2980    Level: developer
2981 
2982 .keywords: matrix, aij, compressed row, sparse, parallel
2983 
2984 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2985 @*/
2986 PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2987 {
2988   PetscErrorCode ierr;
2989 
2990   PetscFunctionBegin;
2991   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
2992   PetscValidType(B,1);
2993   PetscValidLogicalCollectiveInt(B,bs,2);
2994   ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr);
2995   PetscFunctionReturn(0);
2996 }
2997 
2998 #undef __FUNCT__
2999 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ"
3000 PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
3001 {
3002   Mat_MPIBAIJ    *b;
3003   PetscErrorCode ierr;
3004   PetscInt       i;
3005 
3006   PetscFunctionBegin;
3007   ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr);
3008   ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr);
3009   ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
3010   ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
3011   ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
3012 
3013   if (d_nnz) {
3014     for (i=0; i<B->rmap->n/bs; i++) {
3015       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]);
3016     }
3017   }
3018   if (o_nnz) {
3019     for (i=0; i<B->rmap->n/bs; i++) {
3020       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]);
3021     }
3022   }
3023 
3024   b      = (Mat_MPIBAIJ*)B->data;
3025   b->bs2 = bs*bs;
3026   b->mbs = B->rmap->n/bs;
3027   b->nbs = B->cmap->n/bs;
3028   b->Mbs = B->rmap->N/bs;
3029   b->Nbs = B->cmap->N/bs;
3030 
3031   for (i=0; i<=b->size; i++) {
3032     b->rangebs[i] = B->rmap->range[i]/bs;
3033   }
3034   b->rstartbs = B->rmap->rstart/bs;
3035   b->rendbs   = B->rmap->rend/bs;
3036   b->cstartbs = B->cmap->rstart/bs;
3037   b->cendbs   = B->cmap->rend/bs;
3038 
3039   if (!B->preallocated) {
3040     ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr);
3041     ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr);
3042     ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr);
3043     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr);
3044     ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr);
3045     ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr);
3046     ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr);
3047     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr);
3048     ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr);
3049   }
3050 
3051   ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr);
3052   ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr);
3053   B->preallocated = PETSC_TRUE;
3054   PetscFunctionReturn(0);
3055 }
3056 
3057 extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
3058 extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);
3059 
3060 #undef __FUNCT__
3061 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj"
3062 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
3063 {
3064   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
3065   PetscErrorCode ierr;
3066   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
3067   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
3068   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;
3069 
3070   PetscFunctionBegin;
3071   ierr  = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr);
3072   ii[0] = 0;
3073   for (i=0; i<M; i++) {
3074     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]);
3075     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]);
3076     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
3077     /* remove one from count of matrix has diagonal */
3078     for (j=id[i]; j<id[i+1]; j++) {
3079       if (jd[j] == i) {ii[i+1]--;break;}
3080     }
3081   }
3082   ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr);
3083   cnt  = 0;
3084   for (i=0; i<M; i++) {
3085     for (j=io[i]; j<io[i+1]; j++) {
3086       if (garray[jo[j]] > rstart) break;
3087       jj[cnt++] = garray[jo[j]];
3088     }
3089     for (k=id[i]; k<id[i+1]; k++) {
3090       if (jd[k] != i) {
3091         jj[cnt++] = rstart + jd[k];
3092       }
3093     }
3094     for (; j<io[i+1]; j++) {
3095       jj[cnt++] = garray[jo[j]];
3096     }
3097   }
3098   ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr);
3099   PetscFunctionReturn(0);
3100 }
3101 
3102 #include <../src/mat/impls/aij/mpi/mpiaij.h>
3103 
3104 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);
3105 
3106 #undef __FUNCT__
3107 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ"
3108 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
3109 {
3110   PetscErrorCode ierr;
3111   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
3112   Mat            B;
3113   Mat_MPIAIJ     *b;
3114 
3115   PetscFunctionBegin;
3116   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");
3117 
3118   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
3119   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
3120   ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr);
3121   ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr);
3122   ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr);
3123   b    = (Mat_MPIAIJ*) B->data;
3124 
3125   ierr = MatDestroy(&b->A);CHKERRQ(ierr);
3126   ierr = MatDestroy(&b->B);CHKERRQ(ierr);
3127   ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr);
3128   ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr);
3129   ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr);
3130   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3131   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3132   ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3133   ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3134   if (reuse == MAT_REUSE_MATRIX) {
3135     ierr = MatHeaderReplace(A,B);CHKERRQ(ierr);
3136   } else {
3137    *newmat = B;
3138   }
3139   PetscFunctionReturn(0);
3140 }
3141 
3142 #if defined(PETSC_HAVE_MUMPS)
3143 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*);
3144 #endif
3145 
3146 /*MC
3147    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.
3148 
3149    Options Database Keys:
3150 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
3151 . -mat_block_size <bs> - set the blocksize used to store the matrix
3152 - -mat_use_hash_table <fact>
3153 
3154   Level: beginner
3155 
3156 .seealso: MatCreateMPIBAIJ
3157 M*/
3158 
3159 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);
3160 
3161 #undef __FUNCT__
3162 #define __FUNCT__ "MatCreate_MPIBAIJ"
3163 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
3164 {
3165   Mat_MPIBAIJ    *b;
3166   PetscErrorCode ierr;
3167   PetscBool      flg;
3168 
3169   PetscFunctionBegin;
3170   ierr    = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr);
3171   B->data = (void*)b;
3172 
3173   ierr         = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr);
3174   B->assembled = PETSC_FALSE;
3175 
3176   B->insertmode = NOT_SET_VALUES;
3177   ierr          = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr);
3178   ierr          = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr);
3179 
3180   /* build local table of row and column ownerships */
3181   ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr);
3182 
3183   /* build cache for off array entries formed */
3184   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr);
3185 
3186   b->donotstash  = PETSC_FALSE;
3187   b->colmap      = NULL;
3188   b->garray      = NULL;
3189   b->roworiented = PETSC_TRUE;
3190 
3191   /* stuff used in block assembly */
3192   b->barray = 0;
3193 
3194   /* stuff used for matrix vector multiply */
3195   b->lvec  = 0;
3196   b->Mvctx = 0;
3197 
3198   /* stuff for MatGetRow() */
3199   b->rowindices   = 0;
3200   b->rowvalues    = 0;
3201   b->getrowactive = PETSC_FALSE;
3202 
3203   /* hash table stuff */
3204   b->ht           = 0;
3205   b->hd           = 0;
3206   b->ht_size      = 0;
3207   b->ht_flag      = PETSC_FALSE;
3208   b->ht_fact      = 0;
3209   b->ht_total_ct  = 0;
3210   b->ht_insert_ct = 0;
3211 
3212   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
3213   b->ijonly = PETSC_FALSE;
3214 
3215   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr);
3216   ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr);
3217   if (flg) {
3218     PetscReal fact = 1.39;
3219     ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr);
3220     ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr);
3221     if (fact <= 1.0) fact = 1.39;
3222     ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr);
3223     ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr);
3224   }
3225   ierr = PetscOptionsEnd();CHKERRQ(ierr);
3226 
3227 #if defined(PETSC_HAVE_MUMPS)
3228   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr);
3229 #endif
3230   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr);
3231   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr);
3232   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr);
3233   ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr);
3234   ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr);
3235   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr);
3236   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr);
3237   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr);
3238   ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr);
3239   ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr);
3240   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr);
3241   ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr);
3242   PetscFunctionReturn(0);
3243 }
3244 
3245 /*MC
3246    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.
3247 
3248    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
3249    and MATMPIBAIJ otherwise.
3250 
3251    Options Database Keys:
3252 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()
3253 
3254   Level: beginner
3255 
3256 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3257 M*/
3258 
3259 #undef __FUNCT__
3260 #define __FUNCT__ "MatMPIBAIJSetPreallocation"
3261 /*@C
3262    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
3263    (block compressed row).  For good matrix assembly performance
3264    the user should preallocate the matrix storage by setting the parameters
3265    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3266    performance can be increased by more than a factor of 50.
3267 
3268    Collective on Mat
3269 
3270    Input Parameters:
3271 +  A - the matrix
3272 .  bs   - size of block
3273 .  d_nz  - number of block nonzeros per block row in diagonal portion of local
3274            submatrix  (same for all local rows)
3275 .  d_nnz - array containing the number of block nonzeros in the various block rows
3276            of the in diagonal portion of the local (possibly different for each block
3277            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
3278            set it even if it is zero.
3279 .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
3280            submatrix (same for all local rows).
3281 -  o_nnz - array containing the number of nonzeros in the various block rows of the
3282            off-diagonal portion of the local submatrix (possibly different for
3283            each block row) or NULL.
3284 
3285    If the *_nnz parameter is given then the *_nz parameter is ignored
3286 
3287    Options Database Keys:
3288 +   -mat_block_size - size of the blocks to use
3289 -   -mat_use_hash_table <fact>
3290 
3291    Notes:
3292    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3293    than it must be used on all processors that share the object for that argument.
3294 
3295    Storage Information:
3296    For a square global matrix we define each processor's diagonal portion
3297    to be its local rows and the corresponding columns (a square submatrix);
3298    each processor's off-diagonal portion encompasses the remainder of the
3299    local matrix (a rectangular submatrix).
3300 
3301    The user can specify preallocated storage for the diagonal part of
3302    the local submatrix with either d_nz or d_nnz (not both).  Set
3303    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3304    memory allocation.  Likewise, specify preallocated storage for the
3305    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
3306 
3307    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3308    the figure below we depict these three local rows and all columns (0-11).
3309 
3310 .vb
3311            0 1 2 3 4 5 6 7 8 9 10 11
3312           --------------------------
3313    row 3  |o o o d d d o o o o  o  o
3314    row 4  |o o o d d d o o o o  o  o
3315    row 5  |o o o d d d o o o o  o  o
3316           --------------------------
3317 .ve
3318 
3319    Thus, any entries in the d locations are stored in the d (diagonal)
3320    submatrix, and any entries in the o locations are stored in the
3321    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3322    stored simply in the MATSEQBAIJ format for compressed row storage.
3323 
3324    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3325    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3326    In general, for PDE problems in which most nonzeros are near the diagonal,
3327    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3328    or you will get TERRIBLE performance; see the users' manual chapter on
3329    matrices.
3330 
3331    You can call MatGetInfo() to get information on how effective the preallocation was;
3332    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3333    You can also run with the option -info and look for messages with the string
3334    malloc in them to see if additional memory allocation was needed.
3335 
3336    Level: intermediate
3337 
3338 .keywords: matrix, block, aij, compressed row, sparse, parallel
3339 
3340 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
3341 @*/
3342 PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3343 {
3344   PetscErrorCode ierr;
3345 
3346   PetscFunctionBegin;
3347   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
3348   PetscValidType(B,1);
3349   PetscValidLogicalCollectiveInt(B,bs,2);
3350   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);
3351   PetscFunctionReturn(0);
3352 }
3353 
3354 #undef __FUNCT__
3355 #define __FUNCT__ "MatCreateBAIJ"
3356 /*@C
3357    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
3358    (block compressed row).  For good matrix assembly performance
3359    the user should preallocate the matrix storage by setting the parameters
3360    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3361    performance can be increased by more than a factor of 50.
3362 
3363    Collective on MPI_Comm
3364 
3365    Input Parameters:
3366 +  comm - MPI communicator
3367 .  bs   - size of blockk
3368 .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3369            This value should be the same as the local size used in creating the
3370            y vector for the matrix-vector product y = Ax.
3371 .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
3372            This value should be the same as the local size used in creating the
3373            x vector for the matrix-vector product y = Ax.
3374 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3375 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3376 .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
3377            submatrix  (same for all local rows)
3378 .  d_nnz - array containing the number of nonzero blocks in the various block rows
3379            of the in diagonal portion of the local (possibly different for each block
3380            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
3381            and set it even if it is zero.
3382 .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
3383            submatrix (same for all local rows).
3384 -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
3385            off-diagonal portion of the local submatrix (possibly different for
3386            each block row) or NULL.
3387 
3388    Output Parameter:
3389 .  A - the matrix
3390 
3391    Options Database Keys:
3392 +   -mat_block_size - size of the blocks to use
3393 -   -mat_use_hash_table <fact>
3394 
3395    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3396    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3397    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
3398 
3399    Notes:
3400    If the *_nnz parameter is given then the *_nz parameter is ignored
3401 
3402    A nonzero block is any block that as 1 or more nonzeros in it
3403 
3404    The user MUST specify either the local or global matrix dimensions
3405    (possibly both).
3406 
3407    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3408    than it must be used on all processors that share the object for that argument.
3409 
3410    Storage Information:
3411    For a square global matrix we define each processor's diagonal portion
3412    to be its local rows and the corresponding columns (a square submatrix);
3413    each processor's off-diagonal portion encompasses the remainder of the
3414    local matrix (a rectangular submatrix).
3415 
3416    The user can specify preallocated storage for the diagonal part of
3417    the local submatrix with either d_nz or d_nnz (not both).  Set
3418    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3419    memory allocation.  Likewise, specify preallocated storage for the
3420    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
3421 
3422    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3423    the figure below we depict these three local rows and all columns (0-11).
3424 
3425 .vb
3426            0 1 2 3 4 5 6 7 8 9 10 11
3427           --------------------------
3428    row 3  |o o o d d d o o o o  o  o
3429    row 4  |o o o d d d o o o o  o  o
3430    row 5  |o o o d d d o o o o  o  o
3431           --------------------------
3432 .ve
3433 
3434    Thus, any entries in the d locations are stored in the d (diagonal)
3435    submatrix, and any entries in the o locations are stored in the
3436    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3437    stored simply in the MATSEQBAIJ format for compressed row storage.
3438 
3439    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3440    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3441    In general, for PDE problems in which most nonzeros are near the diagonal,
3442    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3443    or you will get TERRIBLE performance; see the users' manual chapter on
3444    matrices.
3445 
3446    Level: intermediate
3447 
3448 .keywords: matrix, block, aij, compressed row, sparse, parallel
3449 
3450 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3451 @*/
3452 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)
3453 {
3454   PetscErrorCode ierr;
3455   PetscMPIInt    size;
3456 
3457   PetscFunctionBegin;
3458   ierr = MatCreate(comm,A);CHKERRQ(ierr);
3459   ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr);
3460   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
3461   if (size > 1) {
3462     ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr);
3463     ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr);
3464   } else {
3465     ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr);
3466     ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr);
3467   }
3468   PetscFunctionReturn(0);
3469 }
3470 
3471 #undef __FUNCT__
3472 #define __FUNCT__ "MatDuplicate_MPIBAIJ"
3473 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
3474 {
3475   Mat            mat;
3476   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
3477   PetscErrorCode ierr;
3478   PetscInt       len=0;
3479 
3480   PetscFunctionBegin;
3481   *newmat = 0;
3482   ierr    = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr);
3483   ierr    = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr);
3484   ierr    = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr);
3485   ierr    = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr);
3486 
3487   mat->factortype   = matin->factortype;
3488   mat->preallocated = PETSC_TRUE;
3489   mat->assembled    = PETSC_TRUE;
3490   mat->insertmode   = NOT_SET_VALUES;
3491 
3492   a             = (Mat_MPIBAIJ*)mat->data;
3493   mat->rmap->bs = matin->rmap->bs;
3494   a->bs2        = oldmat->bs2;
3495   a->mbs        = oldmat->mbs;
3496   a->nbs        = oldmat->nbs;
3497   a->Mbs        = oldmat->Mbs;
3498   a->Nbs        = oldmat->Nbs;
3499 
3500   ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr);
3501   ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr);
3502 
3503   a->size         = oldmat->size;
3504   a->rank         = oldmat->rank;
3505   a->donotstash   = oldmat->donotstash;
3506   a->roworiented  = oldmat->roworiented;
3507   a->rowindices   = 0;
3508   a->rowvalues    = 0;
3509   a->getrowactive = PETSC_FALSE;
3510   a->barray       = 0;
3511   a->rstartbs     = oldmat->rstartbs;
3512   a->rendbs       = oldmat->rendbs;
3513   a->cstartbs     = oldmat->cstartbs;
3514   a->cendbs       = oldmat->cendbs;
3515 
3516   /* hash table stuff */
3517   a->ht           = 0;
3518   a->hd           = 0;
3519   a->ht_size      = 0;
3520   a->ht_flag      = oldmat->ht_flag;
3521   a->ht_fact      = oldmat->ht_fact;
3522   a->ht_total_ct  = 0;
3523   a->ht_insert_ct = 0;
3524 
3525   ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr);
3526   if (oldmat->colmap) {
3527 #if defined(PETSC_USE_CTABLE)
3528     ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr);
3529 #else
3530     ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr);
3531     ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
3532     ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
3533 #endif
3534   } else a->colmap = 0;
3535 
3536   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
3537     ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr);
3538     ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr);
3539     ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr);
3540   } else a->garray = 0;
3541 
3542   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr);
3543   ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr);
3544   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr);
3545   ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr);
3546   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr);
3547 
3548   ierr    = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr);
3549   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr);
3550   ierr    = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr);
3551   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr);
3552   ierr    = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr);
3553   *newmat = mat;
3554   PetscFunctionReturn(0);
3555 }
3556 
3557 #undef __FUNCT__
3558 #define __FUNCT__ "MatLoad_MPIBAIJ"
3559 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
3560 {
3561   PetscErrorCode ierr;
3562   int            fd;
3563   PetscInt       i,nz,j,rstart,rend;
3564   PetscScalar    *vals,*buf;
3565   MPI_Comm       comm;
3566   MPI_Status     status;
3567   PetscMPIInt    rank,size,maxnz;
3568   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
3569   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
3570   PetscInt       jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax;
3571   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
3572   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
3573   PetscInt       dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols;
3574 
3575   PetscFunctionBegin;
3576   ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr);
3577   ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr);
3578   ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr);
3579   ierr = PetscOptionsEnd();CHKERRQ(ierr);
3580 
3581   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
3582   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
3583   if (!rank) {
3584     ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
3585     ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr);
3586     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
3587   }
3588 
3589   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0;
3590 
3591   ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr);
3592   M    = header[1]; N = header[2];
3593 
3594   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
3595   if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M;
3596   if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N;
3597 
3598   /* If global sizes are set, check if they are consistent with that given in the file */
3599   if (sizesset) {
3600     ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr);
3601   }
3602   if (sizesset && newmat->rmap->N != grows) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of rows:Matrix in file has (%d) and input matrix has (%d)",M,grows);
3603   if (sizesset && newmat->cmap->N != gcols) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED, "Inconsistent # of cols:Matrix in file has (%d) and input matrix has (%d)",N,gcols);
3604 
3605   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");
3606 
3607   /*
3608      This code adds extra rows to make sure the number of rows is
3609      divisible by the blocksize
3610   */
3611   Mbs        = M/bs;
3612   extra_rows = bs - M + bs*Mbs;
3613   if (extra_rows == bs) extra_rows = 0;
3614   else                  Mbs++;
3615   if (extra_rows && !rank) {
3616     ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr);
3617   }
3618 
3619   /* determine ownership of all rows */
3620   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
3621     mbs = Mbs/size + ((Mbs % size) > rank);
3622     m   = mbs*bs;
3623   } else { /* User set */
3624     m   = newmat->rmap->n;
3625     mbs = m/bs;
3626   }
3627   ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr);
3628   ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr);
3629 
3630   /* process 0 needs enough room for process with most rows */
3631   if (!rank) {
3632     mmax = rowners[1];
3633     for (i=2; i<=size; i++) {
3634       mmax = PetscMax(mmax,rowners[i]);
3635     }
3636     mmax*=bs;
3637   } else mmax = -1;             /* unused, but compiler warns anyway */
3638 
3639   rowners[0] = 0;
3640   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
3641   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
3642   rstart = rowners[rank];
3643   rend   = rowners[rank+1];
3644 
3645   /* distribute row lengths to all processors */
3646   ierr = PetscMalloc(m*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr);
3647   if (!rank) {
3648     mend = m;
3649     if (size == 1) mend = mend - extra_rows;
3650     ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr);
3651     for (j=mend; j<m; j++) locrowlens[j] = 1;
3652     ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr);
3653     ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr);
3654     ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr);
3655     for (j=0; j<m; j++) {
3656       procsnz[0] += locrowlens[j];
3657     }
3658     for (i=1; i<size; i++) {
3659       mend = browners[i+1] - browners[i];
3660       if (i == size-1) mend = mend - extra_rows;
3661       ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr);
3662       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
3663       /* calculate the number of nonzeros on each processor */
3664       for (j=0; j<browners[i+1]-browners[i]; j++) {
3665         procsnz[i] += rowlengths[j];
3666       }
3667       ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr);
3668     }
3669     ierr = PetscFree(rowlengths);CHKERRQ(ierr);
3670   } else {
3671     ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
3672   }
3673 
3674   if (!rank) {
3675     /* determine max buffer needed and allocate it */
3676     maxnz = procsnz[0];
3677     for (i=1; i<size; i++) {
3678       maxnz = PetscMax(maxnz,procsnz[i]);
3679     }
3680     ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr);
3681 
3682     /* read in my part of the matrix column indices  */
3683     nz     = procsnz[0];
3684     ierr   = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr);
3685     mycols = ibuf;
3686     if (size == 1) nz -= extra_rows;
3687     ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr);
3688     if (size == 1) {
3689       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
3690     }
3691 
3692     /* read in every ones (except the last) and ship off */
3693     for (i=1; i<size-1; i++) {
3694       nz   = procsnz[i];
3695       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
3696       ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr);
3697     }
3698     /* read in the stuff for the last proc */
3699     if (size != 1) {
3700       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
3701       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
3702       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
3703       ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr);
3704     }
3705     ierr = PetscFree(cols);CHKERRQ(ierr);
3706   } else {
3707     /* determine buffer space needed for message */
3708     nz = 0;
3709     for (i=0; i<m; i++) {
3710       nz += locrowlens[i];
3711     }
3712     ierr   = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr);
3713     mycols = ibuf;
3714     /* receive message of column indices*/
3715     ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
3716     ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr);
3717     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
3718   }
3719 
3720   /* loop over local rows, determining number of off diagonal entries */
3721   ierr     = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr);
3722   ierr     = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr);
3723   ierr     = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
3724   ierr     = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
3725   ierr     = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
3726   rowcount = 0; nzcount = 0;
3727   for (i=0; i<mbs; i++) {
3728     dcount  = 0;
3729     odcount = 0;
3730     for (j=0; j<bs; j++) {
3731       kmax = locrowlens[rowcount];
3732       for (k=0; k<kmax; k++) {
3733         tmp = mycols[nzcount++]/bs;
3734         if (!mask[tmp]) {
3735           mask[tmp] = 1;
3736           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
3737           else masked1[dcount++] = tmp;
3738         }
3739       }
3740       rowcount++;
3741     }
3742 
3743     dlens[i]  = dcount;
3744     odlens[i] = odcount;
3745 
3746     /* zero out the mask elements we set */
3747     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
3748     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
3749   }
3750 
3751 
3752   if (!sizesset) {
3753     ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr);
3754   }
3755   ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr);
3756 
3757   if (!rank) {
3758     ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr);
3759     /* read in my part of the matrix numerical values  */
3760     nz     = procsnz[0];
3761     vals   = buf;
3762     mycols = ibuf;
3763     if (size == 1) nz -= extra_rows;
3764     ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3765     if (size == 1) {
3766       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
3767     }
3768 
3769     /* insert into matrix */
3770     jj = rstart*bs;
3771     for (i=0; i<m; i++) {
3772       ierr    = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
3773       mycols += locrowlens[i];
3774       vals   += locrowlens[i];
3775       jj++;
3776     }
3777     /* read in other processors (except the last one) and ship out */
3778     for (i=1; i<size-1; i++) {
3779       nz   = procsnz[i];
3780       vals = buf;
3781       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3782       ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3783     }
3784     /* the last proc */
3785     if (size != 1) {
3786       nz   = procsnz[i] - extra_rows;
3787       vals = buf;
3788       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3789       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
3790       ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3791     }
3792     ierr = PetscFree(procsnz);CHKERRQ(ierr);
3793   } else {
3794     /* receive numeric values */
3795     ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr);
3796 
3797     /* receive message of values*/
3798     vals   = buf;
3799     mycols = ibuf;
3800     ierr   = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3801 
3802     /* insert into matrix */
3803     jj = rstart*bs;
3804     for (i=0; i<m; i++) {
3805       ierr    = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
3806       mycols += locrowlens[i];
3807       vals   += locrowlens[i];
3808       jj++;
3809     }
3810   }
3811   ierr = PetscFree(locrowlens);CHKERRQ(ierr);
3812   ierr = PetscFree(buf);CHKERRQ(ierr);
3813   ierr = PetscFree(ibuf);CHKERRQ(ierr);
3814   ierr = PetscFree2(rowners,browners);CHKERRQ(ierr);
3815   ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr);
3816   ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr);
3817   ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3818   ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3819   PetscFunctionReturn(0);
3820 }
3821 
3822 #undef __FUNCT__
3823 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor"
3824 /*@
3825    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.
3826 
3827    Input Parameters:
3828 .  mat  - the matrix
3829 .  fact - factor
3830 
3831    Not Collective, each process can use a different factor
3832 
3833    Level: advanced
3834 
3835   Notes:
3836    This can also be set by the command line option: -mat_use_hash_table <fact>
3837 
3838 .keywords: matrix, hashtable, factor, HT
3839 
3840 .seealso: MatSetOption()
3841 @*/
3842 PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
3843 {
3844   PetscErrorCode ierr;
3845 
3846   PetscFunctionBegin;
3847   ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr);
3848   PetscFunctionReturn(0);
3849 }
3850 
3851 #undef __FUNCT__
3852 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ"
3853 PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
3854 {
3855   Mat_MPIBAIJ *baij;
3856 
3857   PetscFunctionBegin;
3858   baij          = (Mat_MPIBAIJ*)mat->data;
3859   baij->ht_fact = fact;
3860   PetscFunctionReturn(0);
3861 }
3862 
3863 #undef __FUNCT__
3864 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ"
3865 PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3866 {
3867   Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;
3868 
3869   PetscFunctionBegin;
3870   *Ad     = a->A;
3871   *Ao     = a->B;
3872   *colmap = a->garray;
3873   PetscFunctionReturn(0);
3874 }
3875 
3876 /*
3877     Special version for direct calls from Fortran (to eliminate two function call overheads
3878 */
3879 #if defined(PETSC_HAVE_FORTRAN_CAPS)
3880 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
3881 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
3882 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
3883 #endif
3884 
3885 #undef __FUNCT__
3886 #define __FUNCT__ "matmpibiajsetvaluesblocked"
3887 /*@C
3888   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()
3889 
3890   Collective on Mat
3891 
3892   Input Parameters:
3893 + mat - the matrix
3894 . min - number of input rows
3895 . im - input rows
3896 . nin - number of input columns
3897 . in - input columns
3898 . v - numerical values input
3899 - addvin - INSERT_VALUES or ADD_VALUES
3900 
3901   Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.
3902 
3903   Level: advanced
3904 
3905 .seealso:   MatSetValuesBlocked()
3906 @*/
3907 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
3908 {
3909   /* convert input arguments to C version */
3910   Mat        mat  = *matin;
3911   PetscInt   m    = *min, n = *nin;
3912   InsertMode addv = *addvin;
3913 
3914   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
3915   const MatScalar *value;
3916   MatScalar       *barray     = baij->barray;
3917   PetscBool       roworiented = baij->roworiented;
3918   PetscErrorCode  ierr;
3919   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
3920   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
3921   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;
3922 
3923   PetscFunctionBegin;
3924   /* tasks normally handled by MatSetValuesBlocked() */
3925   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
3926 #if defined(PETSC_USE_DEBUG)
3927   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
3928   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
3929 #endif
3930   if (mat->assembled) {
3931     mat->was_assembled = PETSC_TRUE;
3932     mat->assembled     = PETSC_FALSE;
3933   }
3934   ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr);
3935 
3936 
3937   if (!barray) {
3938     ierr         = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr);
3939     baij->barray = barray;
3940   }
3941 
3942   if (roworiented) stepval = (n-1)*bs;
3943   else stepval = (m-1)*bs;
3944 
3945   for (i=0; i<m; i++) {
3946     if (im[i] < 0) continue;
3947 #if defined(PETSC_USE_DEBUG)
3948     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);
3949 #endif
3950     if (im[i] >= rstart && im[i] < rend) {
3951       row = im[i] - rstart;
3952       for (j=0; j<n; j++) {
3953         /* If NumCol = 1 then a copy is not required */
3954         if ((roworiented) && (n == 1)) {
3955           barray = (MatScalar*)v + i*bs2;
3956         } else if ((!roworiented) && (m == 1)) {
3957           barray = (MatScalar*)v + j*bs2;
3958         } else { /* Here a copy is required */
3959           if (roworiented) {
3960             value = v + i*(stepval+bs)*bs + j*bs;
3961           } else {
3962             value = v + j*(stepval+bs)*bs + i*bs;
3963           }
3964           for (ii=0; ii<bs; ii++,value+=stepval) {
3965             for (jj=0; jj<bs; jj++) {
3966               *barray++ = *value++;
3967             }
3968           }
3969           barray -=bs2;
3970         }
3971 
3972         if (in[j] >= cstart && in[j] < cend) {
3973           col  = in[j] - cstart;
3974           ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
3975         } else if (in[j] < 0) continue;
3976 #if defined(PETSC_USE_DEBUG)
3977         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);
3978 #endif
3979         else {
3980           if (mat->was_assembled) {
3981             if (!baij->colmap) {
3982               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
3983             }
3984 
3985 #if defined(PETSC_USE_DEBUG)
3986 #if defined(PETSC_USE_CTABLE)
3987             { PetscInt data;
3988               ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
3989               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3990             }
3991 #else
3992             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3993 #endif
3994 #endif
3995 #if defined(PETSC_USE_CTABLE)
3996             ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
3997             col  = (col - 1)/bs;
3998 #else
3999             col = (baij->colmap[in[j]] - 1)/bs;
4000 #endif
4001             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
4002               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
4003               col  =  in[j];
4004             }
4005           } else col = in[j];
4006           ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
4007         }
4008       }
4009     } else {
4010       if (!baij->donotstash) {
4011         if (roworiented) {
4012           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
4013         } else {
4014           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
4015         }
4016       }
4017     }
4018   }
4019 
4020   /* task normally handled by MatSetValuesBlocked() */
4021   ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr);
4022   PetscFunctionReturn(0);
4023 }
4024 
4025 #undef __FUNCT__
4026 #define __FUNCT__ "MatCreateMPIBAIJWithArrays"
4027 /*@
4028      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
4029          CSR format the local rows.
4030 
4031    Collective on MPI_Comm
4032 
4033    Input Parameters:
4034 +  comm - MPI communicator
4035 .  bs - the block size, only a block size of 1 is supported
4036 .  m - number of local rows (Cannot be PETSC_DECIDE)
4037 .  n - This value should be the same as the local size used in creating the
4038        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
4039        calculated if N is given) For square matrices n is almost always m.
4040 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
4041 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
4042 .   i - row indices
4043 .   j - column indices
4044 -   a - matrix values
4045 
4046    Output Parameter:
4047 .   mat - the matrix
4048 
4049    Level: intermediate
4050 
4051    Notes:
4052        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
4053      thus you CANNOT change the matrix entries by changing the values of a[] after you have
4054      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
4055 
4056        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
4057 
4058 .keywords: matrix, aij, compressed row, sparse, parallel
4059 
4060 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
4061           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
4062 @*/
4063 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)
4064 {
4065   PetscErrorCode ierr;
4066 
4067   PetscFunctionBegin;
4068   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
4069   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
4070   ierr = MatCreate(comm,mat);CHKERRQ(ierr);
4071   ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr);
4072   ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr);
4073   ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr);
4074   PetscFunctionReturn(0);
4075 }
4076