xref: /petsc/src/mat/impls/baij/mpi/mpibaij.c (revision 040ebd07df7f48cdffac40673e8597e52ed39091)
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 #undef __FUNCT__
2249 #define __FUNCT__ "MatGetSeqNonzeroStructure_MPIBAIJ"
2250 PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A,Mat *newmat)
2251 {
2252   Mat            B;
2253   Mat_MPIBAIJ    *a  = (Mat_MPIBAIJ*)A->data;
2254   Mat_SeqBAIJ    *ad = (Mat_SeqBAIJ*)a->A->data,*bd = (Mat_SeqBAIJ*)a->B->data;
2255   Mat_SeqAIJ     *b;
2256   PetscErrorCode ierr;
2257   PetscMPIInt    size,rank,*recvcounts = 0,*displs = 0;
2258   PetscInt       sendcount,i,*rstarts = A->rmap->range,n,cnt,j,bs = A->rmap->bs;
2259   PetscInt       m,*garray = a->garray,*lens,*jsendbuf,*a_jsendbuf,*b_jsendbuf;
2260 
2261   PetscFunctionBegin;
2262   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr);
2263   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr);
2264 
2265   /* ----------------------------------------------------------------
2266      Tell every processor the number of nonzeros per row
2267   */
2268   ierr = PetscMalloc((A->rmap->N/bs)*sizeof(PetscInt),&lens);CHKERRQ(ierr);
2269   for (i=A->rmap->rstart/bs; i<A->rmap->rend/bs; i++) {
2270     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];
2271   }
2272   sendcount = A->rmap->rend/bs - A->rmap->rstart/bs;
2273   ierr      = PetscMalloc(2*size*sizeof(PetscMPIInt),&recvcounts);CHKERRQ(ierr);
2274   displs    = recvcounts + size;
2275   for (i=0; i<size; i++) {
2276     recvcounts[i] = A->rmap->range[i+1]/bs - A->rmap->range[i]/bs;
2277     displs[i]     = A->rmap->range[i]/bs;
2278   }
2279 #if defined(PETSC_HAVE_MPI_IN_PLACE)
2280   ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2281 #else
2282   ierr = MPI_Allgatherv(lens+A->rmap->rstart/bs,sendcount,MPIU_INT,lens,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2283 #endif
2284   /* ---------------------------------------------------------------
2285      Create the sequential matrix of the same type as the local block diagonal
2286   */
2287   ierr = MatCreate(PETSC_COMM_SELF,&B);CHKERRQ(ierr);
2288   ierr = MatSetSizes(B,A->rmap->N/bs,A->cmap->N/bs,PETSC_DETERMINE,PETSC_DETERMINE);CHKERRQ(ierr);
2289   ierr = MatSetType(B,MATSEQAIJ);CHKERRQ(ierr);
2290   ierr = MatSeqAIJSetPreallocation(B,0,lens);CHKERRQ(ierr);
2291   b    = (Mat_SeqAIJ*)B->data;
2292 
2293   /*--------------------------------------------------------------------
2294     Copy my part of matrix column indices over
2295   */
2296   sendcount  = ad->nz + bd->nz;
2297   jsendbuf   = b->j + b->i[rstarts[rank]/bs];
2298   a_jsendbuf = ad->j;
2299   b_jsendbuf = bd->j;
2300   n          = A->rmap->rend/bs - A->rmap->rstart/bs;
2301   cnt        = 0;
2302   for (i=0; i<n; i++) {
2303 
2304     /* put in lower diagonal portion */
2305     m = bd->i[i+1] - bd->i[i];
2306     while (m > 0) {
2307       /* is it above diagonal (in bd (compressed) numbering) */
2308       if (garray[*b_jsendbuf] > A->rmap->rstart/bs + i) break;
2309       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2310       m--;
2311     }
2312 
2313     /* put in diagonal portion */
2314     for (j=ad->i[i]; j<ad->i[i+1]; j++) {
2315       jsendbuf[cnt++] = A->rmap->rstart/bs + *a_jsendbuf++;
2316     }
2317 
2318     /* put in upper diagonal portion */
2319     while (m-- > 0) {
2320       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2321     }
2322   }
2323   if (cnt != sendcount) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupted PETSc matrix: nz given %D actual nz %D",sendcount,cnt);
2324 
2325   /*--------------------------------------------------------------------
2326     Gather all column indices to all processors
2327   */
2328   for (i=0; i<size; i++) {
2329     recvcounts[i] = 0;
2330     for (j=A->rmap->range[i]/bs; j<A->rmap->range[i+1]/bs; j++) {
2331       recvcounts[i] += lens[j];
2332     }
2333   }
2334   displs[0] = 0;
2335   for (i=1; i<size; i++) {
2336     displs[i] = displs[i-1] + recvcounts[i-1];
2337   }
2338 #if defined(PETSC_HAVE_MPI_IN_PLACE)
2339   ierr = MPI_Allgatherv(MPI_IN_PLACE,0,MPI_DATATYPE_NULL,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2340 #else
2341   ierr = MPI_Allgatherv(jsendbuf,sendcount,MPIU_INT,b->j,recvcounts,displs,MPIU_INT,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2342 #endif
2343   /*--------------------------------------------------------------------
2344     Assemble the matrix into useable form (note numerical values not yet set)
2345   */
2346   /* set the b->ilen (length of each row) values */
2347   ierr = PetscMemcpy(b->ilen,lens,(A->rmap->N/bs)*sizeof(PetscInt));CHKERRQ(ierr);
2348   /* set the b->i indices */
2349   b->i[0] = 0;
2350   for (i=1; i<=A->rmap->N/bs; i++) {
2351     b->i[i] = b->i[i-1] + lens[i-1];
2352   }
2353   ierr = PetscFree(lens);CHKERRQ(ierr);
2354   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2355   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2356   ierr = PetscFree(recvcounts);CHKERRQ(ierr);
2357 
2358   if (A->symmetric) {
2359     ierr = MatSetOption(B,MAT_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
2360   } else if (A->hermitian) {
2361     ierr = MatSetOption(B,MAT_HERMITIAN,PETSC_TRUE);CHKERRQ(ierr);
2362   } else if (A->structurally_symmetric) {
2363     ierr = MatSetOption(B,MAT_STRUCTURALLY_SYMMETRIC,PETSC_TRUE);CHKERRQ(ierr);
2364   }
2365   *newmat = B;
2366   PetscFunctionReturn(0);
2367 }
2368 
2369 #undef __FUNCT__
2370 #define __FUNCT__ "MatSOR_MPIBAIJ"
2371 PetscErrorCode MatSOR_MPIBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2372 {
2373   Mat_MPIBAIJ    *mat = (Mat_MPIBAIJ*)matin->data;
2374   PetscErrorCode ierr;
2375   Vec            bb1 = 0;
2376 
2377   PetscFunctionBegin;
2378   if (flag == SOR_APPLY_UPPER) {
2379     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2380     PetscFunctionReturn(0);
2381   }
2382 
2383   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) {
2384     ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr);
2385   }
2386 
2387   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2388     if (flag & SOR_ZERO_INITIAL_GUESS) {
2389       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2390       its--;
2391     }
2392 
2393     while (its--) {
2394       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2395       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2396 
2397       /* update rhs: bb1 = bb - B*x */
2398       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2399       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2400 
2401       /* local sweep */
2402       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2403     }
2404   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
2405     if (flag & SOR_ZERO_INITIAL_GUESS) {
2406       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2407       its--;
2408     }
2409     while (its--) {
2410       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2411       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2412 
2413       /* update rhs: bb1 = bb - B*x */
2414       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2415       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2416 
2417       /* local sweep */
2418       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2419     }
2420   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
2421     if (flag & SOR_ZERO_INITIAL_GUESS) {
2422       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2423       its--;
2424     }
2425     while (its--) {
2426       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2427       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2428 
2429       /* update rhs: bb1 = bb - B*x */
2430       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2431       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);CHKERRQ(ierr);
2432 
2433       /* local sweep */
2434       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);CHKERRQ(ierr);
2435     }
2436   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel version of SOR requested not supported");
2437 
2438   ierr = VecDestroy(&bb1);CHKERRQ(ierr);
2439   PetscFunctionReturn(0);
2440 }
2441 
2442 #undef __FUNCT__
2443 #define __FUNCT__ "MatInvertBlockDiagonal_MPIBAIJ"
2444 PetscErrorCode  MatInvertBlockDiagonal_MPIBAIJ(Mat A,const PetscScalar **values)
2445 {
2446   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*) A->data;
2447   PetscErrorCode ierr;
2448 
2449   PetscFunctionBegin;
2450   ierr = MatInvertBlockDiagonal(a->A,values);CHKERRQ(ierr);
2451   PetscFunctionReturn(0);
2452 }
2453 
2454 
2455 /* -------------------------------------------------------------------*/
2456 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
2457                                        MatGetRow_MPIBAIJ,
2458                                        MatRestoreRow_MPIBAIJ,
2459                                        MatMult_MPIBAIJ,
2460                                 /* 4*/ MatMultAdd_MPIBAIJ,
2461                                        MatMultTranspose_MPIBAIJ,
2462                                        MatMultTransposeAdd_MPIBAIJ,
2463                                        0,
2464                                        0,
2465                                        0,
2466                                 /*10*/ 0,
2467                                        0,
2468                                        0,
2469                                        MatSOR_MPIBAIJ,
2470                                        MatTranspose_MPIBAIJ,
2471                                 /*15*/ MatGetInfo_MPIBAIJ,
2472                                        MatEqual_MPIBAIJ,
2473                                        MatGetDiagonal_MPIBAIJ,
2474                                        MatDiagonalScale_MPIBAIJ,
2475                                        MatNorm_MPIBAIJ,
2476                                 /*20*/ MatAssemblyBegin_MPIBAIJ,
2477                                        MatAssemblyEnd_MPIBAIJ,
2478                                        MatSetOption_MPIBAIJ,
2479                                        MatZeroEntries_MPIBAIJ,
2480                                 /*24*/ MatZeroRows_MPIBAIJ,
2481                                        0,
2482                                        0,
2483                                        0,
2484                                        0,
2485                                 /*29*/ MatSetUp_MPIBAIJ,
2486                                        0,
2487                                        0,
2488                                        0,
2489                                        0,
2490                                 /*34*/ MatDuplicate_MPIBAIJ,
2491                                        0,
2492                                        0,
2493                                        0,
2494                                        0,
2495                                 /*39*/ MatAXPY_MPIBAIJ,
2496                                        MatGetSubMatrices_MPIBAIJ,
2497                                        MatIncreaseOverlap_MPIBAIJ,
2498                                        MatGetValues_MPIBAIJ,
2499                                        MatCopy_MPIBAIJ,
2500                                 /*44*/ 0,
2501                                        MatScale_MPIBAIJ,
2502                                        0,
2503                                        0,
2504                                        0,
2505                                 /*49*/ 0,
2506                                        0,
2507                                        0,
2508                                        0,
2509                                        0,
2510                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
2511                                        0,
2512                                        MatSetUnfactored_MPIBAIJ,
2513                                        MatPermute_MPIBAIJ,
2514                                        MatSetValuesBlocked_MPIBAIJ,
2515                                 /*59*/ MatGetSubMatrix_MPIBAIJ,
2516                                        MatDestroy_MPIBAIJ,
2517                                        MatView_MPIBAIJ,
2518                                        0,
2519                                        0,
2520                                 /*64*/ 0,
2521                                        0,
2522                                        0,
2523                                        0,
2524                                        0,
2525                                 /*69*/ MatGetRowMaxAbs_MPIBAIJ,
2526                                        0,
2527                                        0,
2528                                        0,
2529                                        0,
2530                                 /*74*/ 0,
2531                                        MatFDColoringApply_BAIJ,
2532                                        0,
2533                                        0,
2534                                        0,
2535                                 /*79*/ 0,
2536                                        0,
2537                                        0,
2538                                        0,
2539                                        MatLoad_MPIBAIJ,
2540                                 /*84*/ 0,
2541                                        0,
2542                                        0,
2543                                        0,
2544                                        0,
2545                                 /*89*/ 0,
2546                                        0,
2547                                        0,
2548                                        0,
2549                                        0,
2550                                 /*94*/ 0,
2551                                        0,
2552                                        0,
2553                                        0,
2554                                        0,
2555                                 /*99*/ 0,
2556                                        0,
2557                                        0,
2558                                        0,
2559                                        0,
2560                                 /*104*/0,
2561                                        MatRealPart_MPIBAIJ,
2562                                        MatImaginaryPart_MPIBAIJ,
2563                                        0,
2564                                        0,
2565                                 /*109*/0,
2566                                        0,
2567                                        0,
2568                                        0,
2569                                        0,
2570                                 /*114*/MatGetSeqNonzeroStructure_MPIBAIJ,
2571                                        0,
2572                                        MatGetGhosts_MPIBAIJ,
2573                                        0,
2574                                        0,
2575                                 /*119*/0,
2576                                        0,
2577                                        0,
2578                                        0,
2579                                        MatGetMultiProcBlock_MPIBAIJ,
2580                                 /*124*/0,
2581                                        0,
2582                                        MatInvertBlockDiagonal_MPIBAIJ,
2583                                        0,
2584                                        0,
2585                                /*129*/ 0,
2586                                        0,
2587                                        0,
2588                                        0,
2589                                        0,
2590                                /*134*/ 0,
2591                                        0,
2592                                        0,
2593                                        0,
2594                                        0,
2595                                /*139*/ 0,
2596                                        0
2597 };
2598 
2599 #undef __FUNCT__
2600 #define __FUNCT__ "MatGetDiagonalBlock_MPIBAIJ"
2601 PetscErrorCode  MatGetDiagonalBlock_MPIBAIJ(Mat A,Mat *a)
2602 {
2603   PetscFunctionBegin;
2604   *a = ((Mat_MPIBAIJ*)A->data)->A;
2605   PetscFunctionReturn(0);
2606 }
2607 
2608 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType,MatReuse,Mat*);
2609 
2610 #undef __FUNCT__
2611 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR_MPIBAIJ"
2612 PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2613 {
2614   PetscInt       m,rstart,cstart,cend;
2615   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
2616   const PetscInt *JJ    =0;
2617   PetscScalar    *values=0;
2618   PetscErrorCode ierr;
2619 
2620   PetscFunctionBegin;
2621   ierr   = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr);
2622   ierr   = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr);
2623   ierr   = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
2624   ierr   = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
2625   ierr   = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
2626   m      = B->rmap->n/bs;
2627   rstart = B->rmap->rstart/bs;
2628   cstart = B->cmap->rstart/bs;
2629   cend   = B->cmap->rend/bs;
2630 
2631   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
2632   ierr = PetscMalloc2(m,PetscInt,&d_nnz,m,PetscInt,&o_nnz);CHKERRQ(ierr);
2633   for (i=0; i<m; i++) {
2634     nz = ii[i+1] - ii[i];
2635     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
2636     nz_max = PetscMax(nz_max,nz);
2637     JJ     = jj + ii[i];
2638     for (j=0; j<nz; j++) {
2639       if (*JJ >= cstart) break;
2640       JJ++;
2641     }
2642     d = 0;
2643     for (; j<nz; j++) {
2644       if (*JJ++ >= cend) break;
2645       d++;
2646     }
2647     d_nnz[i] = d;
2648     o_nnz[i] = nz - d;
2649   }
2650   ierr = MatMPIBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr);
2651   ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr);
2652 
2653   values = (PetscScalar*)V;
2654   if (!values) {
2655     ierr = PetscMalloc(bs*bs*nz_max*sizeof(PetscScalar),&values);CHKERRQ(ierr);
2656     ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr);
2657   }
2658   for (i=0; i<m; i++) {
2659     PetscInt          row    = i + rstart;
2660     PetscInt          ncols  = ii[i+1] - ii[i];
2661     const PetscInt    *icols = jj + ii[i];
2662     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2663     ierr = MatSetValuesBlocked_MPIBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr);
2664   }
2665 
2666   if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); }
2667   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2668   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2669   ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);
2670   PetscFunctionReturn(0);
2671 }
2672 
2673 #undef __FUNCT__
2674 #define __FUNCT__ "MatMPIBAIJSetPreallocationCSR"
2675 /*@C
2676    MatMPIBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2677    (the default parallel PETSc format).
2678 
2679    Collective on MPI_Comm
2680 
2681    Input Parameters:
2682 +  A - the matrix
2683 .  bs - the block size
2684 .  i - the indices into j for the start of each local row (starts with zero)
2685 .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2686 -  v - optional values in the matrix
2687 
2688    Level: developer
2689 
2690 .keywords: matrix, aij, compressed row, sparse, parallel
2691 
2692 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2693 @*/
2694 PetscErrorCode  MatMPIBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2695 {
2696   PetscErrorCode ierr;
2697 
2698   PetscFunctionBegin;
2699   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
2700   PetscValidType(B,1);
2701   PetscValidLogicalCollectiveInt(B,bs,2);
2702   ierr = PetscTryMethod(B,"MatMPIBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr);
2703   PetscFunctionReturn(0);
2704 }
2705 
2706 #undef __FUNCT__
2707 #define __FUNCT__ "MatMPIBAIJSetPreallocation_MPIBAIJ"
2708 PetscErrorCode  MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
2709 {
2710   Mat_MPIBAIJ    *b;
2711   PetscErrorCode ierr;
2712   PetscInt       i;
2713 
2714   PetscFunctionBegin;
2715   ierr = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr);
2716   ierr = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr);
2717   ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
2718   ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
2719   ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
2720 
2721   if (d_nnz) {
2722     for (i=0; i<B->rmap->n/bs; i++) {
2723       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]);
2724     }
2725   }
2726   if (o_nnz) {
2727     for (i=0; i<B->rmap->n/bs; i++) {
2728       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]);
2729     }
2730   }
2731 
2732   b      = (Mat_MPIBAIJ*)B->data;
2733   b->bs2 = bs*bs;
2734   b->mbs = B->rmap->n/bs;
2735   b->nbs = B->cmap->n/bs;
2736   b->Mbs = B->rmap->N/bs;
2737   b->Nbs = B->cmap->N/bs;
2738 
2739   for (i=0; i<=b->size; i++) {
2740     b->rangebs[i] = B->rmap->range[i]/bs;
2741   }
2742   b->rstartbs = B->rmap->rstart/bs;
2743   b->rendbs   = B->rmap->rend/bs;
2744   b->cstartbs = B->cmap->rstart/bs;
2745   b->cendbs   = B->cmap->rend/bs;
2746 
2747   if (!B->preallocated) {
2748     ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr);
2749     ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr);
2750     ierr = MatSetType(b->A,MATSEQBAIJ);CHKERRQ(ierr);
2751     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr);
2752     ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr);
2753     ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr);
2754     ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr);
2755     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr);
2756     ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr);
2757   }
2758 
2759   ierr = MatSeqBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr);
2760   ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr);
2761   B->preallocated = PETSC_TRUE;
2762   PetscFunctionReturn(0);
2763 }
2764 
2765 extern PetscErrorCode  MatDiagonalScaleLocal_MPIBAIJ(Mat,Vec);
2766 extern PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat,PetscReal);
2767 
2768 #undef __FUNCT__
2769 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAdj"
2770 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype,MatReuse reuse,Mat *adj)
2771 {
2772   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ*)B->data;
2773   PetscErrorCode ierr;
2774   Mat_SeqBAIJ    *d  = (Mat_SeqBAIJ*) b->A->data,*o = (Mat_SeqBAIJ*) b->B->data;
2775   PetscInt       M   = B->rmap->n/B->rmap->bs,i,*ii,*jj,cnt,j,k,rstart = B->rmap->rstart/B->rmap->bs;
2776   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;
2777 
2778   PetscFunctionBegin;
2779   ierr  = PetscMalloc((M+1)*sizeof(PetscInt),&ii);CHKERRQ(ierr);
2780   ii[0] = 0;
2781   for (i=0; i<M; i++) {
2782     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]);
2783     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]);
2784     ii[i+1] = ii[i] + id[i+1] - id[i] + io[i+1] - io[i];
2785     /* remove one from count of matrix has diagonal */
2786     for (j=id[i]; j<id[i+1]; j++) {
2787       if (jd[j] == i) {ii[i+1]--;break;}
2788     }
2789   }
2790   ierr = PetscMalloc(ii[M]*sizeof(PetscInt),&jj);CHKERRQ(ierr);
2791   cnt  = 0;
2792   for (i=0; i<M; i++) {
2793     for (j=io[i]; j<io[i+1]; j++) {
2794       if (garray[jo[j]] > rstart) break;
2795       jj[cnt++] = garray[jo[j]];
2796     }
2797     for (k=id[i]; k<id[i+1]; k++) {
2798       if (jd[k] != i) {
2799         jj[cnt++] = rstart + jd[k];
2800       }
2801     }
2802     for (; j<io[i+1]; j++) {
2803       jj[cnt++] = garray[jo[j]];
2804     }
2805   }
2806   ierr = MatCreateMPIAdj(PetscObjectComm((PetscObject)B),M,B->cmap->N/B->rmap->bs,ii,jj,NULL,adj);CHKERRQ(ierr);
2807   PetscFunctionReturn(0);
2808 }
2809 
2810 #include <../src/mat/impls/aij/mpi/mpiaij.h>
2811 
2812 PETSC_EXTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat,MatType,MatReuse,Mat*);
2813 
2814 #undef __FUNCT__
2815 #define __FUNCT__ "MatConvert_MPIBAIJ_MPIAIJ"
2816 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
2817 {
2818   PetscErrorCode ierr;
2819   Mat_MPIBAIJ    *a = (Mat_MPIBAIJ*)A->data;
2820   Mat            B;
2821   Mat_MPIAIJ     *b;
2822 
2823   PetscFunctionBegin;
2824   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");
2825 
2826   ierr = MatCreate(PetscObjectComm((PetscObject)A),&B);CHKERRQ(ierr);
2827   ierr = MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);CHKERRQ(ierr);
2828   ierr = MatSetType(B,MATMPIAIJ);CHKERRQ(ierr);
2829   ierr = MatSeqAIJSetPreallocation(B,0,NULL);CHKERRQ(ierr);
2830   ierr = MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);CHKERRQ(ierr);
2831   b    = (Mat_MPIAIJ*) B->data;
2832 
2833   ierr = MatDestroy(&b->A);CHKERRQ(ierr);
2834   ierr = MatDestroy(&b->B);CHKERRQ(ierr);
2835   ierr = MatDisAssemble_MPIBAIJ(A);CHKERRQ(ierr);
2836   ierr = MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);CHKERRQ(ierr);
2837   ierr = MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);CHKERRQ(ierr);
2838   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2839   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2840   ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2841   ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2842   if (reuse == MAT_REUSE_MATRIX) {
2843     ierr = MatHeaderReplace(A,B);CHKERRQ(ierr);
2844   } else {
2845    *newmat = B;
2846   }
2847   PetscFunctionReturn(0);
2848 }
2849 
2850 #if defined(PETSC_HAVE_MUMPS)
2851 PETSC_EXTERN PetscErrorCode MatGetFactor_baij_mumps(Mat,MatFactorType,Mat*);
2852 #endif
2853 
2854 /*MC
2855    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.
2856 
2857    Options Database Keys:
2858 + -mat_type mpibaij - sets the matrix type to "mpibaij" during a call to MatSetFromOptions()
2859 . -mat_block_size <bs> - set the blocksize used to store the matrix
2860 - -mat_use_hash_table <fact>
2861 
2862   Level: beginner
2863 
2864 .seealso: MatCreateMPIBAIJ
2865 M*/
2866 
2867 PETSC_EXTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat,MatType,MatReuse,Mat*);
2868 
2869 #undef __FUNCT__
2870 #define __FUNCT__ "MatCreate_MPIBAIJ"
2871 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
2872 {
2873   Mat_MPIBAIJ    *b;
2874   PetscErrorCode ierr;
2875   PetscBool      flg;
2876 
2877   PetscFunctionBegin;
2878   ierr    = PetscNewLog(B,Mat_MPIBAIJ,&b);CHKERRQ(ierr);
2879   B->data = (void*)b;
2880 
2881   ierr         = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr);
2882   B->assembled = PETSC_FALSE;
2883 
2884   B->insertmode = NOT_SET_VALUES;
2885   ierr          = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr);
2886   ierr          = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr);
2887 
2888   /* build local table of row and column ownerships */
2889   ierr = PetscMalloc((b->size+1)*sizeof(PetscInt),&b->rangebs);CHKERRQ(ierr);
2890 
2891   /* build cache for off array entries formed */
2892   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr);
2893 
2894   b->donotstash  = PETSC_FALSE;
2895   b->colmap      = NULL;
2896   b->garray      = NULL;
2897   b->roworiented = PETSC_TRUE;
2898 
2899   /* stuff used in block assembly */
2900   b->barray = 0;
2901 
2902   /* stuff used for matrix vector multiply */
2903   b->lvec  = 0;
2904   b->Mvctx = 0;
2905 
2906   /* stuff for MatGetRow() */
2907   b->rowindices   = 0;
2908   b->rowvalues    = 0;
2909   b->getrowactive = PETSC_FALSE;
2910 
2911   /* hash table stuff */
2912   b->ht           = 0;
2913   b->hd           = 0;
2914   b->ht_size      = 0;
2915   b->ht_flag      = PETSC_FALSE;
2916   b->ht_fact      = 0;
2917   b->ht_total_ct  = 0;
2918   b->ht_insert_ct = 0;
2919 
2920   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
2921   b->ijonly = PETSC_FALSE;
2922 
2923   ierr = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPIBAIJ matrix 1","Mat");CHKERRQ(ierr);
2924   ierr = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr);
2925   if (flg) {
2926     PetscReal fact = 1.39;
2927     ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr);
2928     ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr);
2929     if (fact <= 1.0) fact = 1.39;
2930     ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr);
2931     ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr);
2932   }
2933   ierr = PetscOptionsEnd();CHKERRQ(ierr);
2934 
2935 #if defined(PETSC_HAVE_MUMPS)
2936   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_baij_mumps);CHKERRQ(ierr);
2937 #endif
2938   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiadj_C",MatConvert_MPIBAIJ_MPIAdj);CHKERRQ(ierr);
2939   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpiaij_C",MatConvert_MPIBAIJ_MPIAIJ);CHKERRQ(ierr);
2940   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpisbaij_C",MatConvert_MPIBAIJ_MPISBAIJ);CHKERRQ(ierr);
2941   ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPIBAIJ);CHKERRQ(ierr);
2942   ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPIBAIJ);CHKERRQ(ierr);
2943   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPIBAIJ);CHKERRQ(ierr);
2944   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocation_C",MatMPIBAIJSetPreallocation_MPIBAIJ);CHKERRQ(ierr);
2945   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPIBAIJSetPreallocationCSR_C",MatMPIBAIJSetPreallocationCSR_MPIBAIJ);CHKERRQ(ierr);
2946   ierr = PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPIBAIJ);CHKERRQ(ierr);
2947   ierr = PetscObjectComposeFunction((PetscObject)B,"MatSetHashTableFactor_C",MatSetHashTableFactor_MPIBAIJ);CHKERRQ(ierr);
2948   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpibaij_mpibstrm_C",MatConvert_MPIBAIJ_MPIBSTRM);CHKERRQ(ierr);
2949   ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPIBAIJ);CHKERRQ(ierr);
2950   PetscFunctionReturn(0);
2951 }
2952 
2953 /*MC
2954    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.
2955 
2956    This matrix type is identical to MATSEQBAIJ when constructed with a single process communicator,
2957    and MATMPIBAIJ otherwise.
2958 
2959    Options Database Keys:
2960 . -mat_type baij - sets the matrix type to "baij" during a call to MatSetFromOptions()
2961 
2962   Level: beginner
2963 
2964 .seealso: MatCreateBAIJ(),MATSEQBAIJ,MATMPIBAIJ, MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
2965 M*/
2966 
2967 #undef __FUNCT__
2968 #define __FUNCT__ "MatMPIBAIJSetPreallocation"
2969 /*@C
2970    MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in block AIJ format
2971    (block compressed row).  For good matrix assembly performance
2972    the user should preallocate the matrix storage by setting the parameters
2973    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
2974    performance can be increased by more than a factor of 50.
2975 
2976    Collective on Mat
2977 
2978    Input Parameters:
2979 +  A - the matrix
2980 .  bs   - size of block
2981 .  d_nz  - number of block nonzeros per block row in diagonal portion of local
2982            submatrix  (same for all local rows)
2983 .  d_nnz - array containing the number of block nonzeros in the various block rows
2984            of the in diagonal portion of the local (possibly different for each block
2985            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry and
2986            set it even if it is zero.
2987 .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2988            submatrix (same for all local rows).
2989 -  o_nnz - array containing the number of nonzeros in the various block rows of the
2990            off-diagonal portion of the local submatrix (possibly different for
2991            each block row) or NULL.
2992 
2993    If the *_nnz parameter is given then the *_nz parameter is ignored
2994 
2995    Options Database Keys:
2996 +   -mat_block_size - size of the blocks to use
2997 -   -mat_use_hash_table <fact>
2998 
2999    Notes:
3000    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3001    than it must be used on all processors that share the object for that argument.
3002 
3003    Storage Information:
3004    For a square global matrix we define each processor's diagonal portion
3005    to be its local rows and the corresponding columns (a square submatrix);
3006    each processor's off-diagonal portion encompasses the remainder of the
3007    local matrix (a rectangular submatrix).
3008 
3009    The user can specify preallocated storage for the diagonal part of
3010    the local submatrix with either d_nz or d_nnz (not both).  Set
3011    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3012    memory allocation.  Likewise, specify preallocated storage for the
3013    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
3014 
3015    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3016    the figure below we depict these three local rows and all columns (0-11).
3017 
3018 .vb
3019            0 1 2 3 4 5 6 7 8 9 10 11
3020           --------------------------
3021    row 3  |o o o d d d o o o o  o  o
3022    row 4  |o o o d d d o o o o  o  o
3023    row 5  |o o o d d d o o o o  o  o
3024           --------------------------
3025 .ve
3026 
3027    Thus, any entries in the d locations are stored in the d (diagonal)
3028    submatrix, and any entries in the o locations are stored in the
3029    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3030    stored simply in the MATSEQBAIJ format for compressed row storage.
3031 
3032    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3033    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3034    In general, for PDE problems in which most nonzeros are near the diagonal,
3035    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3036    or you will get TERRIBLE performance; see the users' manual chapter on
3037    matrices.
3038 
3039    You can call MatGetInfo() to get information on how effective the preallocation was;
3040    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3041    You can also run with the option -info and look for messages with the string
3042    malloc in them to see if additional memory allocation was needed.
3043 
3044    Level: intermediate
3045 
3046 .keywords: matrix, block, aij, compressed row, sparse, parallel
3047 
3048 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocationCSR(), PetscSplitOwnership()
3049 @*/
3050 PetscErrorCode  MatMPIBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
3051 {
3052   PetscErrorCode ierr;
3053 
3054   PetscFunctionBegin;
3055   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
3056   PetscValidType(B,1);
3057   PetscValidLogicalCollectiveInt(B,bs,2);
3058   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);
3059   PetscFunctionReturn(0);
3060 }
3061 
3062 #undef __FUNCT__
3063 #define __FUNCT__ "MatCreateBAIJ"
3064 /*@C
3065    MatCreateBAIJ - Creates a sparse parallel matrix in block AIJ format
3066    (block compressed row).  For good matrix assembly performance
3067    the user should preallocate the matrix storage by setting the parameters
3068    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
3069    performance can be increased by more than a factor of 50.
3070 
3071    Collective on MPI_Comm
3072 
3073    Input Parameters:
3074 +  comm - MPI communicator
3075 .  bs   - size of blockk
3076 .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
3077            This value should be the same as the local size used in creating the
3078            y vector for the matrix-vector product y = Ax.
3079 .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
3080            This value should be the same as the local size used in creating the
3081            x vector for the matrix-vector product y = Ax.
3082 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3083 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3084 .  d_nz  - number of nonzero blocks per block row in diagonal portion of local
3085            submatrix  (same for all local rows)
3086 .  d_nnz - array containing the number of nonzero blocks in the various block rows
3087            of the in diagonal portion of the local (possibly different for each block
3088            row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
3089            and set it even if it is zero.
3090 .  o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
3091            submatrix (same for all local rows).
3092 -  o_nnz - array containing the number of nonzero blocks in the various block rows of the
3093            off-diagonal portion of the local submatrix (possibly different for
3094            each block row) or NULL.
3095 
3096    Output Parameter:
3097 .  A - the matrix
3098 
3099    Options Database Keys:
3100 +   -mat_block_size - size of the blocks to use
3101 -   -mat_use_hash_table <fact>
3102 
3103    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3104    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3105    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
3106 
3107    Notes:
3108    If the *_nnz parameter is given then the *_nz parameter is ignored
3109 
3110    A nonzero block is any block that as 1 or more nonzeros in it
3111 
3112    The user MUST specify either the local or global matrix dimensions
3113    (possibly both).
3114 
3115    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
3116    than it must be used on all processors that share the object for that argument.
3117 
3118    Storage Information:
3119    For a square global matrix we define each processor's diagonal portion
3120    to be its local rows and the corresponding columns (a square submatrix);
3121    each processor's off-diagonal portion encompasses the remainder of the
3122    local matrix (a rectangular submatrix).
3123 
3124    The user can specify preallocated storage for the diagonal part of
3125    the local submatrix with either d_nz or d_nnz (not both).  Set
3126    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
3127    memory allocation.  Likewise, specify preallocated storage for the
3128    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
3129 
3130    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3131    the figure below we depict these three local rows and all columns (0-11).
3132 
3133 .vb
3134            0 1 2 3 4 5 6 7 8 9 10 11
3135           --------------------------
3136    row 3  |o o o d d d o o o o  o  o
3137    row 4  |o o o d d d o o o o  o  o
3138    row 5  |o o o d d d o o o o  o  o
3139           --------------------------
3140 .ve
3141 
3142    Thus, any entries in the d locations are stored in the d (diagonal)
3143    submatrix, and any entries in the o locations are stored in the
3144    o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3145    stored simply in the MATSEQBAIJ format for compressed row storage.
3146 
3147    Now d_nz should indicate the number of block nonzeros per row in the d matrix,
3148    and o_nz should indicate the number of block nonzeros per row in the o matrix.
3149    In general, for PDE problems in which most nonzeros are near the diagonal,
3150    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
3151    or you will get TERRIBLE performance; see the users' manual chapter on
3152    matrices.
3153 
3154    Level: intermediate
3155 
3156 .keywords: matrix, block, aij, compressed row, sparse, parallel
3157 
3158 .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatCreateBAIJ(), MatMPIBAIJSetPreallocation(), MatMPIBAIJSetPreallocationCSR()
3159 @*/
3160 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)
3161 {
3162   PetscErrorCode ierr;
3163   PetscMPIInt    size;
3164 
3165   PetscFunctionBegin;
3166   ierr = MatCreate(comm,A);CHKERRQ(ierr);
3167   ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr);
3168   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
3169   if (size > 1) {
3170     ierr = MatSetType(*A,MATMPIBAIJ);CHKERRQ(ierr);
3171     ierr = MatMPIBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr);
3172   } else {
3173     ierr = MatSetType(*A,MATSEQBAIJ);CHKERRQ(ierr);
3174     ierr = MatSeqBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr);
3175   }
3176   PetscFunctionReturn(0);
3177 }
3178 
3179 #undef __FUNCT__
3180 #define __FUNCT__ "MatDuplicate_MPIBAIJ"
3181 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
3182 {
3183   Mat            mat;
3184   Mat_MPIBAIJ    *a,*oldmat = (Mat_MPIBAIJ*)matin->data;
3185   PetscErrorCode ierr;
3186   PetscInt       len=0;
3187 
3188   PetscFunctionBegin;
3189   *newmat = 0;
3190   ierr    = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr);
3191   ierr    = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr);
3192   ierr    = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr);
3193   ierr    = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr);
3194 
3195   mat->factortype   = matin->factortype;
3196   mat->preallocated = PETSC_TRUE;
3197   mat->assembled    = PETSC_TRUE;
3198   mat->insertmode   = NOT_SET_VALUES;
3199 
3200   a             = (Mat_MPIBAIJ*)mat->data;
3201   mat->rmap->bs = matin->rmap->bs;
3202   a->bs2        = oldmat->bs2;
3203   a->mbs        = oldmat->mbs;
3204   a->nbs        = oldmat->nbs;
3205   a->Mbs        = oldmat->Mbs;
3206   a->Nbs        = oldmat->Nbs;
3207 
3208   ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr);
3209   ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr);
3210 
3211   a->size         = oldmat->size;
3212   a->rank         = oldmat->rank;
3213   a->donotstash   = oldmat->donotstash;
3214   a->roworiented  = oldmat->roworiented;
3215   a->rowindices   = 0;
3216   a->rowvalues    = 0;
3217   a->getrowactive = PETSC_FALSE;
3218   a->barray       = 0;
3219   a->rstartbs     = oldmat->rstartbs;
3220   a->rendbs       = oldmat->rendbs;
3221   a->cstartbs     = oldmat->cstartbs;
3222   a->cendbs       = oldmat->cendbs;
3223 
3224   /* hash table stuff */
3225   a->ht           = 0;
3226   a->hd           = 0;
3227   a->ht_size      = 0;
3228   a->ht_flag      = oldmat->ht_flag;
3229   a->ht_fact      = oldmat->ht_fact;
3230   a->ht_total_ct  = 0;
3231   a->ht_insert_ct = 0;
3232 
3233   ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+1)*sizeof(PetscInt));CHKERRQ(ierr);
3234   if (oldmat->colmap) {
3235 #if defined(PETSC_USE_CTABLE)
3236     ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr);
3237 #else
3238     ierr = PetscMalloc((a->Nbs)*sizeof(PetscInt),&a->colmap);CHKERRQ(ierr);
3239     ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
3240     ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
3241 #endif
3242   } else a->colmap = 0;
3243 
3244   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
3245     ierr = PetscMalloc(len*sizeof(PetscInt),&a->garray);CHKERRQ(ierr);
3246     ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr);
3247     ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr);
3248   } else a->garray = 0;
3249 
3250   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr);
3251   ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr);
3252   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr);
3253   ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr);
3254   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr);
3255 
3256   ierr    = MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr);
3257   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr);
3258   ierr    = MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr);
3259   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr);
3260   ierr    = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr);
3261   *newmat = mat;
3262   PetscFunctionReturn(0);
3263 }
3264 
3265 #undef __FUNCT__
3266 #define __FUNCT__ "MatLoad_MPIBAIJ"
3267 PetscErrorCode MatLoad_MPIBAIJ(Mat newmat,PetscViewer viewer)
3268 {
3269   PetscErrorCode ierr;
3270   int            fd;
3271   PetscInt       i,nz,j,rstart,rend;
3272   PetscScalar    *vals,*buf;
3273   MPI_Comm       comm;
3274   MPI_Status     status;
3275   PetscMPIInt    rank,size,maxnz;
3276   PetscInt       header[4],*rowlengths = 0,M,N,m,*rowners,*cols;
3277   PetscInt       *locrowlens = NULL,*procsnz = NULL,*browners = NULL;
3278   PetscInt       jj,*mycols,*ibuf,bs=1,Mbs,mbs,extra_rows,mmax;
3279   PetscMPIInt    tag    = ((PetscObject)viewer)->tag;
3280   PetscInt       *dlens = NULL,*odlens = NULL,*mask = NULL,*masked1 = NULL,*masked2 = NULL,rowcount,odcount;
3281   PetscInt       dcount,kmax,k,nzcount,tmp,mend,sizesset=1,grows,gcols;
3282 
3283   PetscFunctionBegin;
3284   ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr);
3285   ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPIBAIJ matrix 2","Mat");CHKERRQ(ierr);
3286   ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr);
3287   ierr = PetscOptionsEnd();CHKERRQ(ierr);
3288 
3289   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
3290   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
3291   if (!rank) {
3292     ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
3293     ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr);
3294     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
3295   }
3296 
3297   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0;
3298 
3299   ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr);
3300   M    = header[1]; N = header[2];
3301 
3302   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
3303   if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M;
3304   if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N;
3305 
3306   /* If global sizes are set, check if they are consistent with that given in the file */
3307   if (sizesset) {
3308     ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr);
3309   }
3310   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);
3311   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);
3312 
3313   if (M != N) SETERRQ(PetscObjectComm((PetscObject)viewer),PETSC_ERR_SUP,"Can only do square matrices");
3314 
3315   /*
3316      This code adds extra rows to make sure the number of rows is
3317      divisible by the blocksize
3318   */
3319   Mbs        = M/bs;
3320   extra_rows = bs - M + bs*Mbs;
3321   if (extra_rows == bs) extra_rows = 0;
3322   else                  Mbs++;
3323   if (extra_rows && !rank) {
3324     ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr);
3325   }
3326 
3327   /* determine ownership of all rows */
3328   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
3329     mbs = Mbs/size + ((Mbs % size) > rank);
3330     m   = mbs*bs;
3331   } else { /* User set */
3332     m   = newmat->rmap->n;
3333     mbs = m/bs;
3334   }
3335   ierr = PetscMalloc2(size+1,PetscInt,&rowners,size+1,PetscInt,&browners);CHKERRQ(ierr);
3336   ierr = MPI_Allgather(&mbs,1,MPIU_INT,rowners+1,1,MPIU_INT,comm);CHKERRQ(ierr);
3337 
3338   /* process 0 needs enough room for process with most rows */
3339   if (!rank) {
3340     mmax = rowners[1];
3341     for (i=2; i<=size; i++) {
3342       mmax = PetscMax(mmax,rowners[i]);
3343     }
3344     mmax*=bs;
3345   } else mmax = -1;             /* unused, but compiler warns anyway */
3346 
3347   rowners[0] = 0;
3348   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
3349   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
3350   rstart = rowners[rank];
3351   rend   = rowners[rank+1];
3352 
3353   /* distribute row lengths to all processors */
3354   ierr = PetscMalloc(m*sizeof(PetscInt),&locrowlens);CHKERRQ(ierr);
3355   if (!rank) {
3356     mend = m;
3357     if (size == 1) mend = mend - extra_rows;
3358     ierr = PetscBinaryRead(fd,locrowlens,mend,PETSC_INT);CHKERRQ(ierr);
3359     for (j=mend; j<m; j++) locrowlens[j] = 1;
3360     ierr = PetscMalloc(mmax*sizeof(PetscInt),&rowlengths);CHKERRQ(ierr);
3361     ierr = PetscMalloc(size*sizeof(PetscInt),&procsnz);CHKERRQ(ierr);
3362     ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr);
3363     for (j=0; j<m; j++) {
3364       procsnz[0] += locrowlens[j];
3365     }
3366     for (i=1; i<size; i++) {
3367       mend = browners[i+1] - browners[i];
3368       if (i == size-1) mend = mend - extra_rows;
3369       ierr = PetscBinaryRead(fd,rowlengths,mend,PETSC_INT);CHKERRQ(ierr);
3370       for (j=mend; j<browners[i+1] - browners[i]; j++) rowlengths[j] = 1;
3371       /* calculate the number of nonzeros on each processor */
3372       for (j=0; j<browners[i+1]-browners[i]; j++) {
3373         procsnz[i] += rowlengths[j];
3374       }
3375       ierr = MPI_Send(rowlengths,browners[i+1]-browners[i],MPIU_INT,i,tag,comm);CHKERRQ(ierr);
3376     }
3377     ierr = PetscFree(rowlengths);CHKERRQ(ierr);
3378   } else {
3379     ierr = MPI_Recv(locrowlens,m,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
3380   }
3381 
3382   if (!rank) {
3383     /* determine max buffer needed and allocate it */
3384     maxnz = procsnz[0];
3385     for (i=1; i<size; i++) {
3386       maxnz = PetscMax(maxnz,procsnz[i]);
3387     }
3388     ierr = PetscMalloc(maxnz*sizeof(PetscInt),&cols);CHKERRQ(ierr);
3389 
3390     /* read in my part of the matrix column indices  */
3391     nz     = procsnz[0];
3392     ierr   = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr);
3393     mycols = ibuf;
3394     if (size == 1) nz -= extra_rows;
3395     ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr);
3396     if (size == 1) {
3397       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
3398     }
3399 
3400     /* read in every ones (except the last) and ship off */
3401     for (i=1; i<size-1; i++) {
3402       nz   = procsnz[i];
3403       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
3404       ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr);
3405     }
3406     /* read in the stuff for the last proc */
3407     if (size != 1) {
3408       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
3409       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
3410       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
3411       ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr);
3412     }
3413     ierr = PetscFree(cols);CHKERRQ(ierr);
3414   } else {
3415     /* determine buffer space needed for message */
3416     nz = 0;
3417     for (i=0; i<m; i++) {
3418       nz += locrowlens[i];
3419     }
3420     ierr   = PetscMalloc((nz+1)*sizeof(PetscInt),&ibuf);CHKERRQ(ierr);
3421     mycols = ibuf;
3422     /* receive message of column indices*/
3423     ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
3424     ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr);
3425     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
3426   }
3427 
3428   /* loop over local rows, determining number of off diagonal entries */
3429   ierr     = PetscMalloc2(rend-rstart,PetscInt,&dlens,rend-rstart,PetscInt,&odlens);CHKERRQ(ierr);
3430   ierr     = PetscMalloc3(Mbs,PetscInt,&mask,Mbs,PetscInt,&masked1,Mbs,PetscInt,&masked2);CHKERRQ(ierr);
3431   ierr     = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
3432   ierr     = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
3433   ierr     = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
3434   rowcount = 0; nzcount = 0;
3435   for (i=0; i<mbs; i++) {
3436     dcount  = 0;
3437     odcount = 0;
3438     for (j=0; j<bs; j++) {
3439       kmax = locrowlens[rowcount];
3440       for (k=0; k<kmax; k++) {
3441         tmp = mycols[nzcount++]/bs;
3442         if (!mask[tmp]) {
3443           mask[tmp] = 1;
3444           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp;
3445           else masked1[dcount++] = tmp;
3446         }
3447       }
3448       rowcount++;
3449     }
3450 
3451     dlens[i]  = dcount;
3452     odlens[i] = odcount;
3453 
3454     /* zero out the mask elements we set */
3455     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
3456     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
3457   }
3458 
3459 
3460   if (!sizesset) {
3461     ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr);
3462   }
3463   ierr = MatMPIBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr);
3464 
3465   if (!rank) {
3466     ierr = PetscMalloc((maxnz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr);
3467     /* read in my part of the matrix numerical values  */
3468     nz     = procsnz[0];
3469     vals   = buf;
3470     mycols = ibuf;
3471     if (size == 1) nz -= extra_rows;
3472     ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3473     if (size == 1) {
3474       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
3475     }
3476 
3477     /* insert into matrix */
3478     jj = rstart*bs;
3479     for (i=0; i<m; i++) {
3480       ierr    = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
3481       mycols += locrowlens[i];
3482       vals   += locrowlens[i];
3483       jj++;
3484     }
3485     /* read in other processors (except the last one) and ship out */
3486     for (i=1; i<size-1; i++) {
3487       nz   = procsnz[i];
3488       vals = buf;
3489       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3490       ierr = MPIULong_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3491     }
3492     /* the last proc */
3493     if (size != 1) {
3494       nz   = procsnz[i] - extra_rows;
3495       vals = buf;
3496       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
3497       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
3498       ierr = MPIULong_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3499     }
3500     ierr = PetscFree(procsnz);CHKERRQ(ierr);
3501   } else {
3502     /* receive numeric values */
3503     ierr = PetscMalloc((nz+1)*sizeof(PetscScalar),&buf);CHKERRQ(ierr);
3504 
3505     /* receive message of values*/
3506     vals   = buf;
3507     mycols = ibuf;
3508     ierr   = MPIULong_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
3509 
3510     /* insert into matrix */
3511     jj = rstart*bs;
3512     for (i=0; i<m; i++) {
3513       ierr    = MatSetValues_MPIBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
3514       mycols += locrowlens[i];
3515       vals   += locrowlens[i];
3516       jj++;
3517     }
3518   }
3519   ierr = PetscFree(locrowlens);CHKERRQ(ierr);
3520   ierr = PetscFree(buf);CHKERRQ(ierr);
3521   ierr = PetscFree(ibuf);CHKERRQ(ierr);
3522   ierr = PetscFree2(rowners,browners);CHKERRQ(ierr);
3523   ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr);
3524   ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr);
3525   ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3526   ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
3527   PetscFunctionReturn(0);
3528 }
3529 
3530 #undef __FUNCT__
3531 #define __FUNCT__ "MatMPIBAIJSetHashTableFactor"
3532 /*@
3533    MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.
3534 
3535    Input Parameters:
3536 .  mat  - the matrix
3537 .  fact - factor
3538 
3539    Not Collective, each process can use a different factor
3540 
3541    Level: advanced
3542 
3543   Notes:
3544    This can also be set by the command line option: -mat_use_hash_table <fact>
3545 
3546 .keywords: matrix, hashtable, factor, HT
3547 
3548 .seealso: MatSetOption()
3549 @*/
3550 PetscErrorCode  MatMPIBAIJSetHashTableFactor(Mat mat,PetscReal fact)
3551 {
3552   PetscErrorCode ierr;
3553 
3554   PetscFunctionBegin;
3555   ierr = PetscTryMethod(mat,"MatSetHashTableFactor_C",(Mat,PetscReal),(mat,fact));CHKERRQ(ierr);
3556   PetscFunctionReturn(0);
3557 }
3558 
3559 #undef __FUNCT__
3560 #define __FUNCT__ "MatSetHashTableFactor_MPIBAIJ"
3561 PetscErrorCode  MatSetHashTableFactor_MPIBAIJ(Mat mat,PetscReal fact)
3562 {
3563   Mat_MPIBAIJ *baij;
3564 
3565   PetscFunctionBegin;
3566   baij          = (Mat_MPIBAIJ*)mat->data;
3567   baij->ht_fact = fact;
3568   PetscFunctionReturn(0);
3569 }
3570 
3571 #undef __FUNCT__
3572 #define __FUNCT__ "MatMPIBAIJGetSeqBAIJ"
3573 PetscErrorCode  MatMPIBAIJGetSeqBAIJ(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
3574 {
3575   Mat_MPIBAIJ *a = (Mat_MPIBAIJ*)A->data;
3576 
3577   PetscFunctionBegin;
3578   *Ad     = a->A;
3579   *Ao     = a->B;
3580   *colmap = a->garray;
3581   PetscFunctionReturn(0);
3582 }
3583 
3584 /*
3585     Special version for direct calls from Fortran (to eliminate two function call overheads
3586 */
3587 #if defined(PETSC_HAVE_FORTRAN_CAPS)
3588 #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
3589 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
3590 #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
3591 #endif
3592 
3593 #undef __FUNCT__
3594 #define __FUNCT__ "matmpibiajsetvaluesblocked"
3595 /*@C
3596   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to MatSetValuesBlocked()
3597 
3598   Collective on Mat
3599 
3600   Input Parameters:
3601 + mat - the matrix
3602 . min - number of input rows
3603 . im - input rows
3604 . nin - number of input columns
3605 . in - input columns
3606 . v - numerical values input
3607 - addvin - INSERT_VALUES or ADD_VALUES
3608 
3609   Notes: This has a complete copy of MatSetValuesBlocked_MPIBAIJ() which is terrible code un-reuse.
3610 
3611   Level: advanced
3612 
3613 .seealso:   MatSetValuesBlocked()
3614 @*/
3615 PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin,PetscInt *min,const PetscInt im[],PetscInt *nin,const PetscInt in[],const MatScalar v[],InsertMode *addvin)
3616 {
3617   /* convert input arguments to C version */
3618   Mat        mat  = *matin;
3619   PetscInt   m    = *min, n = *nin;
3620   InsertMode addv = *addvin;
3621 
3622   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ*)mat->data;
3623   const MatScalar *value;
3624   MatScalar       *barray     = baij->barray;
3625   PetscBool       roworiented = baij->roworiented;
3626   PetscErrorCode  ierr;
3627   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
3628   PetscInt        rend=baij->rendbs,cstart=baij->cstartbs,stepval;
3629   PetscInt        cend=baij->cendbs,bs=mat->rmap->bs,bs2=baij->bs2;
3630 
3631   PetscFunctionBegin;
3632   /* tasks normally handled by MatSetValuesBlocked() */
3633   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
3634 #if defined(PETSC_USE_DEBUG)
3635   else if (mat->insertmode != addv) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Cannot mix add values and insert values");
3636   if (mat->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
3637 #endif
3638   if (mat->assembled) {
3639     mat->was_assembled = PETSC_TRUE;
3640     mat->assembled     = PETSC_FALSE;
3641   }
3642   ierr = PetscLogEventBegin(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr);
3643 
3644 
3645   if (!barray) {
3646     ierr         = PetscMalloc(bs2*sizeof(MatScalar),&barray);CHKERRQ(ierr);
3647     baij->barray = barray;
3648   }
3649 
3650   if (roworiented) stepval = (n-1)*bs;
3651   else stepval = (m-1)*bs;
3652 
3653   for (i=0; i<m; i++) {
3654     if (im[i] < 0) continue;
3655 #if defined(PETSC_USE_DEBUG)
3656     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);
3657 #endif
3658     if (im[i] >= rstart && im[i] < rend) {
3659       row = im[i] - rstart;
3660       for (j=0; j<n; j++) {
3661         /* If NumCol = 1 then a copy is not required */
3662         if ((roworiented) && (n == 1)) {
3663           barray = (MatScalar*)v + i*bs2;
3664         } else if ((!roworiented) && (m == 1)) {
3665           barray = (MatScalar*)v + j*bs2;
3666         } else { /* Here a copy is required */
3667           if (roworiented) {
3668             value = v + i*(stepval+bs)*bs + j*bs;
3669           } else {
3670             value = v + j*(stepval+bs)*bs + i*bs;
3671           }
3672           for (ii=0; ii<bs; ii++,value+=stepval) {
3673             for (jj=0; jj<bs; jj++) {
3674               *barray++ = *value++;
3675             }
3676           }
3677           barray -=bs2;
3678         }
3679 
3680         if (in[j] >= cstart && in[j] < cend) {
3681           col  = in[j] - cstart;
3682           ierr = MatSetValuesBlocked_SeqBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
3683         } else if (in[j] < 0) continue;
3684 #if defined(PETSC_USE_DEBUG)
3685         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);
3686 #endif
3687         else {
3688           if (mat->was_assembled) {
3689             if (!baij->colmap) {
3690               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
3691             }
3692 
3693 #if defined(PETSC_USE_DEBUG)
3694 #if defined(PETSC_USE_CTABLE)
3695             { PetscInt data;
3696               ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
3697               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3698             }
3699 #else
3700             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
3701 #endif
3702 #endif
3703 #if defined(PETSC_USE_CTABLE)
3704             ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
3705             col  = (col - 1)/bs;
3706 #else
3707             col = (baij->colmap[in[j]] - 1)/bs;
3708 #endif
3709             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
3710               ierr = MatDisAssemble_MPIBAIJ(mat);CHKERRQ(ierr);
3711               col  =  in[j];
3712             }
3713           } else col = in[j];
3714           ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
3715         }
3716       }
3717     } else {
3718       if (!baij->donotstash) {
3719         if (roworiented) {
3720           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
3721         } else {
3722           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
3723         }
3724       }
3725     }
3726   }
3727 
3728   /* task normally handled by MatSetValuesBlocked() */
3729   ierr = PetscLogEventEnd(MAT_SetValues,mat,0,0,0);CHKERRQ(ierr);
3730   PetscFunctionReturn(0);
3731 }
3732 
3733 #undef __FUNCT__
3734 #define __FUNCT__ "MatCreateMPIBAIJWithArrays"
3735 /*@
3736      MatCreateMPIBAIJWithArrays - creates a MPI BAIJ matrix using arrays that contain in standard
3737          CSR format the local rows.
3738 
3739    Collective on MPI_Comm
3740 
3741    Input Parameters:
3742 +  comm - MPI communicator
3743 .  bs - the block size, only a block size of 1 is supported
3744 .  m - number of local rows (Cannot be PETSC_DECIDE)
3745 .  n - This value should be the same as the local size used in creating the
3746        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
3747        calculated if N is given) For square matrices n is almost always m.
3748 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
3749 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
3750 .   i - row indices
3751 .   j - column indices
3752 -   a - matrix values
3753 
3754    Output Parameter:
3755 .   mat - the matrix
3756 
3757    Level: intermediate
3758 
3759    Notes:
3760        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
3761      thus you CANNOT change the matrix entries by changing the values of a[] after you have
3762      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
3763 
3764        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
3765 
3766 .keywords: matrix, aij, compressed row, sparse, parallel
3767 
3768 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
3769           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
3770 @*/
3771 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)
3772 {
3773   PetscErrorCode ierr;
3774 
3775   PetscFunctionBegin;
3776   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
3777   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
3778   ierr = MatCreate(comm,mat);CHKERRQ(ierr);
3779   ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr);
3780   ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr);
3781   ierr = MatMPIBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr);
3782   PetscFunctionReturn(0);
3783 }
3784