xref: /petsc/src/mat/impls/sbaij/mpi/mpisbaij.c (revision 772ec989c7718bb40cfbe6762601ac78951cc001)
1 
2 #include <../src/mat/impls/baij/mpi/mpibaij.h>    /*I "petscmat.h" I*/
3 #include <../src/mat/impls/sbaij/mpi/mpisbaij.h>
4 #include <../src/mat/impls/sbaij/seq/sbaij.h>
5 #include <petscblaslapack.h>
6 
7 extern PetscErrorCode MatSetUpMultiply_MPISBAIJ(Mat);
8 extern PetscErrorCode MatSetUpMultiply_MPISBAIJ_2comm(Mat);
9 extern PetscErrorCode MatDisAssemble_MPISBAIJ(Mat);
10 extern PetscErrorCode MatIncreaseOverlap_MPISBAIJ(Mat,PetscInt,IS[],PetscInt);
11 extern PetscErrorCode MatGetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
12 extern PetscErrorCode MatGetValues_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],PetscScalar []);
13 extern PetscErrorCode MatSetValues_SeqSBAIJ(Mat,PetscInt,const PetscInt [],PetscInt,const PetscInt [],const PetscScalar [],InsertMode);
14 extern PetscErrorCode MatSetValuesBlocked_SeqSBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
15 extern PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
16 extern PetscErrorCode MatGetRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
17 extern PetscErrorCode MatRestoreRow_SeqSBAIJ(Mat,PetscInt,PetscInt*,PetscInt**,PetscScalar**);
18 extern PetscErrorCode MatZeroRows_SeqSBAIJ(Mat,IS,PetscScalar*,Vec,Vec);
19 extern PetscErrorCode MatZeroRows_SeqBAIJ(Mat,IS,PetscScalar*,Vec,Vec);
20 extern PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat,Vec,PetscInt[]);
21 extern PetscErrorCode MatSOR_MPISBAIJ(Mat,Vec,PetscReal,MatSORType,PetscReal,PetscInt,PetscInt,Vec);
22 
23 #undef __FUNCT__
24 #define __FUNCT__ "MatStoreValues_MPISBAIJ"
25 PetscErrorCode  MatStoreValues_MPISBAIJ(Mat mat)
26 {
27   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;
28   PetscErrorCode ierr;
29 
30   PetscFunctionBegin;
31   ierr = MatStoreValues(aij->A);CHKERRQ(ierr);
32   ierr = MatStoreValues(aij->B);CHKERRQ(ierr);
33   PetscFunctionReturn(0);
34 }
35 
36 #undef __FUNCT__
37 #define __FUNCT__ "MatRetrieveValues_MPISBAIJ"
38 PetscErrorCode  MatRetrieveValues_MPISBAIJ(Mat mat)
39 {
40   Mat_MPISBAIJ   *aij = (Mat_MPISBAIJ*)mat->data;
41   PetscErrorCode ierr;
42 
43   PetscFunctionBegin;
44   ierr = MatRetrieveValues(aij->A);CHKERRQ(ierr);
45   ierr = MatRetrieveValues(aij->B);CHKERRQ(ierr);
46   PetscFunctionReturn(0);
47 }
48 
49 #define  MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv) \
50   { \
51  \
52     brow = row/bs;  \
53     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow]; \
54     rmax = aimax[brow]; nrow = ailen[brow]; \
55     bcol = col/bs; \
56     ridx = row % bs; cidx = col % bs; \
57     low  = 0; high = nrow; \
58     while (high-low > 3) { \
59       t = (low+high)/2; \
60       if (rp[t] > bcol) high = t; \
61       else              low  = t; \
62     } \
63     for (_i=low; _i<high; _i++) { \
64       if (rp[_i] > bcol) break; \
65       if (rp[_i] == bcol) { \
66         bap = ap + bs2*_i + bs*cidx + ridx; \
67         if (addv == ADD_VALUES) *bap += value;  \
68         else                    *bap  = value;  \
69         goto a_noinsert; \
70       } \
71     } \
72     if (a->nonew == 1) goto a_noinsert; \
73     if (a->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
74     MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,aimax,a->nonew,MatScalar); \
75     N = nrow++ - 1;  \
76     /* shift up all the later entries in this row */ \
77     for (ii=N; ii>=_i; ii--) { \
78       rp[ii+1] = rp[ii]; \
79       ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
80     } \
81     if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr); }  \
82     rp[_i]                      = bcol;  \
83     ap[bs2*_i + bs*cidx + ridx] = value;  \
84     A->nonzerostate++;\
85 a_noinsert:; \
86     ailen[brow] = nrow; \
87   }
88 
89 #define  MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv) \
90   { \
91     brow = row/bs;  \
92     rp   = bj + bi[brow]; ap = ba + bs2*bi[brow]; \
93     rmax = bimax[brow]; nrow = bilen[brow]; \
94     bcol = col/bs; \
95     ridx = row % bs; cidx = col % bs; \
96     low  = 0; high = nrow; \
97     while (high-low > 3) { \
98       t = (low+high)/2; \
99       if (rp[t] > bcol) high = t; \
100       else              low  = t; \
101     } \
102     for (_i=low; _i<high; _i++) { \
103       if (rp[_i] > bcol) break; \
104       if (rp[_i] == bcol) { \
105         bap = ap + bs2*_i + bs*cidx + ridx; \
106         if (addv == ADD_VALUES) *bap += value;  \
107         else                    *bap  = value;  \
108         goto b_noinsert; \
109       } \
110     } \
111     if (b->nonew == 1) goto b_noinsert; \
112     if (b->nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) into matrix", row, col); \
113     MatSeqXAIJReallocateAIJ(B,b->mbs,bs2,nrow,brow,bcol,rmax,ba,bi,bj,rp,ap,bimax,b->nonew,MatScalar); \
114     N = nrow++ - 1;  \
115     /* shift up all the later entries in this row */ \
116     for (ii=N; ii>=_i; ii--) { \
117       rp[ii+1] = rp[ii]; \
118       ierr     = PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));CHKERRQ(ierr); \
119     } \
120     if (N>=_i) { ierr = PetscMemzero(ap+bs2*_i,bs2*sizeof(MatScalar));CHKERRQ(ierr);}  \
121     rp[_i]                      = bcol;  \
122     ap[bs2*_i + bs*cidx + ridx] = value;  \
123     B->nonzerostate++;\
124 b_noinsert:; \
125     bilen[brow] = nrow; \
126   }
127 
128 /* Only add/insert a(i,j) with i<=j (blocks).
129    Any a(i,j) with i>j input by user is ingored.
130 */
131 #undef __FUNCT__
132 #define __FUNCT__ "MatSetValues_MPISBAIJ"
133 PetscErrorCode MatSetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
134 {
135   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
136   MatScalar      value;
137   PetscBool      roworiented = baij->roworiented;
138   PetscErrorCode ierr;
139   PetscInt       i,j,row,col;
140   PetscInt       rstart_orig=mat->rmap->rstart;
141   PetscInt       rend_orig  =mat->rmap->rend,cstart_orig=mat->cmap->rstart;
142   PetscInt       cend_orig  =mat->cmap->rend,bs=mat->rmap->bs;
143 
144   /* Some Variables required in the macro */
145   Mat          A     = baij->A;
146   Mat_SeqSBAIJ *a    = (Mat_SeqSBAIJ*)(A)->data;
147   PetscInt     *aimax=a->imax,*ai=a->i,*ailen=a->ilen,*aj=a->j;
148   MatScalar    *aa   =a->a;
149 
150   Mat         B     = baij->B;
151   Mat_SeqBAIJ *b    = (Mat_SeqBAIJ*)(B)->data;
152   PetscInt    *bimax=b->imax,*bi=b->i,*bilen=b->ilen,*bj=b->j;
153   MatScalar   *ba   =b->a;
154 
155   PetscInt  *rp,ii,nrow,_i,rmax,N,brow,bcol;
156   PetscInt  low,high,t,ridx,cidx,bs2=a->bs2;
157   MatScalar *ap,*bap;
158 
159   /* for stash */
160   PetscInt  n_loc, *in_loc = NULL;
161   MatScalar *v_loc = NULL;
162 
163   PetscFunctionBegin;
164   if (!baij->donotstash) {
165     if (n > baij->n_loc) {
166       ierr = PetscFree(baij->in_loc);CHKERRQ(ierr);
167       ierr = PetscFree(baij->v_loc);CHKERRQ(ierr);
168       ierr = PetscMalloc1(n,&baij->in_loc);CHKERRQ(ierr);
169       ierr = PetscMalloc1(n,&baij->v_loc);CHKERRQ(ierr);
170 
171       baij->n_loc = n;
172     }
173     in_loc = baij->in_loc;
174     v_loc  = baij->v_loc;
175   }
176 
177   for (i=0; i<m; i++) {
178     if (im[i] < 0) continue;
179 #if defined(PETSC_USE_DEBUG)
180     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);
181 #endif
182     if (im[i] >= rstart_orig && im[i] < rend_orig) { /* this processor entry */
183       row = im[i] - rstart_orig;              /* local row index */
184       for (j=0; j<n; j++) {
185         if (im[i]/bs > in[j]/bs) {
186           if (a->ignore_ltriangular) {
187             continue;    /* ignore lower triangular blocks */
188           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
189         }
190         if (in[j] >= cstart_orig && in[j] < cend_orig) {  /* diag entry (A) */
191           col  = in[j] - cstart_orig;         /* local col index */
192           brow = row/bs; bcol = col/bs;
193           if (brow > bcol) continue;  /* ignore lower triangular blocks of A */
194           if (roworiented) value = v[i*n+j];
195           else             value = v[i+j*m];
196           MatSetValues_SeqSBAIJ_A_Private(row,col,value,addv);
197           /* ierr = MatSetValues_SeqBAIJ(baij->A,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
198         } else if (in[j] < 0) continue;
199 #if defined(PETSC_USE_DEBUG)
200         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);
201 #endif
202         else {  /* off-diag entry (B) */
203           if (mat->was_assembled) {
204             if (!baij->colmap) {
205               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
206             }
207 #if defined(PETSC_USE_CTABLE)
208             ierr = PetscTableFind(baij->colmap,in[j]/bs + 1,&col);CHKERRQ(ierr);
209             col  = col - 1;
210 #else
211             col = baij->colmap[in[j]/bs] - 1;
212 #endif
213             if (col < 0 && !((Mat_SeqSBAIJ*)(baij->A->data))->nonew) {
214               ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr);
215               col  =  in[j];
216               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
217               B    = baij->B;
218               b    = (Mat_SeqBAIJ*)(B)->data;
219               bimax= b->imax;bi=b->i;bilen=b->ilen;bj=b->j;
220               ba   = b->a;
221             } else col += in[j]%bs;
222           } else col = in[j];
223           if (roworiented) value = v[i*n+j];
224           else             value = v[i+j*m];
225           MatSetValues_SeqSBAIJ_B_Private(row,col,value,addv);
226           /* ierr = MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv);CHKERRQ(ierr); */
227         }
228       }
229     } else {  /* off processor entry */
230       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]);
231       if (!baij->donotstash) {
232         mat->assembled = PETSC_FALSE;
233         n_loc          = 0;
234         for (j=0; j<n; j++) {
235           if (im[i]/bs > in[j]/bs) continue; /* ignore lower triangular blocks */
236           in_loc[n_loc] = in[j];
237           if (roworiented) {
238             v_loc[n_loc] = v[i*n+j];
239           } else {
240             v_loc[n_loc] = v[j*m+i];
241           }
242           n_loc++;
243         }
244         ierr = MatStashValuesRow_Private(&mat->stash,im[i],n_loc,in_loc,v_loc,PETSC_FALSE);CHKERRQ(ierr);
245       }
246     }
247   }
248   PetscFunctionReturn(0);
249 }
250 
251 #undef __FUNCT__
252 #define __FUNCT__ "MatSetValuesBlocked_MPISBAIJ"
253 PetscErrorCode MatSetValuesBlocked_MPISBAIJ(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const MatScalar v[],InsertMode addv)
254 {
255   Mat_MPISBAIJ    *baij = (Mat_MPISBAIJ*)mat->data;
256   const MatScalar *value;
257   MatScalar       *barray     =baij->barray;
258   PetscBool       roworiented = baij->roworiented,ignore_ltriangular = ((Mat_SeqSBAIJ*)baij->A->data)->ignore_ltriangular;
259   PetscErrorCode  ierr;
260   PetscInt        i,j,ii,jj,row,col,rstart=baij->rstartbs;
261   PetscInt        rend=baij->rendbs,cstart=baij->rstartbs,stepval;
262   PetscInt        cend=baij->rendbs,bs=mat->rmap->bs,bs2=baij->bs2;
263 
264   PetscFunctionBegin;
265   if (!barray) {
266     ierr         = PetscMalloc1(bs2,&barray);CHKERRQ(ierr);
267     baij->barray = barray;
268   }
269 
270   if (roworiented) {
271     stepval = (n-1)*bs;
272   } else {
273     stepval = (m-1)*bs;
274   }
275   for (i=0; i<m; i++) {
276     if (im[i] < 0) continue;
277 #if defined(PETSC_USE_DEBUG)
278     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);
279 #endif
280     if (im[i] >= rstart && im[i] < rend) {
281       row = im[i] - rstart;
282       for (j=0; j<n; j++) {
283         if (im[i] > in[j]) {
284           if (ignore_ltriangular) continue; /* ignore lower triangular blocks */
285           else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_USER,"Lower triangular value cannot be set for sbaij format. Ignoring these values, run with -mat_ignore_lower_triangular or call MatSetOption(mat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE)");
286         }
287         /* If NumCol = 1 then a copy is not required */
288         if ((roworiented) && (n == 1)) {
289           barray = (MatScalar*) v + i*bs2;
290         } else if ((!roworiented) && (m == 1)) {
291           barray = (MatScalar*) v + j*bs2;
292         } else { /* Here a copy is required */
293           if (roworiented) {
294             value = v + i*(stepval+bs)*bs + j*bs;
295           } else {
296             value = v + j*(stepval+bs)*bs + i*bs;
297           }
298           for (ii=0; ii<bs; ii++,value+=stepval) {
299             for (jj=0; jj<bs; jj++) {
300               *barray++ = *value++;
301             }
302           }
303           barray -=bs2;
304         }
305 
306         if (in[j] >= cstart && in[j] < cend) {
307           col  = in[j] - cstart;
308           ierr = MatSetValuesBlocked_SeqSBAIJ(baij->A,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
309         } else if (in[j] < 0) continue;
310 #if defined(PETSC_USE_DEBUG)
311         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);
312 #endif
313         else {
314           if (mat->was_assembled) {
315             if (!baij->colmap) {
316               ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
317             }
318 
319 #if defined(PETSC_USE_DEBUG)
320 #if defined(PETSC_USE_CTABLE)
321             { PetscInt data;
322               ierr = PetscTableFind(baij->colmap,in[j]+1,&data);CHKERRQ(ierr);
323               if ((data - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
324             }
325 #else
326             if ((baij->colmap[in[j]] - 1) % bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Incorrect colmap");
327 #endif
328 #endif
329 #if defined(PETSC_USE_CTABLE)
330             ierr = PetscTableFind(baij->colmap,in[j]+1,&col);CHKERRQ(ierr);
331             col  = (col - 1)/bs;
332 #else
333             col = (baij->colmap[in[j]] - 1)/bs;
334 #endif
335             if (col < 0 && !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
336               ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr);
337               col  = in[j];
338             }
339           } else col = in[j];
340           ierr = MatSetValuesBlocked_SeqBAIJ(baij->B,1,&row,1,&col,barray,addv);CHKERRQ(ierr);
341         }
342       }
343     } else {
344       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]);
345       if (!baij->donotstash) {
346         if (roworiented) {
347           ierr = MatStashValuesRowBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
348         } else {
349           ierr = MatStashValuesColBlocked_Private(&mat->bstash,im[i],n,in,v,m,n,i);CHKERRQ(ierr);
350         }
351       }
352     }
353   }
354   PetscFunctionReturn(0);
355 }
356 
357 #undef __FUNCT__
358 #define __FUNCT__ "MatGetValues_MPISBAIJ"
359 PetscErrorCode MatGetValues_MPISBAIJ(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
360 {
361   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
362   PetscErrorCode ierr;
363   PetscInt       bs       = mat->rmap->bs,i,j,bsrstart = mat->rmap->rstart,bsrend = mat->rmap->rend;
364   PetscInt       bscstart = mat->cmap->rstart,bscend = mat->cmap->rend,row,col,data;
365 
366   PetscFunctionBegin;
367   for (i=0; i<m; i++) {
368     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]); */
369     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);
370     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
371       row = idxm[i] - bsrstart;
372       for (j=0; j<n; j++) {
373         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column %D",idxn[j]); */
374         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);
375         if (idxn[j] >= bscstart && idxn[j] < bscend) {
376           col  = idxn[j] - bscstart;
377           ierr = MatGetValues_SeqSBAIJ(baij->A,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
378         } else {
379           if (!baij->colmap) {
380             ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
381           }
382 #if defined(PETSC_USE_CTABLE)
383           ierr = PetscTableFind(baij->colmap,idxn[j]/bs+1,&data);CHKERRQ(ierr);
384           data--;
385 #else
386           data = baij->colmap[idxn[j]/bs]-1;
387 #endif
388           if ((data < 0) || (baij->garray[data/bs] != idxn[j]/bs)) *(v+i*n+j) = 0.0;
389           else {
390             col  = data + idxn[j]%bs;
391             ierr = MatGetValues_SeqBAIJ(baij->B,1,&row,1,&col,v+i*n+j);CHKERRQ(ierr);
392           }
393         }
394       }
395     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
396   }
397   PetscFunctionReturn(0);
398 }
399 
400 #undef __FUNCT__
401 #define __FUNCT__ "MatNorm_MPISBAIJ"
402 PetscErrorCode MatNorm_MPISBAIJ(Mat mat,NormType type,PetscReal *norm)
403 {
404   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
405   PetscErrorCode ierr;
406   PetscReal      sum[2],*lnorm2;
407 
408   PetscFunctionBegin;
409   if (baij->size == 1) {
410     ierr =  MatNorm(baij->A,type,norm);CHKERRQ(ierr);
411   } else {
412     if (type == NORM_FROBENIUS) {
413       ierr    = PetscMalloc1(2,&lnorm2);CHKERRQ(ierr);
414       ierr    =  MatNorm(baij->A,type,lnorm2);CHKERRQ(ierr);
415       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2++;            /* squar power of norm(A) */
416       ierr    =  MatNorm(baij->B,type,lnorm2);CHKERRQ(ierr);
417       *lnorm2 = (*lnorm2)*(*lnorm2); lnorm2--;             /* squar power of norm(B) */
418       ierr    = MPI_Allreduce(lnorm2,sum,2,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
419       *norm   = PetscSqrtReal(sum[0] + 2*sum[1]);
420       ierr    = PetscFree(lnorm2);CHKERRQ(ierr);
421     } else if (type == NORM_INFINITY || type == NORM_1) { /* max row/column sum */
422       Mat_SeqSBAIJ *amat=(Mat_SeqSBAIJ*)baij->A->data;
423       Mat_SeqBAIJ  *bmat=(Mat_SeqBAIJ*)baij->B->data;
424       PetscReal    *rsum,*rsum2,vabs;
425       PetscInt     *jj,*garray=baij->garray,rstart=baij->rstartbs,nz;
426       PetscInt     brow,bcol,col,bs=baij->A->rmap->bs,row,grow,gcol,mbs=amat->mbs;
427       MatScalar    *v;
428 
429       ierr = PetscMalloc2(mat->cmap->N,&rsum,mat->cmap->N,&rsum2);CHKERRQ(ierr);
430       ierr = PetscMemzero(rsum,mat->cmap->N*sizeof(PetscReal));CHKERRQ(ierr);
431       /* Amat */
432       v = amat->a; jj = amat->j;
433       for (brow=0; brow<mbs; brow++) {
434         grow = bs*(rstart + brow);
435         nz   = amat->i[brow+1] - amat->i[brow];
436         for (bcol=0; bcol<nz; bcol++) {
437           gcol = bs*(rstart + *jj); jj++;
438           for (col=0; col<bs; col++) {
439             for (row=0; row<bs; row++) {
440               vabs            = PetscAbsScalar(*v); v++;
441               rsum[gcol+col] += vabs;
442               /* non-diagonal block */
443               if (bcol > 0 && vabs > 0.0) rsum[grow+row] += vabs;
444             }
445           }
446         }
447       }
448       /* Bmat */
449       v = bmat->a; jj = bmat->j;
450       for (brow=0; brow<mbs; brow++) {
451         grow = bs*(rstart + brow);
452         nz = bmat->i[brow+1] - bmat->i[brow];
453         for (bcol=0; bcol<nz; bcol++) {
454           gcol = bs*garray[*jj]; jj++;
455           for (col=0; col<bs; col++) {
456             for (row=0; row<bs; row++) {
457               vabs            = PetscAbsScalar(*v); v++;
458               rsum[gcol+col] += vabs;
459               rsum[grow+row] += vabs;
460             }
461           }
462         }
463       }
464       ierr  = MPI_Allreduce(rsum,rsum2,mat->cmap->N,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
465       *norm = 0.0;
466       for (col=0; col<mat->cmap->N; col++) {
467         if (rsum2[col] > *norm) *norm = rsum2[col];
468       }
469       ierr = PetscFree2(rsum,rsum2);CHKERRQ(ierr);
470     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support for this norm yet");
471   }
472   PetscFunctionReturn(0);
473 }
474 
475 #undef __FUNCT__
476 #define __FUNCT__ "MatAssemblyBegin_MPISBAIJ"
477 PetscErrorCode MatAssemblyBegin_MPISBAIJ(Mat mat,MatAssemblyType mode)
478 {
479   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
480   PetscErrorCode ierr;
481   PetscInt       nstash,reallocs;
482   InsertMode     addv;
483 
484   PetscFunctionBegin;
485   if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(0);
486 
487   /* make sure all processors are either in INSERTMODE or ADDMODE */
488   ierr = MPI_Allreduce((PetscEnum*)&mat->insertmode,(PetscEnum*)&addv,1,MPIU_ENUM,MPI_BOR,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
489   if (addv == (ADD_VALUES|INSERT_VALUES)) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_WRONGSTATE,"Some processors inserted others added");
490   mat->insertmode = addv; /* in case this processor had no cache */
491 
492   ierr = MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);CHKERRQ(ierr);
493   ierr = MatStashScatterBegin_Private(mat,&mat->bstash,baij->rangebs);CHKERRQ(ierr);
494   ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr);
495   ierr = PetscInfo2(mat,"Stash has %D entries,uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr);
496   ierr = MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);CHKERRQ(ierr);
497   ierr = PetscInfo2(mat,"Block-Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);CHKERRQ(ierr);
498   PetscFunctionReturn(0);
499 }
500 
501 #undef __FUNCT__
502 #define __FUNCT__ "MatAssemblyEnd_MPISBAIJ"
503 PetscErrorCode MatAssemblyEnd_MPISBAIJ(Mat mat,MatAssemblyType mode)
504 {
505   Mat_MPISBAIJ   *baij=(Mat_MPISBAIJ*)mat->data;
506   Mat_SeqSBAIJ   *a   =(Mat_SeqSBAIJ*)baij->A->data;
507   PetscErrorCode ierr;
508   PetscInt       i,j,rstart,ncols,flg,bs2=baij->bs2;
509   PetscInt       *row,*col;
510   PetscBool      other_disassembled;
511   PetscMPIInt    n;
512   PetscBool      r1,r2,r3;
513   MatScalar      *val;
514   InsertMode     addv = mat->insertmode;
515 
516   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
517   PetscFunctionBegin;
518   if (!baij->donotstash &&  !mat->nooffprocentries) {
519     while (1) {
520       ierr = MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
521       if (!flg) break;
522 
523       for (i=0; i<n;) {
524         /* Now identify the consecutive vals belonging to the same row */
525         for (j=i,rstart=row[j]; j<n; j++) {
526           if (row[j] != rstart) break;
527         }
528         if (j < n) ncols = j-i;
529         else       ncols = n-i;
530         /* Now assemble all these values with a single function call */
531         ierr = MatSetValues_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i,addv);CHKERRQ(ierr);
532         i    = j;
533       }
534     }
535     ierr = MatStashScatterEnd_Private(&mat->stash);CHKERRQ(ierr);
536     /* Now process the block-stash. Since the values are stashed column-oriented,
537        set the roworiented flag to column oriented, and after MatSetValues()
538        restore the original flags */
539     r1 = baij->roworiented;
540     r2 = a->roworiented;
541     r3 = ((Mat_SeqBAIJ*)baij->B->data)->roworiented;
542 
543     baij->roworiented = PETSC_FALSE;
544     a->roworiented    = PETSC_FALSE;
545 
546     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = PETSC_FALSE; /* b->roworinted */
547     while (1) {
548       ierr = MatStashScatterGetMesg_Private(&mat->bstash,&n,&row,&col,&val,&flg);CHKERRQ(ierr);
549       if (!flg) break;
550 
551       for (i=0; i<n;) {
552         /* Now identify the consecutive vals belonging to the same row */
553         for (j=i,rstart=row[j]; j<n; j++) {
554           if (row[j] != rstart) break;
555         }
556         if (j < n) ncols = j-i;
557         else       ncols = n-i;
558         ierr = MatSetValuesBlocked_MPISBAIJ(mat,1,row+i,ncols,col+i,val+i*bs2,addv);CHKERRQ(ierr);
559         i    = j;
560       }
561     }
562     ierr = MatStashScatterEnd_Private(&mat->bstash);CHKERRQ(ierr);
563 
564     baij->roworiented = r1;
565     a->roworiented    = r2;
566 
567     ((Mat_SeqBAIJ*)baij->B->data)->roworiented = r3; /* b->roworinted */
568   }
569 
570   ierr = MatAssemblyBegin(baij->A,mode);CHKERRQ(ierr);
571   ierr = MatAssemblyEnd(baij->A,mode);CHKERRQ(ierr);
572 
573   /* determine if any processor has disassembled, if so we must
574      also disassemble ourselfs, in order that we may reassemble. */
575   /*
576      if nonzero structure of submatrix B cannot change then we know that
577      no processor disassembled thus we can skip this stuff
578   */
579   if (!((Mat_SeqBAIJ*)baij->B->data)->nonew) {
580     ierr = MPI_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
581     if (mat->was_assembled && !other_disassembled) {
582       ierr = MatDisAssemble_MPISBAIJ(mat);CHKERRQ(ierr);
583     }
584   }
585 
586   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
587     ierr = MatSetUpMultiply_MPISBAIJ(mat);CHKERRQ(ierr); /* setup Mvctx and sMvctx */
588   }
589   ierr = MatAssemblyBegin(baij->B,mode);CHKERRQ(ierr);
590   ierr = MatAssemblyEnd(baij->B,mode);CHKERRQ(ierr);
591 
592   ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr);
593 
594   baij->rowvalues = 0;
595 
596   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
597   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ*)(baij->A->data))->nonew) {
598     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
599     ierr = MPI_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
600   }
601   PetscFunctionReturn(0);
602 }
603 
604 extern PetscErrorCode MatView_SeqSBAIJ_ASCII(Mat,PetscViewer);
605 extern PetscErrorCode MatSetValues_MPIBAIJ(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[],const PetscScalar[],InsertMode);
606 #include <petscdraw.h>
607 #undef __FUNCT__
608 #define __FUNCT__ "MatView_MPISBAIJ_ASCIIorDraworSocket"
609 static PetscErrorCode MatView_MPISBAIJ_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
610 {
611   Mat_MPISBAIJ      *baij = (Mat_MPISBAIJ*)mat->data;
612   PetscErrorCode    ierr;
613   PetscInt          bs   = mat->rmap->bs;
614   PetscMPIInt       rank = baij->rank;
615   PetscBool         iascii,isdraw;
616   PetscViewer       sviewer;
617   PetscViewerFormat format;
618 
619   PetscFunctionBegin;
620   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
621   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
622   if (iascii) {
623     ierr = PetscViewerGetFormat(viewer,&format);CHKERRQ(ierr);
624     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
625       MatInfo info;
626       ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);CHKERRQ(ierr);
627       ierr = MatGetInfo(mat,MAT_LOCAL,&info);CHKERRQ(ierr);
628       ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_TRUE);CHKERRQ(ierr);
629       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D bs %D mem %D\n",rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,mat->rmap->bs,(PetscInt)info.memory);CHKERRQ(ierr);
630       ierr = MatGetInfo(baij->A,MAT_LOCAL,&info);CHKERRQ(ierr);
631       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr);
632       ierr = MatGetInfo(baij->B,MAT_LOCAL,&info);CHKERRQ(ierr);
633       ierr = PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);CHKERRQ(ierr);
634       ierr = PetscViewerFlush(viewer);CHKERRQ(ierr);
635       ierr = PetscViewerASCIISynchronizedAllow(viewer,PETSC_FALSE);CHKERRQ(ierr);
636       ierr = PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");CHKERRQ(ierr);
637       ierr = VecScatterView(baij->Mvctx,viewer);CHKERRQ(ierr);
638       PetscFunctionReturn(0);
639     } else if (format == PETSC_VIEWER_ASCII_INFO) {
640       ierr = PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);CHKERRQ(ierr);
641       PetscFunctionReturn(0);
642     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
643       PetscFunctionReturn(0);
644     }
645   }
646 
647   if (isdraw) {
648     PetscDraw draw;
649     PetscBool isnull;
650     ierr = PetscViewerDrawGetDraw(viewer,0,&draw);CHKERRQ(ierr);
651     ierr = PetscDrawIsNull(draw,&isnull);CHKERRQ(ierr); if (isnull) PetscFunctionReturn(0);
652   }
653 
654   {
655     /* assemble the entire matrix onto first processor. */
656     Mat          A;
657     Mat_SeqSBAIJ *Aloc;
658     Mat_SeqBAIJ  *Bloc;
659     PetscInt     M = mat->rmap->N,N = mat->cmap->N,*ai,*aj,col,i,j,k,*rvals,mbs = baij->mbs;
660     MatScalar    *a;
661 
662     /* Should this be the same type as mat? */
663     ierr = MatCreate(PetscObjectComm((PetscObject)mat),&A);CHKERRQ(ierr);
664     if (!rank) {
665       ierr = MatSetSizes(A,M,N,M,N);CHKERRQ(ierr);
666     } else {
667       ierr = MatSetSizes(A,0,0,M,N);CHKERRQ(ierr);
668     }
669     ierr = MatSetType(A,MATMPISBAIJ);CHKERRQ(ierr);
670     ierr = MatMPISBAIJSetPreallocation(A,mat->rmap->bs,0,NULL,0,NULL);CHKERRQ(ierr);
671     ierr = MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);CHKERRQ(ierr);
672     ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)A);CHKERRQ(ierr);
673 
674     /* copy over the A part */
675     Aloc = (Mat_SeqSBAIJ*)baij->A->data;
676     ai   = Aloc->i; aj = Aloc->j; a = Aloc->a;
677     ierr = PetscMalloc1(bs,&rvals);CHKERRQ(ierr);
678 
679     for (i=0; i<mbs; i++) {
680       rvals[0] = bs*(baij->rstartbs + i);
681       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
682       for (j=ai[i]; j<ai[i+1]; j++) {
683         col = (baij->cstartbs+aj[j])*bs;
684         for (k=0; k<bs; k++) {
685           ierr = MatSetValues_MPISBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
686           col++;
687           a += bs;
688         }
689       }
690     }
691     /* copy over the B part */
692     Bloc = (Mat_SeqBAIJ*)baij->B->data;
693     ai   = Bloc->i; aj = Bloc->j; a = Bloc->a;
694     for (i=0; i<mbs; i++) {
695 
696       rvals[0] = bs*(baij->rstartbs + i);
697       for (j=1; j<bs; j++) rvals[j] = rvals[j-1] + 1;
698       for (j=ai[i]; j<ai[i+1]; j++) {
699         col = baij->garray[aj[j]]*bs;
700         for (k=0; k<bs; k++) {
701           ierr = MatSetValues_MPIBAIJ(A,bs,rvals,1,&col,a,INSERT_VALUES);CHKERRQ(ierr);
702           col++;
703           a += bs;
704         }
705       }
706     }
707     ierr = PetscFree(rvals);CHKERRQ(ierr);
708     ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
709     ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
710     /*
711        Everyone has to call to draw the matrix since the graphics waits are
712        synchronized across all processors that share the PetscDraw object
713     */
714     ierr = PetscViewerGetSingleton(viewer,&sviewer);CHKERRQ(ierr);
715     if (!rank) {
716         ierr = MatView_SeqSBAIJ_ASCII(((Mat_MPISBAIJ*)(A->data))->A,sviewer);CHKERRQ(ierr);
717     }
718     ierr = PetscViewerRestoreSingleton(viewer,&sviewer);CHKERRQ(ierr);
719     ierr = MatDestroy(&A);CHKERRQ(ierr);
720   }
721   PetscFunctionReturn(0);
722 }
723 
724 #undef __FUNCT__
725 #define __FUNCT__ "MatView_MPISBAIJ"
726 PetscErrorCode MatView_MPISBAIJ(Mat mat,PetscViewer viewer)
727 {
728   PetscErrorCode ierr;
729   PetscBool      iascii,isdraw,issocket,isbinary;
730 
731   PetscFunctionBegin;
732   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);CHKERRQ(ierr);
733   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);CHKERRQ(ierr);
734   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);CHKERRQ(ierr);
735   ierr = PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);CHKERRQ(ierr);
736   if (iascii || isdraw || issocket || isbinary) {
737     ierr = MatView_MPISBAIJ_ASCIIorDraworSocket(mat,viewer);CHKERRQ(ierr);
738   }
739   PetscFunctionReturn(0);
740 }
741 
742 #undef __FUNCT__
743 #define __FUNCT__ "MatDestroy_MPISBAIJ"
744 PetscErrorCode MatDestroy_MPISBAIJ(Mat mat)
745 {
746   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
747   PetscErrorCode ierr;
748 
749   PetscFunctionBegin;
750 #if defined(PETSC_USE_LOG)
751   PetscLogObjectState((PetscObject)mat,"Rows=%D,Cols=%D",mat->rmap->N,mat->cmap->N);
752 #endif
753   ierr = MatStashDestroy_Private(&mat->stash);CHKERRQ(ierr);
754   ierr = MatStashDestroy_Private(&mat->bstash);CHKERRQ(ierr);
755   ierr = MatDestroy(&baij->A);CHKERRQ(ierr);
756   ierr = MatDestroy(&baij->B);CHKERRQ(ierr);
757 #if defined(PETSC_USE_CTABLE)
758   ierr = PetscTableDestroy(&baij->colmap);CHKERRQ(ierr);
759 #else
760   ierr = PetscFree(baij->colmap);CHKERRQ(ierr);
761 #endif
762   ierr = PetscFree(baij->garray);CHKERRQ(ierr);
763   ierr = VecDestroy(&baij->lvec);CHKERRQ(ierr);
764   ierr = VecScatterDestroy(&baij->Mvctx);CHKERRQ(ierr);
765   ierr = VecDestroy(&baij->slvec0);CHKERRQ(ierr);
766   ierr = VecDestroy(&baij->slvec0b);CHKERRQ(ierr);
767   ierr = VecDestroy(&baij->slvec1);CHKERRQ(ierr);
768   ierr = VecDestroy(&baij->slvec1a);CHKERRQ(ierr);
769   ierr = VecDestroy(&baij->slvec1b);CHKERRQ(ierr);
770   ierr = VecScatterDestroy(&baij->sMvctx);CHKERRQ(ierr);
771   ierr = PetscFree2(baij->rowvalues,baij->rowindices);CHKERRQ(ierr);
772   ierr = PetscFree(baij->barray);CHKERRQ(ierr);
773   ierr = PetscFree(baij->hd);CHKERRQ(ierr);
774   ierr = VecDestroy(&baij->diag);CHKERRQ(ierr);
775   ierr = VecDestroy(&baij->bb1);CHKERRQ(ierr);
776   ierr = VecDestroy(&baij->xx1);CHKERRQ(ierr);
777 #if defined(PETSC_USE_REAL_MAT_SINGLE)
778   ierr = PetscFree(baij->setvaluescopy);CHKERRQ(ierr);
779 #endif
780   ierr = PetscFree(baij->in_loc);CHKERRQ(ierr);
781   ierr = PetscFree(baij->v_loc);CHKERRQ(ierr);
782   ierr = PetscFree(baij->rangebs);CHKERRQ(ierr);
783   ierr = PetscFree(mat->data);CHKERRQ(ierr);
784 
785   ierr = PetscObjectChangeTypeName((PetscObject)mat,0);CHKERRQ(ierr);
786   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);CHKERRQ(ierr);
787   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);CHKERRQ(ierr);
788   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatGetDiagonalBlock_C",NULL);CHKERRQ(ierr);
789   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatMPISBAIJSetPreallocation_C",NULL);CHKERRQ(ierr);
790   ierr = PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisbaij_mpisbstrm_C",NULL);CHKERRQ(ierr);
791   PetscFunctionReturn(0);
792 }
793 
794 #undef __FUNCT__
795 #define __FUNCT__ "MatMult_MPISBAIJ_Hermitian"
796 PetscErrorCode MatMult_MPISBAIJ_Hermitian(Mat A,Vec xx,Vec yy)
797 {
798   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
799   PetscErrorCode ierr;
800   PetscInt       nt,mbs=a->mbs,bs=A->rmap->bs;
801   PetscScalar    *x,*from;
802 
803   PetscFunctionBegin;
804   ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr);
805   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
806 
807   /* diagonal part */
808   ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr);
809   ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr);
810 
811   /* subdiagonal part */
812   ierr = (*a->B->ops->multhermitiantranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr);
813 
814   /* copy x into the vec slvec0 */
815   ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr);
816   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
817 
818   ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr);
819   ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr);
820   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
821 
822   ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
823   ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
824   /* supperdiagonal part */
825   ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr);
826   PetscFunctionReturn(0);
827 }
828 
829 #undef __FUNCT__
830 #define __FUNCT__ "MatMult_MPISBAIJ"
831 PetscErrorCode MatMult_MPISBAIJ(Mat A,Vec xx,Vec yy)
832 {
833   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
834   PetscErrorCode ierr;
835   PetscInt       nt,mbs=a->mbs,bs=A->rmap->bs;
836   PetscScalar    *x,*from;
837 
838   PetscFunctionBegin;
839   ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr);
840   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
841 
842   /* diagonal part */
843   ierr = (*a->A->ops->mult)(a->A,xx,a->slvec1a);CHKERRQ(ierr);
844   ierr = VecSet(a->slvec1b,0.0);CHKERRQ(ierr);
845 
846   /* subdiagonal part */
847   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr);
848 
849   /* copy x into the vec slvec0 */
850   ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr);
851   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
852 
853   ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr);
854   ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr);
855   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
856 
857   ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
858   ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
859   /* supperdiagonal part */
860   ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,yy);CHKERRQ(ierr);
861   PetscFunctionReturn(0);
862 }
863 
864 #undef __FUNCT__
865 #define __FUNCT__ "MatMult_MPISBAIJ_2comm"
866 PetscErrorCode MatMult_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy)
867 {
868   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
869   PetscErrorCode ierr;
870   PetscInt       nt;
871 
872   PetscFunctionBegin;
873   ierr = VecGetLocalSize(xx,&nt);CHKERRQ(ierr);
874   if (nt != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A and xx");
875 
876   ierr = VecGetLocalSize(yy,&nt);CHKERRQ(ierr);
877   if (nt != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible parition of A and yy");
878 
879   ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
880   /* do diagonal part */
881   ierr = (*a->A->ops->mult)(a->A,xx,yy);CHKERRQ(ierr);
882   /* do supperdiagonal part */
883   ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
884   ierr = (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);CHKERRQ(ierr);
885   /* do subdiagonal part */
886   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr);
887   ierr = VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
888   ierr = VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
889   PetscFunctionReturn(0);
890 }
891 
892 #undef __FUNCT__
893 #define __FUNCT__ "MatMultAdd_MPISBAIJ"
894 PetscErrorCode MatMultAdd_MPISBAIJ(Mat A,Vec xx,Vec yy,Vec zz)
895 {
896   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
897   PetscErrorCode ierr;
898   PetscInt       mbs=a->mbs,bs=A->rmap->bs;
899   PetscScalar    *x,*from,zero=0.0;
900 
901   PetscFunctionBegin;
902   /*
903   PetscSynchronizedPrintf(PetscObjectComm((PetscObject)A)," MatMultAdd is called ...\n");
904   PetscSynchronizedFlush(PetscObjectComm((PetscObject)A),PETSC_STDOUT);
905   */
906   /* diagonal part */
907   ierr = (*a->A->ops->multadd)(a->A,xx,yy,a->slvec1a);CHKERRQ(ierr);
908   ierr = VecSet(a->slvec1b,zero);CHKERRQ(ierr);
909 
910   /* subdiagonal part */
911   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->slvec0b);CHKERRQ(ierr);
912 
913   /* copy x into the vec slvec0 */
914   ierr = VecGetArray(a->slvec0,&from);CHKERRQ(ierr);
915   ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
916   ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr);
917   ierr = VecRestoreArray(a->slvec0,&from);CHKERRQ(ierr);
918 
919   ierr = VecScatterBegin(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
920   ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
921   ierr = VecScatterEnd(a->sMvctx,a->slvec0,a->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
922 
923   /* supperdiagonal part */
924   ierr = (*a->B->ops->multadd)(a->B,a->slvec1b,a->slvec1a,zz);CHKERRQ(ierr);
925   PetscFunctionReturn(0);
926 }
927 
928 #undef __FUNCT__
929 #define __FUNCT__ "MatMultAdd_MPISBAIJ_2comm"
930 PetscErrorCode MatMultAdd_MPISBAIJ_2comm(Mat A,Vec xx,Vec yy,Vec zz)
931 {
932   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
933   PetscErrorCode ierr;
934 
935   PetscFunctionBegin;
936   ierr = VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
937   /* do diagonal part */
938   ierr = (*a->A->ops->multadd)(a->A,xx,yy,zz);CHKERRQ(ierr);
939   /* do supperdiagonal part */
940   ierr = VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
941   ierr = (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);CHKERRQ(ierr);
942 
943   /* do subdiagonal part */
944   ierr = (*a->B->ops->multtranspose)(a->B,xx,a->lvec);CHKERRQ(ierr);
945   ierr = VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
946   ierr = VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
947   PetscFunctionReturn(0);
948 }
949 
950 /*
951   This only works correctly for square matrices where the subblock A->A is the
952    diagonal block
953 */
954 #undef __FUNCT__
955 #define __FUNCT__ "MatGetDiagonal_MPISBAIJ"
956 PetscErrorCode MatGetDiagonal_MPISBAIJ(Mat A,Vec v)
957 {
958   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
959   PetscErrorCode ierr;
960 
961   PetscFunctionBegin;
962   /* if (a->rmap->N != a->cmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block"); */
963   ierr = MatGetDiagonal(a->A,v);CHKERRQ(ierr);
964   PetscFunctionReturn(0);
965 }
966 
967 #undef __FUNCT__
968 #define __FUNCT__ "MatScale_MPISBAIJ"
969 PetscErrorCode MatScale_MPISBAIJ(Mat A,PetscScalar aa)
970 {
971   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
972   PetscErrorCode ierr;
973 
974   PetscFunctionBegin;
975   ierr = MatScale(a->A,aa);CHKERRQ(ierr);
976   ierr = MatScale(a->B,aa);CHKERRQ(ierr);
977   PetscFunctionReturn(0);
978 }
979 
980 #undef __FUNCT__
981 #define __FUNCT__ "MatGetRow_MPISBAIJ"
982 PetscErrorCode MatGetRow_MPISBAIJ(Mat matin,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
983 {
984   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
985   PetscScalar    *vworkA,*vworkB,**pvA,**pvB,*v_p;
986   PetscErrorCode ierr;
987   PetscInt       bs = matin->rmap->bs,bs2 = mat->bs2,i,*cworkA,*cworkB,**pcA,**pcB;
988   PetscInt       nztot,nzA,nzB,lrow,brstart = matin->rmap->rstart,brend = matin->rmap->rend;
989   PetscInt       *cmap,*idx_p,cstart = mat->rstartbs;
990 
991   PetscFunctionBegin;
992   if (mat->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Already active");
993   mat->getrowactive = PETSC_TRUE;
994 
995   if (!mat->rowvalues && (idx || v)) {
996     /*
997         allocate enough space to hold information from the longest row.
998     */
999     Mat_SeqSBAIJ *Aa = (Mat_SeqSBAIJ*)mat->A->data;
1000     Mat_SeqBAIJ  *Ba = (Mat_SeqBAIJ*)mat->B->data;
1001     PetscInt     max = 1,mbs = mat->mbs,tmp;
1002     for (i=0; i<mbs; i++) {
1003       tmp = Aa->i[i+1] - Aa->i[i] + Ba->i[i+1] - Ba->i[i]; /* row length */
1004       if (max < tmp) max = tmp;
1005     }
1006     ierr = PetscMalloc2(max*bs2,&mat->rowvalues,max*bs2,&mat->rowindices);CHKERRQ(ierr);
1007   }
1008 
1009   if (row < brstart || row >= brend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local rows");
1010   lrow = row - brstart;  /* local row index */
1011 
1012   pvA = &vworkA; pcA = &cworkA; pvB = &vworkB; pcB = &cworkB;
1013   if (!v)   {pvA = 0; pvB = 0;}
1014   if (!idx) {pcA = 0; if (!v) pcB = 0;}
1015   ierr  = (*mat->A->ops->getrow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr);
1016   ierr  = (*mat->B->ops->getrow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr);
1017   nztot = nzA + nzB;
1018 
1019   cmap = mat->garray;
1020   if (v  || idx) {
1021     if (nztot) {
1022       /* Sort by increasing column numbers, assuming A and B already sorted */
1023       PetscInt imark = -1;
1024       if (v) {
1025         *v = v_p = mat->rowvalues;
1026         for (i=0; i<nzB; i++) {
1027           if (cmap[cworkB[i]/bs] < cstart) v_p[i] = vworkB[i];
1028           else break;
1029         }
1030         imark = i;
1031         for (i=0; i<nzA; i++)     v_p[imark+i] = vworkA[i];
1032         for (i=imark; i<nzB; i++) v_p[nzA+i]   = vworkB[i];
1033       }
1034       if (idx) {
1035         *idx = idx_p = mat->rowindices;
1036         if (imark > -1) {
1037           for (i=0; i<imark; i++) {
1038             idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1039           }
1040         } else {
1041           for (i=0; i<nzB; i++) {
1042             if (cmap[cworkB[i]/bs] < cstart) idx_p[i] = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs;
1043             else break;
1044           }
1045           imark = i;
1046         }
1047         for (i=0; i<nzA; i++)     idx_p[imark+i] = cstart*bs + cworkA[i];
1048         for (i=imark; i<nzB; i++) idx_p[nzA+i]   = cmap[cworkB[i]/bs]*bs + cworkB[i]%bs ;
1049       }
1050     } else {
1051       if (idx) *idx = 0;
1052       if (v)   *v   = 0;
1053     }
1054   }
1055   *nz  = nztot;
1056   ierr = (*mat->A->ops->restorerow)(mat->A,lrow,&nzA,pcA,pvA);CHKERRQ(ierr);
1057   ierr = (*mat->B->ops->restorerow)(mat->B,lrow,&nzB,pcB,pvB);CHKERRQ(ierr);
1058   PetscFunctionReturn(0);
1059 }
1060 
1061 #undef __FUNCT__
1062 #define __FUNCT__ "MatRestoreRow_MPISBAIJ"
1063 PetscErrorCode MatRestoreRow_MPISBAIJ(Mat mat,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1064 {
1065   Mat_MPISBAIJ *baij = (Mat_MPISBAIJ*)mat->data;
1066 
1067   PetscFunctionBegin;
1068   if (!baij->getrowactive) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"MatGetRow() must be called first");
1069   baij->getrowactive = PETSC_FALSE;
1070   PetscFunctionReturn(0);
1071 }
1072 
1073 #undef __FUNCT__
1074 #define __FUNCT__ "MatGetRowUpperTriangular_MPISBAIJ"
1075 PetscErrorCode MatGetRowUpperTriangular_MPISBAIJ(Mat A)
1076 {
1077   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1078   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1079 
1080   PetscFunctionBegin;
1081   aA->getrow_utriangular = PETSC_TRUE;
1082   PetscFunctionReturn(0);
1083 }
1084 #undef __FUNCT__
1085 #define __FUNCT__ "MatRestoreRowUpperTriangular_MPISBAIJ"
1086 PetscErrorCode MatRestoreRowUpperTriangular_MPISBAIJ(Mat A)
1087 {
1088   Mat_MPISBAIJ *a  = (Mat_MPISBAIJ*)A->data;
1089   Mat_SeqSBAIJ *aA = (Mat_SeqSBAIJ*)a->A->data;
1090 
1091   PetscFunctionBegin;
1092   aA->getrow_utriangular = PETSC_FALSE;
1093   PetscFunctionReturn(0);
1094 }
1095 
1096 #undef __FUNCT__
1097 #define __FUNCT__ "MatRealPart_MPISBAIJ"
1098 PetscErrorCode MatRealPart_MPISBAIJ(Mat A)
1099 {
1100   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1101   PetscErrorCode ierr;
1102 
1103   PetscFunctionBegin;
1104   ierr = MatRealPart(a->A);CHKERRQ(ierr);
1105   ierr = MatRealPart(a->B);CHKERRQ(ierr);
1106   PetscFunctionReturn(0);
1107 }
1108 
1109 #undef __FUNCT__
1110 #define __FUNCT__ "MatImaginaryPart_MPISBAIJ"
1111 PetscErrorCode MatImaginaryPart_MPISBAIJ(Mat A)
1112 {
1113   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1114   PetscErrorCode ierr;
1115 
1116   PetscFunctionBegin;
1117   ierr = MatImaginaryPart(a->A);CHKERRQ(ierr);
1118   ierr = MatImaginaryPart(a->B);CHKERRQ(ierr);
1119   PetscFunctionReturn(0);
1120 }
1121 
1122 #undef __FUNCT__
1123 #define __FUNCT__ "MatZeroEntries_MPISBAIJ"
1124 PetscErrorCode MatZeroEntries_MPISBAIJ(Mat A)
1125 {
1126   Mat_MPISBAIJ   *l = (Mat_MPISBAIJ*)A->data;
1127   PetscErrorCode ierr;
1128 
1129   PetscFunctionBegin;
1130   ierr = MatZeroEntries(l->A);CHKERRQ(ierr);
1131   ierr = MatZeroEntries(l->B);CHKERRQ(ierr);
1132   PetscFunctionReturn(0);
1133 }
1134 
1135 #undef __FUNCT__
1136 #define __FUNCT__ "MatGetInfo_MPISBAIJ"
1137 PetscErrorCode MatGetInfo_MPISBAIJ(Mat matin,MatInfoType flag,MatInfo *info)
1138 {
1139   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)matin->data;
1140   Mat            A  = a->A,B = a->B;
1141   PetscErrorCode ierr;
1142   PetscReal      isend[5],irecv[5];
1143 
1144   PetscFunctionBegin;
1145   info->block_size = (PetscReal)matin->rmap->bs;
1146 
1147   ierr = MatGetInfo(A,MAT_LOCAL,info);CHKERRQ(ierr);
1148 
1149   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
1150   isend[3] = info->memory;  isend[4] = info->mallocs;
1151 
1152   ierr = MatGetInfo(B,MAT_LOCAL,info);CHKERRQ(ierr);
1153 
1154   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
1155   isend[3] += info->memory;  isend[4] += info->mallocs;
1156   if (flag == MAT_LOCAL) {
1157     info->nz_used      = isend[0];
1158     info->nz_allocated = isend[1];
1159     info->nz_unneeded  = isend[2];
1160     info->memory       = isend[3];
1161     info->mallocs      = isend[4];
1162   } else if (flag == MAT_GLOBAL_MAX) {
1163     ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr);
1164 
1165     info->nz_used      = irecv[0];
1166     info->nz_allocated = irecv[1];
1167     info->nz_unneeded  = irecv[2];
1168     info->memory       = irecv[3];
1169     info->mallocs      = irecv[4];
1170   } else if (flag == MAT_GLOBAL_SUM) {
1171     ierr = MPI_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));CHKERRQ(ierr);
1172 
1173     info->nz_used      = irecv[0];
1174     info->nz_allocated = irecv[1];
1175     info->nz_unneeded  = irecv[2];
1176     info->memory       = irecv[3];
1177     info->mallocs      = irecv[4];
1178   } else SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Unknown MatInfoType argument %d",(int)flag);
1179   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1180   info->fill_ratio_needed = 0;
1181   info->factor_mallocs    = 0;
1182   PetscFunctionReturn(0);
1183 }
1184 
1185 #undef __FUNCT__
1186 #define __FUNCT__ "MatSetOption_MPISBAIJ"
1187 PetscErrorCode MatSetOption_MPISBAIJ(Mat A,MatOption op,PetscBool flg)
1188 {
1189   Mat_MPISBAIJ   *a  = (Mat_MPISBAIJ*)A->data;
1190   Mat_SeqSBAIJ   *aA = (Mat_SeqSBAIJ*)a->A->data;
1191   PetscErrorCode ierr;
1192 
1193   PetscFunctionBegin;
1194   switch (op) {
1195   case MAT_NEW_NONZERO_LOCATIONS:
1196   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1197   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1198   case MAT_KEEP_NONZERO_PATTERN:
1199   case MAT_NEW_NONZERO_LOCATION_ERR:
1200     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1201     ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr);
1202     break;
1203   case MAT_ROW_ORIENTED:
1204     a->roworiented = flg;
1205 
1206     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1207     ierr = MatSetOption(a->B,op,flg);CHKERRQ(ierr);
1208     break;
1209   case MAT_NEW_DIAGONALS:
1210     ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr);
1211     break;
1212   case MAT_IGNORE_OFF_PROC_ENTRIES:
1213     a->donotstash = flg;
1214     break;
1215   case MAT_USE_HASH_TABLE:
1216     a->ht_flag = flg;
1217     break;
1218   case MAT_HERMITIAN:
1219     if (!A->assembled) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Must call MatAssemblyEnd() first");
1220     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1221 
1222     A->ops->mult = MatMult_MPISBAIJ_Hermitian;
1223     break;
1224   case MAT_SPD:
1225     A->spd_set = PETSC_TRUE;
1226     A->spd     = flg;
1227     if (flg) {
1228       A->symmetric                  = PETSC_TRUE;
1229       A->structurally_symmetric     = PETSC_TRUE;
1230       A->symmetric_set              = PETSC_TRUE;
1231       A->structurally_symmetric_set = PETSC_TRUE;
1232     }
1233     break;
1234   case MAT_SYMMETRIC:
1235     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1236     break;
1237   case MAT_STRUCTURALLY_SYMMETRIC:
1238     ierr = MatSetOption(a->A,op,flg);CHKERRQ(ierr);
1239     break;
1240   case MAT_SYMMETRY_ETERNAL:
1241     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Matrix must be symmetric");
1242     ierr = PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);CHKERRQ(ierr);
1243     break;
1244   case MAT_IGNORE_LOWER_TRIANGULAR:
1245     aA->ignore_ltriangular = flg;
1246     break;
1247   case MAT_ERROR_LOWER_TRIANGULAR:
1248     aA->ignore_ltriangular = flg;
1249     break;
1250   case MAT_GETROW_UPPERTRIANGULAR:
1251     aA->getrow_utriangular = flg;
1252     break;
1253   default:
1254     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1255   }
1256   PetscFunctionReturn(0);
1257 }
1258 
1259 #undef __FUNCT__
1260 #define __FUNCT__ "MatTranspose_MPISBAIJ"
1261 PetscErrorCode MatTranspose_MPISBAIJ(Mat A,MatReuse reuse,Mat *B)
1262 {
1263   PetscErrorCode ierr;
1264 
1265   PetscFunctionBegin;
1266   if (MAT_INITIAL_MATRIX || *B != A) {
1267     ierr = MatDuplicate(A,MAT_COPY_VALUES,B);CHKERRQ(ierr);
1268   }
1269   PetscFunctionReturn(0);
1270 }
1271 
1272 #undef __FUNCT__
1273 #define __FUNCT__ "MatDiagonalScale_MPISBAIJ"
1274 PetscErrorCode MatDiagonalScale_MPISBAIJ(Mat mat,Vec ll,Vec rr)
1275 {
1276   Mat_MPISBAIJ   *baij = (Mat_MPISBAIJ*)mat->data;
1277   Mat            a     = baij->A, b=baij->B;
1278   PetscErrorCode ierr;
1279   PetscInt       nv,m,n;
1280   PetscBool      flg;
1281 
1282   PetscFunctionBegin;
1283   if (ll != rr) {
1284     ierr = VecEqual(ll,rr,&flg);CHKERRQ(ierr);
1285     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"For symmetric format, left and right scaling vectors must be same\n");
1286   }
1287   if (!ll) PetscFunctionReturn(0);
1288 
1289   ierr = MatGetLocalSize(mat,&m,&n);CHKERRQ(ierr);
1290   if (m != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"For symmetric format, local size %d %d must be same",m,n);
1291 
1292   ierr = VecGetLocalSize(rr,&nv);CHKERRQ(ierr);
1293   if (nv!=n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Left and right vector non-conforming local size");
1294 
1295   ierr = VecScatterBegin(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1296 
1297   /* left diagonalscale the off-diagonal part */
1298   ierr = (*b->ops->diagonalscale)(b,ll,NULL);CHKERRQ(ierr);
1299 
1300   /* scale the diagonal part */
1301   ierr = (*a->ops->diagonalscale)(a,ll,rr);CHKERRQ(ierr);
1302 
1303   /* right diagonalscale the off-diagonal part */
1304   ierr = VecScatterEnd(baij->Mvctx,rr,baij->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
1305   ierr = (*b->ops->diagonalscale)(b,NULL,baij->lvec);CHKERRQ(ierr);
1306   PetscFunctionReturn(0);
1307 }
1308 
1309 #undef __FUNCT__
1310 #define __FUNCT__ "MatSetUnfactored_MPISBAIJ"
1311 PetscErrorCode MatSetUnfactored_MPISBAIJ(Mat A)
1312 {
1313   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1314   PetscErrorCode ierr;
1315 
1316   PetscFunctionBegin;
1317   ierr = MatSetUnfactored(a->A);CHKERRQ(ierr);
1318   PetscFunctionReturn(0);
1319 }
1320 
1321 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat,MatDuplicateOption,Mat*);
1322 
1323 #undef __FUNCT__
1324 #define __FUNCT__ "MatEqual_MPISBAIJ"
1325 PetscErrorCode MatEqual_MPISBAIJ(Mat A,Mat B,PetscBool  *flag)
1326 {
1327   Mat_MPISBAIJ   *matB = (Mat_MPISBAIJ*)B->data,*matA = (Mat_MPISBAIJ*)A->data;
1328   Mat            a,b,c,d;
1329   PetscBool      flg;
1330   PetscErrorCode ierr;
1331 
1332   PetscFunctionBegin;
1333   a = matA->A; b = matA->B;
1334   c = matB->A; d = matB->B;
1335 
1336   ierr = MatEqual(a,c,&flg);CHKERRQ(ierr);
1337   if (flg) {
1338     ierr = MatEqual(b,d,&flg);CHKERRQ(ierr);
1339   }
1340   ierr = MPI_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
1341   PetscFunctionReturn(0);
1342 }
1343 
1344 #undef __FUNCT__
1345 #define __FUNCT__ "MatCopy_MPISBAIJ"
1346 PetscErrorCode MatCopy_MPISBAIJ(Mat A,Mat B,MatStructure str)
1347 {
1348   PetscErrorCode ierr;
1349   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
1350   Mat_MPISBAIJ   *b = (Mat_MPISBAIJ*)B->data;
1351 
1352   PetscFunctionBegin;
1353   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1354   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1355     ierr = MatGetRowUpperTriangular(A);CHKERRQ(ierr);
1356     ierr = MatCopy_Basic(A,B,str);CHKERRQ(ierr);
1357     ierr = MatRestoreRowUpperTriangular(A);CHKERRQ(ierr);
1358   } else {
1359     ierr = MatCopy(a->A,b->A,str);CHKERRQ(ierr);
1360     ierr = MatCopy(a->B,b->B,str);CHKERRQ(ierr);
1361   }
1362   PetscFunctionReturn(0);
1363 }
1364 
1365 #undef __FUNCT__
1366 #define __FUNCT__ "MatSetUp_MPISBAIJ"
1367 PetscErrorCode MatSetUp_MPISBAIJ(Mat A)
1368 {
1369   PetscErrorCode ierr;
1370 
1371   PetscFunctionBegin;
1372   ierr = MatMPISBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0,PETSC_DEFAULT,0);CHKERRQ(ierr);
1373   PetscFunctionReturn(0);
1374 }
1375 
1376 #undef __FUNCT__
1377 #define __FUNCT__ "MatAXPY_MPISBAIJ"
1378 PetscErrorCode MatAXPY_MPISBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
1379 {
1380   PetscErrorCode ierr;
1381   Mat_MPISBAIJ   *xx=(Mat_MPISBAIJ*)X->data,*yy=(Mat_MPISBAIJ*)Y->data;
1382   PetscBLASInt   bnz,one=1;
1383   Mat_SeqSBAIJ   *xa,*ya;
1384   Mat_SeqBAIJ    *xb,*yb;
1385 
1386   PetscFunctionBegin;
1387   if (str == SAME_NONZERO_PATTERN) {
1388     PetscScalar alpha = a;
1389     xa   = (Mat_SeqSBAIJ*)xx->A->data;
1390     ya   = (Mat_SeqSBAIJ*)yy->A->data;
1391     ierr = PetscBLASIntCast(xa->nz,&bnz);CHKERRQ(ierr);
1392     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xa->a,&one,ya->a,&one));
1393     xb   = (Mat_SeqBAIJ*)xx->B->data;
1394     yb   = (Mat_SeqBAIJ*)yy->B->data;
1395     ierr = PetscBLASIntCast(xb->nz,&bnz);CHKERRQ(ierr);
1396     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,xb->a,&one,yb->a,&one));
1397   } else {
1398     ierr = MatGetRowUpperTriangular(X);CHKERRQ(ierr);
1399     ierr = MatAXPY_Basic(Y,a,X,str);CHKERRQ(ierr);
1400     ierr = MatRestoreRowUpperTriangular(X);CHKERRQ(ierr);
1401   }
1402   PetscFunctionReturn(0);
1403 }
1404 
1405 #undef __FUNCT__
1406 #define __FUNCT__ "MatGetSubMatrices_MPISBAIJ"
1407 PetscErrorCode MatGetSubMatrices_MPISBAIJ(Mat A,PetscInt n,const IS irow[],const IS icol[],MatReuse scall,Mat *B[])
1408 {
1409   PetscErrorCode ierr;
1410   PetscInt       i;
1411   PetscBool      flg;
1412 
1413   PetscFunctionBegin;
1414   for (i=0; i<n; i++) {
1415     ierr = ISEqual(irow[i],icol[i],&flg);CHKERRQ(ierr);
1416     if (!flg) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only get symmetric submatrix for MPISBAIJ matrices");
1417   }
1418   ierr = MatGetSubMatrices_MPIBAIJ(A,n,irow,icol,scall,B);CHKERRQ(ierr);
1419   PetscFunctionReturn(0);
1420 }
1421 
1422 
1423 /* -------------------------------------------------------------------*/
1424 static struct _MatOps MatOps_Values = {MatSetValues_MPISBAIJ,
1425                                        MatGetRow_MPISBAIJ,
1426                                        MatRestoreRow_MPISBAIJ,
1427                                        MatMult_MPISBAIJ,
1428                                /*  4*/ MatMultAdd_MPISBAIJ,
1429                                        MatMult_MPISBAIJ,       /* transpose versions are same as non-transpose */
1430                                        MatMultAdd_MPISBAIJ,
1431                                        0,
1432                                        0,
1433                                        0,
1434                                /* 10*/ 0,
1435                                        0,
1436                                        0,
1437                                        MatSOR_MPISBAIJ,
1438                                        MatTranspose_MPISBAIJ,
1439                                /* 15*/ MatGetInfo_MPISBAIJ,
1440                                        MatEqual_MPISBAIJ,
1441                                        MatGetDiagonal_MPISBAIJ,
1442                                        MatDiagonalScale_MPISBAIJ,
1443                                        MatNorm_MPISBAIJ,
1444                                /* 20*/ MatAssemblyBegin_MPISBAIJ,
1445                                        MatAssemblyEnd_MPISBAIJ,
1446                                        MatSetOption_MPISBAIJ,
1447                                        MatZeroEntries_MPISBAIJ,
1448                                /* 24*/ 0,
1449                                        0,
1450                                        0,
1451                                        0,
1452                                        0,
1453                                /* 29*/ MatSetUp_MPISBAIJ,
1454                                        0,
1455                                        0,
1456                                        0,
1457                                        0,
1458                                /* 34*/ MatDuplicate_MPISBAIJ,
1459                                        0,
1460                                        0,
1461                                        0,
1462                                        0,
1463                                /* 39*/ MatAXPY_MPISBAIJ,
1464                                        MatGetSubMatrices_MPISBAIJ,
1465                                        MatIncreaseOverlap_MPISBAIJ,
1466                                        MatGetValues_MPISBAIJ,
1467                                        MatCopy_MPISBAIJ,
1468                                /* 44*/ 0,
1469                                        MatScale_MPISBAIJ,
1470                                        0,
1471                                        0,
1472                                        0,
1473                                /* 49*/ 0,
1474                                        0,
1475                                        0,
1476                                        0,
1477                                        0,
1478                                /* 54*/ 0,
1479                                        0,
1480                                        MatSetUnfactored_MPISBAIJ,
1481                                        0,
1482                                        MatSetValuesBlocked_MPISBAIJ,
1483                                /* 59*/ 0,
1484                                        0,
1485                                        0,
1486                                        0,
1487                                        0,
1488                                /* 64*/ 0,
1489                                        0,
1490                                        0,
1491                                        0,
1492                                        0,
1493                                /* 69*/ MatGetRowMaxAbs_MPISBAIJ,
1494                                        0,
1495                                        0,
1496                                        0,
1497                                        0,
1498                                /* 74*/ 0,
1499                                        0,
1500                                        0,
1501                                        0,
1502                                        0,
1503                                /* 79*/ 0,
1504                                        0,
1505                                        0,
1506                                        0,
1507                                        MatLoad_MPISBAIJ,
1508                                /* 84*/ 0,
1509                                        0,
1510                                        0,
1511                                        0,
1512                                        0,
1513                                /* 89*/ 0,
1514                                        0,
1515                                        0,
1516                                        0,
1517                                        0,
1518                                /* 94*/ 0,
1519                                        0,
1520                                        0,
1521                                        0,
1522                                        0,
1523                                /* 99*/ 0,
1524                                        0,
1525                                        0,
1526                                        0,
1527                                        0,
1528                                /*104*/ 0,
1529                                        MatRealPart_MPISBAIJ,
1530                                        MatImaginaryPart_MPISBAIJ,
1531                                        MatGetRowUpperTriangular_MPISBAIJ,
1532                                        MatRestoreRowUpperTriangular_MPISBAIJ,
1533                                /*109*/ 0,
1534                                        0,
1535                                        0,
1536                                        0,
1537                                        0,
1538                                /*114*/ 0,
1539                                        0,
1540                                        0,
1541                                        0,
1542                                        0,
1543                                /*119*/ 0,
1544                                        0,
1545                                        0,
1546                                        0,
1547                                        0,
1548                                /*124*/ 0,
1549                                        0,
1550                                        0,
1551                                        0,
1552                                        0,
1553                                /*129*/ 0,
1554                                        0,
1555                                        0,
1556                                        0,
1557                                        0,
1558                                /*134*/ 0,
1559                                        0,
1560                                        0,
1561                                        0,
1562                                        0,
1563                                /*139*/ 0,
1564                                        0,
1565                                        0
1566 };
1567 
1568 
1569 #undef __FUNCT__
1570 #define __FUNCT__ "MatGetDiagonalBlock_MPISBAIJ"
1571 PetscErrorCode  MatGetDiagonalBlock_MPISBAIJ(Mat A,Mat *a)
1572 {
1573   PetscFunctionBegin;
1574   *a = ((Mat_MPISBAIJ*)A->data)->A;
1575   PetscFunctionReturn(0);
1576 }
1577 
1578 #undef __FUNCT__
1579 #define __FUNCT__ "MatMPISBAIJSetPreallocation_MPISBAIJ"
1580 PetscErrorCode  MatMPISBAIJSetPreallocation_MPISBAIJ(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt *d_nnz,PetscInt o_nz,const PetscInt *o_nnz)
1581 {
1582   Mat_MPISBAIJ   *b;
1583   PetscErrorCode ierr;
1584   PetscInt       i,mbs,Mbs;
1585 
1586   PetscFunctionBegin;
1587   ierr = MatSetBlockSize(B,PetscAbs(bs));CHKERRQ(ierr);
1588   ierr = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
1589   ierr = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
1590   ierr = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
1591 
1592   b   = (Mat_MPISBAIJ*)B->data;
1593   mbs = B->rmap->n/bs;
1594   Mbs = B->rmap->N/bs;
1595   if (mbs*bs != B->rmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"No of local rows %D must be divisible by blocksize %D",B->rmap->N,bs);
1596 
1597   B->rmap->bs = bs;
1598   b->bs2      = bs*bs;
1599   b->mbs      = mbs;
1600   b->nbs      = mbs;
1601   b->Mbs      = Mbs;
1602   b->Nbs      = Mbs;
1603 
1604   for (i=0; i<=b->size; i++) {
1605     b->rangebs[i] = B->rmap->range[i]/bs;
1606   }
1607   b->rstartbs = B->rmap->rstart/bs;
1608   b->rendbs   = B->rmap->rend/bs;
1609 
1610   b->cstartbs = B->cmap->rstart/bs;
1611   b->cendbs   = B->cmap->rend/bs;
1612 
1613   if (!B->preallocated) {
1614     ierr = MatCreate(PETSC_COMM_SELF,&b->A);CHKERRQ(ierr);
1615     ierr = MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);CHKERRQ(ierr);
1616     ierr = MatSetType(b->A,MATSEQSBAIJ);CHKERRQ(ierr);
1617     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);CHKERRQ(ierr);
1618     ierr = MatCreate(PETSC_COMM_SELF,&b->B);CHKERRQ(ierr);
1619     ierr = MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);CHKERRQ(ierr);
1620     ierr = MatSetType(b->B,MATSEQBAIJ);CHKERRQ(ierr);
1621     ierr = PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);CHKERRQ(ierr);
1622     ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),bs,&B->bstash);CHKERRQ(ierr);
1623   }
1624 
1625   ierr = MatSeqSBAIJSetPreallocation(b->A,bs,d_nz,d_nnz);CHKERRQ(ierr);
1626   ierr = MatSeqBAIJSetPreallocation(b->B,bs,o_nz,o_nnz);CHKERRQ(ierr);
1627 
1628   B->preallocated = PETSC_TRUE;
1629   PetscFunctionReturn(0);
1630 }
1631 
1632 #undef __FUNCT__
1633 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR_MPISBAIJ"
1634 PetscErrorCode MatMPISBAIJSetPreallocationCSR_MPISBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
1635 {
1636   PetscInt       m,rstart,cstart,cend;
1637   PetscInt       i,j,d,nz,nz_max=0,*d_nnz=0,*o_nnz=0;
1638   const PetscInt *JJ    =0;
1639   PetscScalar    *values=0;
1640   PetscErrorCode ierr;
1641 
1642   PetscFunctionBegin;
1643   if (bs < 1) SETERRQ1(PetscObjectComm((PetscObject)B),PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
1644   ierr   = PetscLayoutSetBlockSize(B->rmap,bs);CHKERRQ(ierr);
1645   ierr   = PetscLayoutSetBlockSize(B->cmap,bs);CHKERRQ(ierr);
1646   ierr   = PetscLayoutSetUp(B->rmap);CHKERRQ(ierr);
1647   ierr   = PetscLayoutSetUp(B->cmap);CHKERRQ(ierr);
1648   ierr   = PetscLayoutGetBlockSize(B->rmap,&bs);CHKERRQ(ierr);
1649   m      = B->rmap->n/bs;
1650   rstart = B->rmap->rstart/bs;
1651   cstart = B->cmap->rstart/bs;
1652   cend   = B->cmap->rend/bs;
1653 
1654   if (ii[0]) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"ii[0] must be 0 but it is %D",ii[0]);
1655   ierr = PetscMalloc2(m,&d_nnz,m,&o_nnz);CHKERRQ(ierr);
1656   for (i=0; i<m; i++) {
1657     nz = ii[i+1] - ii[i];
1658     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Local row %D has a negative number of columns %D",i,nz);
1659     nz_max = PetscMax(nz_max,nz);
1660     JJ     = jj + ii[i];
1661     for (j=0; j<nz; j++) {
1662       if (*JJ >= cstart) break;
1663       JJ++;
1664     }
1665     d = 0;
1666     for (; j<nz; j++) {
1667       if (*JJ++ >= cend) break;
1668       d++;
1669     }
1670     d_nnz[i] = d;
1671     o_nnz[i] = nz - d;
1672   }
1673   ierr = MatMPISBAIJSetPreallocation(B,bs,0,d_nnz,0,o_nnz);CHKERRQ(ierr);
1674   ierr = PetscFree2(d_nnz,o_nnz);CHKERRQ(ierr);
1675 
1676   values = (PetscScalar*)V;
1677   if (!values) {
1678     ierr = PetscMalloc1(bs*bs*nz_max,&values);CHKERRQ(ierr);
1679     ierr = PetscMemzero(values,bs*bs*nz_max*sizeof(PetscScalar));CHKERRQ(ierr);
1680   }
1681   for (i=0; i<m; i++) {
1682     PetscInt          row    = i + rstart;
1683     PetscInt          ncols  = ii[i+1] - ii[i];
1684     const PetscInt    *icols = jj + ii[i];
1685     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
1686     ierr = MatSetValuesBlocked_MPISBAIJ(B,1,&row,ncols,icols,svals,INSERT_VALUES);CHKERRQ(ierr);
1687   }
1688 
1689   if (!V) { ierr = PetscFree(values);CHKERRQ(ierr); }
1690   ierr = MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1691   ierr = MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
1692   ierr = MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);
1693   PetscFunctionReturn(0);
1694 }
1695 
1696 #if defined(PETSC_HAVE_MUMPS)
1697 PETSC_EXTERN PetscErrorCode MatGetFactor_sbaij_mumps(Mat,MatFactorType,Mat*);
1698 #endif
1699 #if defined(PETSC_HAVE_PASTIX)
1700 PETSC_EXTERN PetscErrorCode MatGetFactor_mpisbaij_pastix(Mat,MatFactorType,Mat*);
1701 #endif
1702 
1703 /*MC
1704    MATMPISBAIJ - MATMPISBAIJ = "mpisbaij" - A matrix type to be used for distributed symmetric sparse block matrices,
1705    based on block compressed sparse row format.  Only the upper triangular portion of the "diagonal" portion of
1706    the matrix is stored.
1707 
1708   For complex numbers by default this matrix is symmetric, NOT Hermitian symmetric. To make it Hermitian symmetric you
1709   can call MatSetOption(Mat, MAT_HERMITIAN);
1710 
1711    Options Database Keys:
1712 . -mat_type mpisbaij - sets the matrix type to "mpisbaij" during a call to MatSetFromOptions()
1713 
1714   Level: beginner
1715 
1716 .seealso: MatCreateMPISBAIJ
1717 M*/
1718 
1719 PETSC_EXTERN PetscErrorCode MatConvert_MPISBAIJ_MPISBSTRM(Mat,MatType,MatReuse,Mat*);
1720 
1721 #undef __FUNCT__
1722 #define __FUNCT__ "MatCreate_MPISBAIJ"
1723 PETSC_EXTERN PetscErrorCode MatCreate_MPISBAIJ(Mat B)
1724 {
1725   Mat_MPISBAIJ   *b;
1726   PetscErrorCode ierr;
1727   PetscBool      flg;
1728 
1729   PetscFunctionBegin;
1730   ierr    = PetscNewLog(B,&b);CHKERRQ(ierr);
1731   B->data = (void*)b;
1732   ierr    = PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));CHKERRQ(ierr);
1733 
1734   B->ops->destroy = MatDestroy_MPISBAIJ;
1735   B->ops->view    = MatView_MPISBAIJ;
1736   B->assembled    = PETSC_FALSE;
1737   B->insertmode   = NOT_SET_VALUES;
1738 
1739   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);CHKERRQ(ierr);
1740   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)B),&b->size);CHKERRQ(ierr);
1741 
1742   /* build local table of row and column ownerships */
1743   ierr = PetscMalloc1((b->size+2),&b->rangebs);CHKERRQ(ierr);
1744 
1745   /* build cache for off array entries formed */
1746   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);CHKERRQ(ierr);
1747 
1748   b->donotstash  = PETSC_FALSE;
1749   b->colmap      = NULL;
1750   b->garray      = NULL;
1751   b->roworiented = PETSC_TRUE;
1752 
1753   /* stuff used in block assembly */
1754   b->barray = 0;
1755 
1756   /* stuff used for matrix vector multiply */
1757   b->lvec    = 0;
1758   b->Mvctx   = 0;
1759   b->slvec0  = 0;
1760   b->slvec0b = 0;
1761   b->slvec1  = 0;
1762   b->slvec1a = 0;
1763   b->slvec1b = 0;
1764   b->sMvctx  = 0;
1765 
1766   /* stuff for MatGetRow() */
1767   b->rowindices   = 0;
1768   b->rowvalues    = 0;
1769   b->getrowactive = PETSC_FALSE;
1770 
1771   /* hash table stuff */
1772   b->ht           = 0;
1773   b->hd           = 0;
1774   b->ht_size      = 0;
1775   b->ht_flag      = PETSC_FALSE;
1776   b->ht_fact      = 0;
1777   b->ht_total_ct  = 0;
1778   b->ht_insert_ct = 0;
1779 
1780   /* stuff for MatGetSubMatrices_MPIBAIJ_local() */
1781   b->ijonly = PETSC_FALSE;
1782 
1783   b->in_loc = 0;
1784   b->v_loc  = 0;
1785   b->n_loc  = 0;
1786   ierr      = PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Options for loading MPISBAIJ matrix 1","Mat");CHKERRQ(ierr);
1787   ierr      = PetscOptionsBool("-mat_use_hash_table","Use hash table to save memory in constructing matrix","MatSetOption",PETSC_FALSE,&flg,NULL);CHKERRQ(ierr);
1788   if (flg) {
1789     PetscReal fact = 1.39;
1790     ierr = MatSetOption(B,MAT_USE_HASH_TABLE,PETSC_TRUE);CHKERRQ(ierr);
1791     ierr = PetscOptionsReal("-mat_use_hash_table","Use hash table factor","MatMPIBAIJSetHashTableFactor",fact,&fact,NULL);CHKERRQ(ierr);
1792     if (fact <= 1.0) fact = 1.39;
1793     ierr = MatMPIBAIJSetHashTableFactor(B,fact);CHKERRQ(ierr);
1794     ierr = PetscInfo1(B,"Hash table Factor used %5.2f\n",fact);CHKERRQ(ierr);
1795   }
1796   ierr = PetscOptionsEnd();CHKERRQ(ierr);
1797 
1798 #if defined(PETSC_HAVE_PASTIX)
1799   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_pastix_C",MatGetFactor_mpisbaij_pastix);CHKERRQ(ierr);
1800 #endif
1801 #if defined(PETSC_HAVE_MUMPS)
1802   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetFactor_mumps_C",MatGetFactor_sbaij_mumps);CHKERRQ(ierr);
1803 #endif
1804   ierr = PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISBAIJ);CHKERRQ(ierr);
1805   ierr = PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISBAIJ);CHKERRQ(ierr);
1806   ierr = PetscObjectComposeFunction((PetscObject)B,"MatGetDiagonalBlock_C",MatGetDiagonalBlock_MPISBAIJ);CHKERRQ(ierr);
1807   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocation_C",MatMPISBAIJSetPreallocation_MPISBAIJ);CHKERRQ(ierr);
1808   ierr = PetscObjectComposeFunction((PetscObject)B,"MatMPISBAIJSetPreallocationCSR_C",MatMPISBAIJSetPreallocationCSR_MPISBAIJ);CHKERRQ(ierr);
1809   ierr = PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisbaij_mpisbstrm_C",MatConvert_MPISBAIJ_MPISBSTRM);CHKERRQ(ierr);
1810 
1811   B->symmetric                  = PETSC_TRUE;
1812   B->structurally_symmetric     = PETSC_TRUE;
1813   B->symmetric_set              = PETSC_TRUE;
1814   B->structurally_symmetric_set = PETSC_TRUE;
1815 
1816   ierr = PetscObjectChangeTypeName((PetscObject)B,MATMPISBAIJ);CHKERRQ(ierr);
1817   PetscFunctionReturn(0);
1818 }
1819 
1820 /*MC
1821    MATSBAIJ - MATSBAIJ = "sbaij" - A matrix type to be used for symmetric block sparse matrices.
1822 
1823    This matrix type is identical to MATSEQSBAIJ when constructed with a single process communicator,
1824    and MATMPISBAIJ otherwise.
1825 
1826    Options Database Keys:
1827 . -mat_type sbaij - sets the matrix type to "sbaij" during a call to MatSetFromOptions()
1828 
1829   Level: beginner
1830 
1831 .seealso: MatCreateMPISBAIJ,MATSEQSBAIJ,MATMPISBAIJ
1832 M*/
1833 
1834 #undef __FUNCT__
1835 #define __FUNCT__ "MatMPISBAIJSetPreallocation"
1836 /*@C
1837    MatMPISBAIJSetPreallocation - For good matrix assembly performance
1838    the user should preallocate the matrix storage by setting the parameters
1839    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
1840    performance can be increased by more than a factor of 50.
1841 
1842    Collective on Mat
1843 
1844    Input Parameters:
1845 +  A - the matrix
1846 .  bs   - size of blockk
1847 .  d_nz  - number of block nonzeros per block row in diagonal portion of local
1848            submatrix  (same for all local rows)
1849 .  d_nnz - array containing the number of block nonzeros in the various block rows
1850            in the upper triangular and diagonal part of the in diagonal portion of the local
1851            (possibly different for each block row) or NULL.  If you plan to factor the matrix you must leave room
1852            for the diagonal entry and set a value even if it is zero.
1853 .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
1854            submatrix (same for all local rows).
1855 -  o_nnz - array containing the number of nonzeros in the various block rows of the
1856            off-diagonal portion of the local submatrix that is right of the diagonal
1857            (possibly different for each block row) or NULL.
1858 
1859 
1860    Options Database Keys:
1861 .   -mat_no_unroll - uses code that does not unroll the loops in the
1862                      block calculations (much slower)
1863 .   -mat_block_size - size of the blocks to use
1864 
1865    Notes:
1866 
1867    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
1868    than it must be used on all processors that share the object for that argument.
1869 
1870    If the *_nnz parameter is given then the *_nz parameter is ignored
1871 
1872    Storage Information:
1873    For a square global matrix we define each processor's diagonal portion
1874    to be its local rows and the corresponding columns (a square submatrix);
1875    each processor's off-diagonal portion encompasses the remainder of the
1876    local matrix (a rectangular submatrix).
1877 
1878    The user can specify preallocated storage for the diagonal part of
1879    the local submatrix with either d_nz or d_nnz (not both).  Set
1880    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
1881    memory allocation.  Likewise, specify preallocated storage for the
1882    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
1883 
1884    You can call MatGetInfo() to get information on how effective the preallocation was;
1885    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
1886    You can also run with the option -info and look for messages with the string
1887    malloc in them to see if additional memory allocation was needed.
1888 
1889    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
1890    the figure below we depict these three local rows and all columns (0-11).
1891 
1892 .vb
1893            0 1 2 3 4 5 6 7 8 9 10 11
1894           --------------------------
1895    row 3  |. . . d d d o o o o  o  o
1896    row 4  |. . . d d d o o o o  o  o
1897    row 5  |. . . d d d o o o o  o  o
1898           --------------------------
1899 .ve
1900 
1901    Thus, any entries in the d locations are stored in the d (diagonal)
1902    submatrix, and any entries in the o locations are stored in the
1903    o (off-diagonal) submatrix.  Note that the d matrix is stored in
1904    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.
1905 
1906    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
1907    plus the diagonal part of the d matrix,
1908    and o_nz should indicate the number of block nonzeros per row in the o matrix
1909 
1910    In general, for PDE problems in which most nonzeros are near the diagonal,
1911    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
1912    or you will get TERRIBLE performance; see the users' manual chapter on
1913    matrices.
1914 
1915    Level: intermediate
1916 
1917 .keywords: matrix, block, aij, compressed row, sparse, parallel
1918 
1919 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ(), PetscSplitOwnership()
1920 @*/
1921 PetscErrorCode  MatMPISBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
1922 {
1923   PetscErrorCode ierr;
1924 
1925   PetscFunctionBegin;
1926   PetscValidHeaderSpecific(B,MAT_CLASSID,1);
1927   PetscValidType(B,1);
1928   PetscValidLogicalCollectiveInt(B,bs,2);
1929   ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,bs,d_nz,d_nnz,o_nz,o_nnz));CHKERRQ(ierr);
1930   PetscFunctionReturn(0);
1931 }
1932 
1933 #undef __FUNCT__
1934 #define __FUNCT__ "MatCreateSBAIJ"
1935 /*@C
1936    MatCreateSBAIJ - Creates a sparse parallel matrix in symmetric block AIJ format
1937    (block compressed row).  For good matrix assembly performance
1938    the user should preallocate the matrix storage by setting the parameters
1939    d_nz (or d_nnz) and o_nz (or o_nnz).  By setting these parameters accurately,
1940    performance can be increased by more than a factor of 50.
1941 
1942    Collective on MPI_Comm
1943 
1944    Input Parameters:
1945 +  comm - MPI communicator
1946 .  bs   - size of blockk
1947 .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
1948            This value should be the same as the local size used in creating the
1949            y vector for the matrix-vector product y = Ax.
1950 .  n - number of local columns (or PETSC_DECIDE to have calculated if N is given)
1951            This value should be the same as the local size used in creating the
1952            x vector for the matrix-vector product y = Ax.
1953 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
1954 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
1955 .  d_nz  - number of block nonzeros per block row in diagonal portion of local
1956            submatrix  (same for all local rows)
1957 .  d_nnz - array containing the number of block nonzeros in the various block rows
1958            in the upper triangular portion of the in diagonal portion of the local
1959            (possibly different for each block block row) or NULL.
1960            If you plan to factor the matrix you must leave room for the diagonal entry and
1961            set its value even if it is zero.
1962 .  o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
1963            submatrix (same for all local rows).
1964 -  o_nnz - array containing the number of nonzeros in the various block rows of the
1965            off-diagonal portion of the local submatrix (possibly different for
1966            each block row) or NULL.
1967 
1968    Output Parameter:
1969 .  A - the matrix
1970 
1971    Options Database Keys:
1972 .   -mat_no_unroll - uses code that does not unroll the loops in the
1973                      block calculations (much slower)
1974 .   -mat_block_size - size of the blocks to use
1975 .   -mat_mpi - use the parallel matrix data structures even on one processor
1976                (defaults to using SeqBAIJ format on one processor)
1977 
1978    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
1979    MatXXXXSetPreallocation() paradgm instead of this routine directly.
1980    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]
1981 
1982    Notes:
1983    The number of rows and columns must be divisible by blocksize.
1984    This matrix type does not support complex Hermitian operation.
1985 
1986    The user MUST specify either the local or global matrix dimensions
1987    (possibly both).
1988 
1989    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one processor
1990    than it must be used on all processors that share the object for that argument.
1991 
1992    If the *_nnz parameter is given then the *_nz parameter is ignored
1993 
1994    Storage Information:
1995    For a square global matrix we define each processor's diagonal portion
1996    to be its local rows and the corresponding columns (a square submatrix);
1997    each processor's off-diagonal portion encompasses the remainder of the
1998    local matrix (a rectangular submatrix).
1999 
2000    The user can specify preallocated storage for the diagonal part of
2001    the local submatrix with either d_nz or d_nnz (not both).  Set
2002    d_nz=PETSC_DEFAULT and d_nnz=NULL for PETSc to control dynamic
2003    memory allocation.  Likewise, specify preallocated storage for the
2004    off-diagonal part of the local submatrix with o_nz or o_nnz (not both).
2005 
2006    Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
2007    the figure below we depict these three local rows and all columns (0-11).
2008 
2009 .vb
2010            0 1 2 3 4 5 6 7 8 9 10 11
2011           --------------------------
2012    row 3  |. . . d d d o o o o  o  o
2013    row 4  |. . . d d d o o o o  o  o
2014    row 5  |. . . d d d o o o o  o  o
2015           --------------------------
2016 .ve
2017 
2018    Thus, any entries in the d locations are stored in the d (diagonal)
2019    submatrix, and any entries in the o locations are stored in the
2020    o (off-diagonal) submatrix.  Note that the d matrix is stored in
2021    MatSeqSBAIJ format and the o submatrix in MATSEQBAIJ format.
2022 
2023    Now d_nz should indicate the number of block nonzeros per row in the upper triangular
2024    plus the diagonal part of the d matrix,
2025    and o_nz should indicate the number of block nonzeros per row in the o matrix.
2026    In general, for PDE problems in which most nonzeros are near the diagonal,
2027    one expects d_nz >> o_nz.   For large problems you MUST preallocate memory
2028    or you will get TERRIBLE performance; see the users' manual chapter on
2029    matrices.
2030 
2031    Level: intermediate
2032 
2033 .keywords: matrix, block, aij, compressed row, sparse, parallel
2034 
2035 .seealso: MatCreate(), MatCreateSeqSBAIJ(), MatSetValues(), MatCreateBAIJ()
2036 @*/
2037 
2038 PetscErrorCode  MatCreateSBAIJ(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)
2039 {
2040   PetscErrorCode ierr;
2041   PetscMPIInt    size;
2042 
2043   PetscFunctionBegin;
2044   ierr = MatCreate(comm,A);CHKERRQ(ierr);
2045   ierr = MatSetSizes(*A,m,n,M,N);CHKERRQ(ierr);
2046   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
2047   if (size > 1) {
2048     ierr = MatSetType(*A,MATMPISBAIJ);CHKERRQ(ierr);
2049     ierr = MatMPISBAIJSetPreallocation(*A,bs,d_nz,d_nnz,o_nz,o_nnz);CHKERRQ(ierr);
2050   } else {
2051     ierr = MatSetType(*A,MATSEQSBAIJ);CHKERRQ(ierr);
2052     ierr = MatSeqSBAIJSetPreallocation(*A,bs,d_nz,d_nnz);CHKERRQ(ierr);
2053   }
2054   PetscFunctionReturn(0);
2055 }
2056 
2057 
2058 #undef __FUNCT__
2059 #define __FUNCT__ "MatDuplicate_MPISBAIJ"
2060 static PetscErrorCode MatDuplicate_MPISBAIJ(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
2061 {
2062   Mat            mat;
2063   Mat_MPISBAIJ   *a,*oldmat = (Mat_MPISBAIJ*)matin->data;
2064   PetscErrorCode ierr;
2065   PetscInt       len=0,nt,bs=matin->rmap->bs,mbs=oldmat->mbs;
2066   PetscScalar    *array;
2067 
2068   PetscFunctionBegin;
2069   *newmat = 0;
2070 
2071   ierr = MatCreate(PetscObjectComm((PetscObject)matin),&mat);CHKERRQ(ierr);
2072   ierr = MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);CHKERRQ(ierr);
2073   ierr = MatSetType(mat,((PetscObject)matin)->type_name);CHKERRQ(ierr);
2074   ierr = PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));CHKERRQ(ierr);
2075   ierr = PetscLayoutReference(matin->rmap,&mat->rmap);CHKERRQ(ierr);
2076   ierr = PetscLayoutReference(matin->cmap,&mat->cmap);CHKERRQ(ierr);
2077 
2078   mat->factortype   = matin->factortype;
2079   mat->preallocated = PETSC_TRUE;
2080   mat->assembled    = PETSC_TRUE;
2081   mat->insertmode   = NOT_SET_VALUES;
2082 
2083   a      = (Mat_MPISBAIJ*)mat->data;
2084   a->bs2 = oldmat->bs2;
2085   a->mbs = oldmat->mbs;
2086   a->nbs = oldmat->nbs;
2087   a->Mbs = oldmat->Mbs;
2088   a->Nbs = oldmat->Nbs;
2089 
2090 
2091   a->size         = oldmat->size;
2092   a->rank         = oldmat->rank;
2093   a->donotstash   = oldmat->donotstash;
2094   a->roworiented  = oldmat->roworiented;
2095   a->rowindices   = 0;
2096   a->rowvalues    = 0;
2097   a->getrowactive = PETSC_FALSE;
2098   a->barray       = 0;
2099   a->rstartbs     = oldmat->rstartbs;
2100   a->rendbs       = oldmat->rendbs;
2101   a->cstartbs     = oldmat->cstartbs;
2102   a->cendbs       = oldmat->cendbs;
2103 
2104   /* hash table stuff */
2105   a->ht           = 0;
2106   a->hd           = 0;
2107   a->ht_size      = 0;
2108   a->ht_flag      = oldmat->ht_flag;
2109   a->ht_fact      = oldmat->ht_fact;
2110   a->ht_total_ct  = 0;
2111   a->ht_insert_ct = 0;
2112 
2113   ierr = PetscMemcpy(a->rangebs,oldmat->rangebs,(a->size+2)*sizeof(PetscInt));CHKERRQ(ierr);
2114   if (oldmat->colmap) {
2115 #if defined(PETSC_USE_CTABLE)
2116     ierr = PetscTableCreateCopy(oldmat->colmap,&a->colmap);CHKERRQ(ierr);
2117 #else
2118     ierr = PetscMalloc1((a->Nbs),&a->colmap);CHKERRQ(ierr);
2119     ierr = PetscLogObjectMemory((PetscObject)mat,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
2120     ierr = PetscMemcpy(a->colmap,oldmat->colmap,(a->Nbs)*sizeof(PetscInt));CHKERRQ(ierr);
2121 #endif
2122   } else a->colmap = 0;
2123 
2124   if (oldmat->garray && (len = ((Mat_SeqBAIJ*)(oldmat->B->data))->nbs)) {
2125     ierr = PetscMalloc1(len,&a->garray);CHKERRQ(ierr);
2126     ierr = PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));CHKERRQ(ierr);
2127     ierr = PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt));CHKERRQ(ierr);
2128   } else a->garray = 0;
2129 
2130   ierr = MatStashCreate_Private(PetscObjectComm((PetscObject)matin),matin->rmap->bs,&mat->bstash);CHKERRQ(ierr);
2131   ierr = VecDuplicate(oldmat->lvec,&a->lvec);CHKERRQ(ierr);
2132   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);CHKERRQ(ierr);
2133   ierr = VecScatterCopy(oldmat->Mvctx,&a->Mvctx);CHKERRQ(ierr);
2134   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);CHKERRQ(ierr);
2135 
2136   ierr =  VecDuplicate(oldmat->slvec0,&a->slvec0);CHKERRQ(ierr);
2137   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr);
2138   ierr =  VecDuplicate(oldmat->slvec1,&a->slvec1);CHKERRQ(ierr);
2139   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr);
2140 
2141   ierr = VecGetLocalSize(a->slvec1,&nt);CHKERRQ(ierr);
2142   ierr = VecGetArray(a->slvec1,&array);CHKERRQ(ierr);
2143   ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,bs*mbs,array,&a->slvec1a);CHKERRQ(ierr);
2144   ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec1b);CHKERRQ(ierr);
2145   ierr = VecRestoreArray(a->slvec1,&array);CHKERRQ(ierr);
2146   ierr = VecGetArray(a->slvec0,&array);CHKERRQ(ierr);
2147   ierr = VecCreateSeqWithArray(PETSC_COMM_SELF,1,nt-bs*mbs,array+bs*mbs,&a->slvec0b);CHKERRQ(ierr);
2148   ierr = VecRestoreArray(a->slvec0,&array);CHKERRQ(ierr);
2149   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0);CHKERRQ(ierr);
2150   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1);CHKERRQ(ierr);
2151   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec0b);CHKERRQ(ierr);
2152   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1a);CHKERRQ(ierr);
2153   ierr = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->slvec1b);CHKERRQ(ierr);
2154 
2155   /* ierr =  VecScatterCopy(oldmat->sMvctx,&a->sMvctx); - not written yet, replaced by the lazy trick: */
2156   ierr      = PetscObjectReference((PetscObject)oldmat->sMvctx);CHKERRQ(ierr);
2157   a->sMvctx = oldmat->sMvctx;
2158   ierr      = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->sMvctx);CHKERRQ(ierr);
2159 
2160   ierr    =  MatDuplicate(oldmat->A,cpvalues,&a->A);CHKERRQ(ierr);
2161   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);CHKERRQ(ierr);
2162   ierr    =  MatDuplicate(oldmat->B,cpvalues,&a->B);CHKERRQ(ierr);
2163   ierr    = PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);CHKERRQ(ierr);
2164   ierr    = PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);CHKERRQ(ierr);
2165   *newmat = mat;
2166   PetscFunctionReturn(0);
2167 }
2168 
2169 #undef __FUNCT__
2170 #define __FUNCT__ "MatLoad_MPISBAIJ"
2171 PetscErrorCode MatLoad_MPISBAIJ(Mat newmat,PetscViewer viewer)
2172 {
2173   PetscErrorCode ierr;
2174   PetscInt       i,nz,j,rstart,rend;
2175   PetscScalar    *vals,*buf;
2176   MPI_Comm       comm;
2177   MPI_Status     status;
2178   PetscMPIInt    rank,size,tag = ((PetscObject)viewer)->tag,*sndcounts = 0,*browners,maxnz,*rowners,mmbs;
2179   PetscInt       header[4],*rowlengths = 0,M,N,m,*cols,*locrowlens;
2180   PetscInt       *procsnz = 0,jj,*mycols,*ibuf;
2181   PetscInt       bs       =1,Mbs,mbs,extra_rows;
2182   PetscInt       *dlens,*odlens,*mask,*masked1,*masked2,rowcount,odcount;
2183   PetscInt       dcount,kmax,k,nzcount,tmp,sizesset=1,grows,gcols;
2184   int            fd;
2185 
2186   PetscFunctionBegin;
2187   ierr = PetscObjectGetComm((PetscObject)viewer,&comm);CHKERRQ(ierr);
2188   ierr = PetscOptionsBegin(comm,NULL,"Options for loading MPISBAIJ matrix 2","Mat");CHKERRQ(ierr);
2189   ierr = PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);CHKERRQ(ierr);
2190   ierr = PetscOptionsEnd();CHKERRQ(ierr);
2191 
2192   ierr = MPI_Comm_size(comm,&size);CHKERRQ(ierr);
2193   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
2194   if (!rank) {
2195     ierr = PetscViewerBinaryGetDescriptor(viewer,&fd);CHKERRQ(ierr);
2196     ierr = PetscBinaryRead(fd,(char*)header,4,PETSC_INT);CHKERRQ(ierr);
2197     if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not matrix object");
2198     if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as MPISBAIJ");
2199   }
2200 
2201   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) sizesset = 0;
2202 
2203   ierr = MPI_Bcast(header+1,3,MPIU_INT,0,comm);CHKERRQ(ierr);
2204   M    = header[1];
2205   N    = header[2];
2206 
2207   /* If global rows/cols are set to PETSC_DECIDE, set it to the sizes given in the file */
2208   if (sizesset && newmat->rmap->N < 0) newmat->rmap->N = M;
2209   if (sizesset && newmat->cmap->N < 0) newmat->cmap->N = N;
2210 
2211   /* If global sizes are set, check if they are consistent with that given in the file */
2212   if (sizesset) {
2213     ierr = MatGetSize(newmat,&grows,&gcols);CHKERRQ(ierr);
2214   }
2215   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);
2216   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);
2217 
2218   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");
2219 
2220   /*
2221      This code adds extra rows to make sure the number of rows is
2222      divisible by the blocksize
2223   */
2224   Mbs        = M/bs;
2225   extra_rows = bs - M + bs*(Mbs);
2226   if (extra_rows == bs) extra_rows = 0;
2227   else                  Mbs++;
2228   if (extra_rows &&!rank) {
2229     ierr = PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");CHKERRQ(ierr);
2230   }
2231 
2232   /* determine ownership of all rows */
2233   if (newmat->rmap->n < 0) { /* PETSC_DECIDE */
2234     mbs = Mbs/size + ((Mbs % size) > rank);
2235     m   = mbs*bs;
2236   } else { /* User Set */
2237     m   = newmat->rmap->n;
2238     mbs = m/bs;
2239   }
2240   ierr       = PetscMalloc2(size+1,&rowners,size+1,&browners);CHKERRQ(ierr);
2241   ierr       = PetscMPIIntCast(mbs,&mmbs);CHKERRQ(ierr);
2242   ierr       = MPI_Allgather(&mmbs,1,MPI_INT,rowners+1,1,MPI_INT,comm);CHKERRQ(ierr);
2243   rowners[0] = 0;
2244   for (i=2; i<=size; i++) rowners[i] += rowners[i-1];
2245   for (i=0; i<=size; i++) browners[i] = rowners[i]*bs;
2246   rstart = rowners[rank];
2247   rend   = rowners[rank+1];
2248 
2249   /* distribute row lengths to all processors */
2250   ierr = PetscMalloc1((rend-rstart)*bs,&locrowlens);CHKERRQ(ierr);
2251   if (!rank) {
2252     ierr = PetscMalloc1((M+extra_rows),&rowlengths);CHKERRQ(ierr);
2253     ierr = PetscBinaryRead(fd,rowlengths,M,PETSC_INT);CHKERRQ(ierr);
2254     for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;
2255     ierr = PetscMalloc1(size,&sndcounts);CHKERRQ(ierr);
2256     for (i=0; i<size; i++) sndcounts[i] = browners[i+1] - browners[i];
2257     ierr = MPI_Scatterv(rowlengths,sndcounts,browners,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr);
2258     ierr = PetscFree(sndcounts);CHKERRQ(ierr);
2259   } else {
2260     ierr = MPI_Scatterv(0,0,0,MPIU_INT,locrowlens,(rend-rstart)*bs,MPIU_INT,0,comm);CHKERRQ(ierr);
2261   }
2262 
2263   if (!rank) {   /* procs[0] */
2264     /* calculate the number of nonzeros on each processor */
2265     ierr = PetscMalloc1(size,&procsnz);CHKERRQ(ierr);
2266     ierr = PetscMemzero(procsnz,size*sizeof(PetscInt));CHKERRQ(ierr);
2267     for (i=0; i<size; i++) {
2268       for (j=rowners[i]*bs; j< rowners[i+1]*bs; j++) {
2269         procsnz[i] += rowlengths[j];
2270       }
2271     }
2272     ierr = PetscFree(rowlengths);CHKERRQ(ierr);
2273 
2274     /* determine max buffer needed and allocate it */
2275     maxnz = 0;
2276     for (i=0; i<size; i++) {
2277       maxnz = PetscMax(maxnz,procsnz[i]);
2278     }
2279     ierr = PetscMalloc1(maxnz,&cols);CHKERRQ(ierr);
2280 
2281     /* read in my part of the matrix column indices  */
2282     nz     = procsnz[0];
2283     ierr   = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr);
2284     mycols = ibuf;
2285     if (size == 1) nz -= extra_rows;
2286     ierr = PetscBinaryRead(fd,mycols,nz,PETSC_INT);CHKERRQ(ierr);
2287     if (size == 1) {
2288       for (i=0; i< extra_rows; i++) mycols[nz+i] = M+i;
2289     }
2290 
2291     /* read in every ones (except the last) and ship off */
2292     for (i=1; i<size-1; i++) {
2293       nz   = procsnz[i];
2294       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
2295       ierr = MPI_Send(cols,nz,MPIU_INT,i,tag,comm);CHKERRQ(ierr);
2296     }
2297     /* read in the stuff for the last proc */
2298     if (size != 1) {
2299       nz   = procsnz[size-1] - extra_rows;  /* the extra rows are not on the disk */
2300       ierr = PetscBinaryRead(fd,cols,nz,PETSC_INT);CHKERRQ(ierr);
2301       for (i=0; i<extra_rows; i++) cols[nz+i] = M+i;
2302       ierr = MPI_Send(cols,nz+extra_rows,MPIU_INT,size-1,tag,comm);CHKERRQ(ierr);
2303     }
2304     ierr = PetscFree(cols);CHKERRQ(ierr);
2305   } else {  /* procs[i], i>0 */
2306     /* determine buffer space needed for message */
2307     nz = 0;
2308     for (i=0; i<m; i++) nz += locrowlens[i];
2309     ierr   = PetscMalloc1(nz,&ibuf);CHKERRQ(ierr);
2310     mycols = ibuf;
2311     /* receive message of column indices*/
2312     ierr = MPI_Recv(mycols,nz,MPIU_INT,0,tag,comm,&status);CHKERRQ(ierr);
2313     ierr = MPI_Get_count(&status,MPIU_INT,&maxnz);CHKERRQ(ierr);
2314     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2315   }
2316 
2317   /* loop over local rows, determining number of off diagonal entries */
2318   ierr     = PetscMalloc2(rend-rstart,&dlens,rend-rstart,&odlens);CHKERRQ(ierr);
2319   ierr     = PetscMalloc3(Mbs,&mask,Mbs,&masked1,Mbs,&masked2);CHKERRQ(ierr);
2320   ierr     = PetscMemzero(mask,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
2321   ierr     = PetscMemzero(masked1,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
2322   ierr     = PetscMemzero(masked2,Mbs*sizeof(PetscInt));CHKERRQ(ierr);
2323   rowcount = 0;
2324   nzcount  = 0;
2325   for (i=0; i<mbs; i++) {
2326     dcount  = 0;
2327     odcount = 0;
2328     for (j=0; j<bs; j++) {
2329       kmax = locrowlens[rowcount];
2330       for (k=0; k<kmax; k++) {
2331         tmp = mycols[nzcount++]/bs; /* block col. index */
2332         if (!mask[tmp]) {
2333           mask[tmp] = 1;
2334           if (tmp < rstart || tmp >= rend) masked2[odcount++] = tmp; /* entry in off-diag portion */
2335           else masked1[dcount++] = tmp; /* entry in diag portion */
2336         }
2337       }
2338       rowcount++;
2339     }
2340 
2341     dlens[i]  = dcount;  /* d_nzz[i] */
2342     odlens[i] = odcount; /* o_nzz[i] */
2343 
2344     /* zero out the mask elements we set */
2345     for (j=0; j<dcount; j++) mask[masked1[j]] = 0;
2346     for (j=0; j<odcount; j++) mask[masked2[j]] = 0;
2347   }
2348   if (!sizesset) {
2349     ierr = MatSetSizes(newmat,m,m,M+extra_rows,N+extra_rows);CHKERRQ(ierr);
2350   }
2351   ierr = MatMPISBAIJSetPreallocation(newmat,bs,0,dlens,0,odlens);CHKERRQ(ierr);
2352   ierr = MatSetOption(newmat,MAT_IGNORE_LOWER_TRIANGULAR,PETSC_TRUE);CHKERRQ(ierr);
2353 
2354   if (!rank) {
2355     ierr = PetscMalloc1(maxnz,&buf);CHKERRQ(ierr);
2356     /* read in my part of the matrix numerical values  */
2357     nz     = procsnz[0];
2358     vals   = buf;
2359     mycols = ibuf;
2360     if (size == 1) nz -= extra_rows;
2361     ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
2362     if (size == 1) {
2363       for (i=0; i< extra_rows; i++) vals[nz+i] = 1.0;
2364     }
2365 
2366     /* insert into matrix */
2367     jj = rstart*bs;
2368     for (i=0; i<m; i++) {
2369       ierr    = MatSetValues(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
2370       mycols += locrowlens[i];
2371       vals   += locrowlens[i];
2372       jj++;
2373     }
2374 
2375     /* read in other processors (except the last one) and ship out */
2376     for (i=1; i<size-1; i++) {
2377       nz   = procsnz[i];
2378       vals = buf;
2379       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
2380       ierr = MPI_Send(vals,nz,MPIU_SCALAR,i,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
2381     }
2382     /* the last proc */
2383     if (size != 1) {
2384       nz   = procsnz[i] - extra_rows;
2385       vals = buf;
2386       ierr = PetscBinaryRead(fd,vals,nz,PETSC_SCALAR);CHKERRQ(ierr);
2387       for (i=0; i<extra_rows; i++) vals[nz+i] = 1.0;
2388       ierr = MPI_Send(vals,nz+extra_rows,MPIU_SCALAR,size-1,((PetscObject)newmat)->tag,comm);CHKERRQ(ierr);
2389     }
2390     ierr = PetscFree(procsnz);CHKERRQ(ierr);
2391 
2392   } else {
2393     /* receive numeric values */
2394     ierr = PetscMalloc1(nz,&buf);CHKERRQ(ierr);
2395 
2396     /* receive message of values*/
2397     vals   = buf;
2398     mycols = ibuf;
2399     ierr   = MPI_Recv(vals,nz,MPIU_SCALAR,0,((PetscObject)newmat)->tag,comm,&status);CHKERRQ(ierr);
2400     ierr   = MPI_Get_count(&status,MPIU_SCALAR,&maxnz);CHKERRQ(ierr);
2401     if (maxnz != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"something is wrong with file");
2402 
2403     /* insert into matrix */
2404     jj = rstart*bs;
2405     for (i=0; i<m; i++) {
2406       ierr    = MatSetValues_MPISBAIJ(newmat,1,&jj,locrowlens[i],mycols,vals,INSERT_VALUES);CHKERRQ(ierr);
2407       mycols += locrowlens[i];
2408       vals   += locrowlens[i];
2409       jj++;
2410     }
2411   }
2412 
2413   ierr = PetscFree(locrowlens);CHKERRQ(ierr);
2414   ierr = PetscFree(buf);CHKERRQ(ierr);
2415   ierr = PetscFree(ibuf);CHKERRQ(ierr);
2416   ierr = PetscFree2(rowners,browners);CHKERRQ(ierr);
2417   ierr = PetscFree2(dlens,odlens);CHKERRQ(ierr);
2418   ierr = PetscFree3(mask,masked1,masked2);CHKERRQ(ierr);
2419   ierr = MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2420   ierr = MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
2421   PetscFunctionReturn(0);
2422 }
2423 
2424 #undef __FUNCT__
2425 #define __FUNCT__ "MatMPISBAIJSetHashTableFactor"
2426 /*XXXXX@
2427    MatMPISBAIJSetHashTableFactor - Sets the factor required to compute the size of the HashTable.
2428 
2429    Input Parameters:
2430 .  mat  - the matrix
2431 .  fact - factor
2432 
2433    Not Collective on Mat, each process can have a different hash factor
2434 
2435    Level: advanced
2436 
2437   Notes:
2438    This can also be set by the command line option: -mat_use_hash_table fact
2439 
2440 .keywords: matrix, hashtable, factor, HT
2441 
2442 .seealso: MatSetOption()
2443 @XXXXX*/
2444 
2445 
2446 #undef __FUNCT__
2447 #define __FUNCT__ "MatGetRowMaxAbs_MPISBAIJ"
2448 PetscErrorCode MatGetRowMaxAbs_MPISBAIJ(Mat A,Vec v,PetscInt idx[])
2449 {
2450   Mat_MPISBAIJ   *a = (Mat_MPISBAIJ*)A->data;
2451   Mat_SeqBAIJ    *b = (Mat_SeqBAIJ*)(a->B)->data;
2452   PetscReal      atmp;
2453   PetscReal      *work,*svalues,*rvalues;
2454   PetscErrorCode ierr;
2455   PetscInt       i,bs,mbs,*bi,*bj,brow,j,ncols,krow,kcol,col,row,Mbs,bcol;
2456   PetscMPIInt    rank,size;
2457   PetscInt       *rowners_bs,dest,count,source;
2458   PetscScalar    *va;
2459   MatScalar      *ba;
2460   MPI_Status     stat;
2461 
2462   PetscFunctionBegin;
2463   if (idx) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Send email to petsc-maint@mcs.anl.gov");
2464   ierr = MatGetRowMaxAbs(a->A,v,NULL);CHKERRQ(ierr);
2465   ierr = VecGetArray(v,&va);CHKERRQ(ierr);
2466 
2467   ierr = MPI_Comm_size(PetscObjectComm((PetscObject)A),&size);CHKERRQ(ierr);
2468   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)A),&rank);CHKERRQ(ierr);
2469 
2470   bs  = A->rmap->bs;
2471   mbs = a->mbs;
2472   Mbs = a->Mbs;
2473   ba  = b->a;
2474   bi  = b->i;
2475   bj  = b->j;
2476 
2477   /* find ownerships */
2478   rowners_bs = A->rmap->range;
2479 
2480   /* each proc creates an array to be distributed */
2481   ierr = PetscMalloc1(bs*Mbs,&work);CHKERRQ(ierr);
2482   ierr = PetscMemzero(work,bs*Mbs*sizeof(PetscReal));CHKERRQ(ierr);
2483 
2484   /* row_max for B */
2485   if (rank != size-1) {
2486     for (i=0; i<mbs; i++) {
2487       ncols = bi[1] - bi[0]; bi++;
2488       brow  = bs*i;
2489       for (j=0; j<ncols; j++) {
2490         bcol = bs*(*bj);
2491         for (kcol=0; kcol<bs; kcol++) {
2492           col  = bcol + kcol;                /* local col index */
2493           col += rowners_bs[rank+1];      /* global col index */
2494           for (krow=0; krow<bs; krow++) {
2495             atmp = PetscAbsScalar(*ba); ba++;
2496             row  = brow + krow;   /* local row index */
2497             if (PetscRealPart(va[row]) < atmp) va[row] = atmp;
2498             if (work[col] < atmp) work[col] = atmp;
2499           }
2500         }
2501         bj++;
2502       }
2503     }
2504 
2505     /* send values to its owners */
2506     for (dest=rank+1; dest<size; dest++) {
2507       svalues = work + rowners_bs[dest];
2508       count   = rowners_bs[dest+1]-rowners_bs[dest];
2509       ierr    = MPI_Send(svalues,count,MPIU_REAL,dest,rank,PetscObjectComm((PetscObject)A));CHKERRQ(ierr);
2510     }
2511   }
2512 
2513   /* receive values */
2514   if (rank) {
2515     rvalues = work;
2516     count   = rowners_bs[rank+1]-rowners_bs[rank];
2517     for (source=0; source<rank; source++) {
2518       ierr = MPI_Recv(rvalues,count,MPIU_REAL,MPI_ANY_SOURCE,MPI_ANY_TAG,PetscObjectComm((PetscObject)A),&stat);CHKERRQ(ierr);
2519       /* process values */
2520       for (i=0; i<count; i++) {
2521         if (PetscRealPart(va[i]) < rvalues[i]) va[i] = rvalues[i];
2522       }
2523     }
2524   }
2525 
2526   ierr = VecRestoreArray(v,&va);CHKERRQ(ierr);
2527   ierr = PetscFree(work);CHKERRQ(ierr);
2528   PetscFunctionReturn(0);
2529 }
2530 
2531 #undef __FUNCT__
2532 #define __FUNCT__ "MatSOR_MPISBAIJ"
2533 PetscErrorCode MatSOR_MPISBAIJ(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2534 {
2535   Mat_MPISBAIJ      *mat = (Mat_MPISBAIJ*)matin->data;
2536   PetscErrorCode    ierr;
2537   PetscInt          mbs=mat->mbs,bs=matin->rmap->bs;
2538   PetscScalar       *x,*ptr,*from;
2539   Vec               bb1;
2540   const PetscScalar *b;
2541 
2542   PetscFunctionBegin;
2543   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
2544   if (bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");
2545 
2546   if (flag == SOR_APPLY_UPPER) {
2547     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2548     PetscFunctionReturn(0);
2549   }
2550 
2551   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2552     if (flag & SOR_ZERO_INITIAL_GUESS) {
2553       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr);
2554       its--;
2555     }
2556 
2557     ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr);
2558     while (its--) {
2559 
2560       /* lower triangular part: slvec0b = - B^T*xx */
2561       ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr);
2562 
2563       /* copy xx into slvec0a */
2564       ierr = VecGetArray(mat->slvec0,&ptr);CHKERRQ(ierr);
2565       ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
2566       ierr = PetscMemcpy(ptr,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr);
2567       ierr = VecRestoreArray(mat->slvec0,&ptr);CHKERRQ(ierr);
2568 
2569       ierr = VecScale(mat->slvec0,-1.0);CHKERRQ(ierr);
2570 
2571       /* copy bb into slvec1a */
2572       ierr = VecGetArray(mat->slvec1,&ptr);CHKERRQ(ierr);
2573       ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr);
2574       ierr = PetscMemcpy(ptr,b,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr);
2575       ierr = VecRestoreArray(mat->slvec1,&ptr);CHKERRQ(ierr);
2576 
2577       /* set slvec1b = 0 */
2578       ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr);
2579 
2580       ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2581       ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
2582       ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr);
2583       ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2584 
2585       /* upper triangular part: bb1 = bb1 - B*x */
2586       ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,bb1);CHKERRQ(ierr);
2587 
2588       /* local diagonal sweep */
2589       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr);
2590     }
2591     ierr = VecDestroy(&bb1);CHKERRQ(ierr);
2592   } else if ((flag & SOR_LOCAL_FORWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2593     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2594   } else if ((flag & SOR_LOCAL_BACKWARD_SWEEP) && (its == 1) && (flag & SOR_ZERO_INITIAL_GUESS)) {
2595     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);CHKERRQ(ierr);
2596   } else if (flag & SOR_EISENSTAT) {
2597     Vec               xx1;
2598     PetscBool         hasop;
2599     const PetscScalar *diag;
2600     PetscScalar       *sl,scale = (omega - 2.0)/omega;
2601     PetscInt          i,n;
2602 
2603     if (!mat->xx1) {
2604       ierr = VecDuplicate(bb,&mat->xx1);CHKERRQ(ierr);
2605       ierr = VecDuplicate(bb,&mat->bb1);CHKERRQ(ierr);
2606     }
2607     xx1 = mat->xx1;
2608     bb1 = mat->bb1;
2609 
2610     ierr = (*mat->A->ops->sor)(mat->A,bb,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_BACKWARD_SWEEP),fshift,lits,1,xx);CHKERRQ(ierr);
2611 
2612     if (!mat->diag) {
2613       /* this is wrong for same matrix with new nonzero values */
2614       ierr = MatGetVecs(matin,&mat->diag,NULL);CHKERRQ(ierr);
2615       ierr = MatGetDiagonal(matin,mat->diag);CHKERRQ(ierr);
2616     }
2617     ierr = MatHasOperation(matin,MATOP_MULT_DIAGONAL_BLOCK,&hasop);CHKERRQ(ierr);
2618 
2619     if (hasop) {
2620       ierr = MatMultDiagonalBlock(matin,xx,bb1);CHKERRQ(ierr);
2621       ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr);
2622     } else {
2623       /*
2624           These two lines are replaced by code that may be a bit faster for a good compiler
2625       ierr = VecPointwiseMult(mat->slvec1a,mat->diag,xx);CHKERRQ(ierr);
2626       ierr = VecAYPX(mat->slvec1a,scale,bb);CHKERRQ(ierr);
2627       */
2628       ierr = VecGetArray(mat->slvec1a,&sl);CHKERRQ(ierr);
2629       ierr = VecGetArrayRead(mat->diag,&diag);CHKERRQ(ierr);
2630       ierr = VecGetArrayRead(bb,&b);CHKERRQ(ierr);
2631       ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
2632       ierr = VecGetLocalSize(xx,&n);CHKERRQ(ierr);
2633       if (omega == 1.0) {
2634         for (i=0; i<n; i++) sl[i] = b[i] - diag[i]*x[i];
2635         ierr = PetscLogFlops(2.0*n);CHKERRQ(ierr);
2636       } else {
2637         for (i=0; i<n; i++) sl[i] = b[i] + scale*diag[i]*x[i];
2638         ierr = PetscLogFlops(3.0*n);CHKERRQ(ierr);
2639       }
2640       ierr = VecRestoreArray(mat->slvec1a,&sl);CHKERRQ(ierr);
2641       ierr = VecRestoreArrayRead(mat->diag,&diag);CHKERRQ(ierr);
2642       ierr = VecRestoreArrayRead(bb,&b);CHKERRQ(ierr);
2643       ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
2644     }
2645 
2646     /* multiply off-diagonal portion of matrix */
2647     ierr = VecSet(mat->slvec1b,0.0);CHKERRQ(ierr);
2648     ierr = (*mat->B->ops->multtranspose)(mat->B,xx,mat->slvec0b);CHKERRQ(ierr);
2649     ierr = VecGetArray(mat->slvec0,&from);CHKERRQ(ierr);
2650     ierr = VecGetArray(xx,&x);CHKERRQ(ierr);
2651     ierr = PetscMemcpy(from,x,bs*mbs*sizeof(MatScalar));CHKERRQ(ierr);
2652     ierr = VecRestoreArray(mat->slvec0,&from);CHKERRQ(ierr);
2653     ierr = VecRestoreArray(xx,&x);CHKERRQ(ierr);
2654     ierr = VecScatterBegin(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2655     ierr = VecScatterEnd(mat->sMvctx,mat->slvec0,mat->slvec1,ADD_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2656     ierr = (*mat->B->ops->multadd)(mat->B,mat->slvec1b,mat->slvec1a,mat->slvec1a);CHKERRQ(ierr);
2657 
2658     /* local sweep */
2659     ierr = (*mat->A->ops->sor)(mat->A,mat->slvec1a,omega,(MatSORType)(SOR_ZERO_INITIAL_GUESS | SOR_LOCAL_FORWARD_SWEEP),fshift,lits,1,xx1);CHKERRQ(ierr);
2660     ierr = VecAXPY(xx,1.0,xx1);CHKERRQ(ierr);
2661   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2662   PetscFunctionReturn(0);
2663 }
2664 
2665 #undef __FUNCT__
2666 #define __FUNCT__ "MatSOR_MPISBAIJ_2comm"
2667 PetscErrorCode MatSOR_MPISBAIJ_2comm(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
2668 {
2669   Mat_MPISBAIJ   *mat = (Mat_MPISBAIJ*)matin->data;
2670   PetscErrorCode ierr;
2671   Vec            lvec1,bb1;
2672 
2673   PetscFunctionBegin;
2674   if (its <= 0 || lits <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
2675   if (matin->rmap->bs > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"SSOR for block size > 1 is not yet implemented");
2676 
2677   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2678     if (flag & SOR_ZERO_INITIAL_GUESS) {
2679       ierr = (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,lits,xx);CHKERRQ(ierr);
2680       its--;
2681     }
2682 
2683     ierr = VecDuplicate(mat->lvec,&lvec1);CHKERRQ(ierr);
2684     ierr = VecDuplicate(bb,&bb1);CHKERRQ(ierr);
2685     while (its--) {
2686       ierr = VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2687 
2688       /* lower diagonal part: bb1 = bb - B^T*xx */
2689       ierr = (*mat->B->ops->multtranspose)(mat->B,xx,lvec1);CHKERRQ(ierr);
2690       ierr = VecScale(lvec1,-1.0);CHKERRQ(ierr);
2691 
2692       ierr = VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
2693       ierr = VecCopy(bb,bb1);CHKERRQ(ierr);
2694       ierr = VecScatterBegin(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
2695 
2696       /* upper diagonal part: bb1 = bb1 - B*x */
2697       ierr = VecScale(mat->lvec,-1.0);CHKERRQ(ierr);
2698       ierr = (*mat->B->ops->multadd)(mat->B,mat->lvec,bb1,bb1);CHKERRQ(ierr);
2699 
2700       ierr = VecScatterEnd(mat->Mvctx,lvec1,bb1,ADD_VALUES,SCATTER_REVERSE);CHKERRQ(ierr);
2701 
2702       /* diagonal sweep */
2703       ierr = (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,lits,xx);CHKERRQ(ierr);
2704     }
2705     ierr = VecDestroy(&lvec1);CHKERRQ(ierr);
2706     ierr = VecDestroy(&bb1);CHKERRQ(ierr);
2707   } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatSORType is not supported for SBAIJ matrix format");
2708   PetscFunctionReturn(0);
2709 }
2710 
2711 #undef __FUNCT__
2712 #define __FUNCT__ "MatCreateMPISBAIJWithArrays"
2713 /*@
2714      MatCreateMPISBAIJWithArrays - creates a MPI SBAIJ matrix using arrays that contain in standard
2715          CSR format the local rows.
2716 
2717    Collective on MPI_Comm
2718 
2719    Input Parameters:
2720 +  comm - MPI communicator
2721 .  bs - the block size, only a block size of 1 is supported
2722 .  m - number of local rows (Cannot be PETSC_DECIDE)
2723 .  n - This value should be the same as the local size used in creating the
2724        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
2725        calculated if N is given) For square matrices n is almost always m.
2726 .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
2727 .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
2728 .   i - row indices
2729 .   j - column indices
2730 -   a - matrix values
2731 
2732    Output Parameter:
2733 .   mat - the matrix
2734 
2735    Level: intermediate
2736 
2737    Notes:
2738        The i, j, and a arrays ARE copied by this routine into the internal format used by PETSc;
2739      thus you CANNOT change the matrix entries by changing the values of a[] after you have
2740      called this routine. Use MatCreateMPIAIJWithSplitArrays() to avoid needing to copy the arrays.
2741 
2742        The i and j indices are 0 based, and i indices are indices corresponding to the local j array.
2743 
2744 .keywords: matrix, aij, compressed row, sparse, parallel
2745 
2746 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIAIJSetPreallocation(), MatMPIAIJSetPreallocationCSR(),
2747           MPIAIJ, MatCreateAIJ(), MatCreateMPIAIJWithSplitArrays()
2748 @*/
2749 PetscErrorCode  MatCreateMPISBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt M,PetscInt N,const PetscInt i[],const PetscInt j[],const PetscScalar a[],Mat *mat)
2750 {
2751   PetscErrorCode ierr;
2752 
2753 
2754   PetscFunctionBegin;
2755   if (i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");
2756   if (m < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"local number of rows (m) cannot be PETSC_DECIDE, or negative");
2757   ierr = MatCreate(comm,mat);CHKERRQ(ierr);
2758   ierr = MatSetSizes(*mat,m,n,M,N);CHKERRQ(ierr);
2759   ierr = MatSetType(*mat,MATMPISBAIJ);CHKERRQ(ierr);
2760   ierr = MatMPISBAIJSetPreallocationCSR(*mat,bs,i,j,a);CHKERRQ(ierr);
2761   PetscFunctionReturn(0);
2762 }
2763 
2764 
2765 #undef __FUNCT__
2766 #define __FUNCT__ "MatMPISBAIJSetPreallocationCSR"
2767 /*@C
2768    MatMPISBAIJSetPreallocationCSR - Allocates memory for a sparse parallel matrix in BAIJ format
2769    (the default parallel PETSc format).
2770 
2771    Collective on MPI_Comm
2772 
2773    Input Parameters:
2774 +  A - the matrix
2775 .  bs - the block size
2776 .  i - the indices into j for the start of each local row (starts with zero)
2777 .  j - the column indices for each local row (starts with zero) these must be sorted for each row
2778 -  v - optional values in the matrix
2779 
2780    Level: developer
2781 
2782 .keywords: matrix, aij, compressed row, sparse, parallel
2783 
2784 .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatMPIBAIJSetPreallocation(), MatCreateAIJ(), MPIAIJ
2785 @*/
2786 PetscErrorCode  MatMPISBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
2787 {
2788   PetscErrorCode ierr;
2789 
2790   PetscFunctionBegin;
2791   ierr = PetscTryMethod(B,"MatMPISBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));CHKERRQ(ierr);
2792   PetscFunctionReturn(0);
2793 }
2794 
2795 
2796