xref: /petsc/src/mat/impls/baij/mpi/mpibaij.c (revision 83d0d507e8eaf8d844b49c5dbd0d8d7c8cefa37b)
1 #include <../src/mat/impls/baij/mpi/mpibaij.h> /*I  "petscmat.h"  I*/
2 
3 #include <petsc/private/hashseti.h>
4 #include <petscblaslapack.h>
5 #include <petscsf.h>
6 
7 static PetscErrorCode MatDestroy_MPIBAIJ(Mat mat)
8 {
9   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
10 
11   PetscFunctionBegin;
12   PetscCall(PetscLogObjectState((PetscObject)mat, "Rows=%" PetscInt_FMT ",Cols=%" PetscInt_FMT, mat->rmap->N, mat->cmap->N));
13   PetscCall(MatStashDestroy_Private(&mat->stash));
14   PetscCall(MatStashDestroy_Private(&mat->bstash));
15   PetscCall(MatDestroy(&baij->A));
16   PetscCall(MatDestroy(&baij->B));
17 #if defined(PETSC_USE_CTABLE)
18   PetscCall(PetscHMapIDestroy(&baij->colmap));
19 #else
20   PetscCall(PetscFree(baij->colmap));
21 #endif
22   PetscCall(PetscFree(baij->garray));
23   PetscCall(VecDestroy(&baij->lvec));
24   PetscCall(VecScatterDestroy(&baij->Mvctx));
25   PetscCall(PetscFree2(baij->rowvalues, baij->rowindices));
26   PetscCall(PetscFree(baij->barray));
27   PetscCall(PetscFree2(baij->hd, baij->ht));
28   PetscCall(PetscFree(baij->rangebs));
29   PetscCall(PetscFree(mat->data));
30 
31   PetscCall(PetscObjectChangeTypeName((PetscObject)mat, NULL));
32   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatStoreValues_C", NULL));
33   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatRetrieveValues_C", NULL));
34   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPIBAIJSetPreallocation_C", NULL));
35   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatMPIBAIJSetPreallocationCSR_C", NULL));
36   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatDiagonalScaleLocal_C", NULL));
37   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatSetHashTableFactor_C", NULL));
38   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpibaij_mpisbaij_C", NULL));
39   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpibaij_mpiadj_C", NULL));
40   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpibaij_mpiaij_C", NULL));
41 #if defined(PETSC_HAVE_HYPRE)
42   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpibaij_hypre_C", NULL));
43 #endif
44   PetscCall(PetscObjectComposeFunction((PetscObject)mat, "MatConvert_mpibaij_is_C", NULL));
45   PetscFunctionReturn(PETSC_SUCCESS);
46 }
47 
48 /* defines MatSetValues_MPI_Hash(), MatAssemblyBegin_MPI_Hash(), and  MatAssemblyEnd_MPI_Hash() */
49 #define TYPE BAIJ
50 #include "../src/mat/impls/aij/mpi/mpihashmat.h"
51 #undef TYPE
52 
53 #if defined(PETSC_HAVE_HYPRE)
54 PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat, MatType, MatReuse, Mat *);
55 #endif
56 
57 static PetscErrorCode MatGetRowMaxAbs_MPIBAIJ(Mat A, Vec v, PetscInt idx[])
58 {
59   Mat_MPIBAIJ       *a = (Mat_MPIBAIJ *)A->data;
60   PetscInt           i, *idxb = NULL, m = A->rmap->n, bs = A->cmap->bs;
61   PetscScalar       *va, *vv;
62   Vec                vB, vA;
63   const PetscScalar *vb;
64 
65   PetscFunctionBegin;
66   PetscCall(MatCreateVecs(a->A, NULL, &vA));
67   PetscCall(MatGetRowMaxAbs(a->A, vA, idx));
68 
69   PetscCall(VecGetArrayWrite(vA, &va));
70   if (idx) {
71     for (i = 0; i < m; i++) {
72       if (PetscAbsScalar(va[i])) idx[i] += A->cmap->rstart;
73     }
74   }
75 
76   PetscCall(MatCreateVecs(a->B, NULL, &vB));
77   PetscCall(PetscMalloc1(m, &idxb));
78   PetscCall(MatGetRowMaxAbs(a->B, vB, idxb));
79 
80   PetscCall(VecGetArrayWrite(v, &vv));
81   PetscCall(VecGetArrayRead(vB, &vb));
82   for (i = 0; i < m; i++) {
83     if (PetscAbsScalar(va[i]) < PetscAbsScalar(vb[i])) {
84       vv[i] = vb[i];
85       if (idx) idx[i] = bs * a->garray[idxb[i] / bs] + (idxb[i] % bs);
86     } else {
87       vv[i] = va[i];
88       if (idx && PetscAbsScalar(va[i]) == PetscAbsScalar(vb[i]) && idxb[i] != -1 && idx[i] > bs * a->garray[idxb[i] / bs] + (idxb[i] % bs)) idx[i] = bs * a->garray[idxb[i] / bs] + (idxb[i] % bs);
89     }
90   }
91   PetscCall(VecRestoreArrayWrite(vA, &vv));
92   PetscCall(VecRestoreArrayWrite(vA, &va));
93   PetscCall(VecRestoreArrayRead(vB, &vb));
94   PetscCall(PetscFree(idxb));
95   PetscCall(VecDestroy(&vA));
96   PetscCall(VecDestroy(&vB));
97   PetscFunctionReturn(PETSC_SUCCESS);
98 }
99 
100 static PetscErrorCode MatGetRowSumAbs_MPIBAIJ(Mat A, Vec v)
101 {
102   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
103   Vec          vB, vA;
104 
105   PetscFunctionBegin;
106   PetscCall(MatCreateVecs(a->A, NULL, &vA));
107   PetscCall(MatGetRowSumAbs(a->A, vA));
108   PetscCall(MatCreateVecs(a->B, NULL, &vB));
109   PetscCall(MatGetRowSumAbs(a->B, vB));
110   PetscCall(VecAXPY(vA, 1.0, vB));
111   PetscCall(VecDestroy(&vB));
112   PetscCall(VecCopy(vA, v));
113   PetscCall(VecDestroy(&vA));
114   PetscFunctionReturn(PETSC_SUCCESS);
115 }
116 
117 static PetscErrorCode MatStoreValues_MPIBAIJ(Mat mat)
118 {
119   Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data;
120 
121   PetscFunctionBegin;
122   PetscCall(MatStoreValues(aij->A));
123   PetscCall(MatStoreValues(aij->B));
124   PetscFunctionReturn(PETSC_SUCCESS);
125 }
126 
127 static PetscErrorCode MatRetrieveValues_MPIBAIJ(Mat mat)
128 {
129   Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)mat->data;
130 
131   PetscFunctionBegin;
132   PetscCall(MatRetrieveValues(aij->A));
133   PetscCall(MatRetrieveValues(aij->B));
134   PetscFunctionReturn(PETSC_SUCCESS);
135 }
136 
137 /*
138      Local utility routine that creates a mapping from the global column
139    number to the local number in the off-diagonal part of the local
140    storage of the matrix.  This is done in a non scalable way since the
141    length of colmap equals the global matrix length.
142 */
143 PetscErrorCode MatCreateColmap_MPIBAIJ_Private(Mat mat)
144 {
145   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
146   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ *)baij->B->data;
147   PetscInt     nbs = B->nbs, i, bs = mat->rmap->bs;
148 
149   PetscFunctionBegin;
150 #if defined(PETSC_USE_CTABLE)
151   PetscCall(PetscHMapICreateWithSize(baij->nbs, &baij->colmap));
152   for (i = 0; i < nbs; i++) PetscCall(PetscHMapISet(baij->colmap, baij->garray[i] + 1, i * bs + 1));
153 #else
154   PetscCall(PetscCalloc1(baij->Nbs + 1, &baij->colmap));
155   for (i = 0; i < nbs; i++) baij->colmap[baij->garray[i]] = i * bs + 1;
156 #endif
157   PetscFunctionReturn(PETSC_SUCCESS);
158 }
159 
160 #define MatSetValues_SeqBAIJ_A_Private(row, col, value, addv, orow, ocol) \
161   do { \
162     brow = row / bs; \
163     rp   = PetscSafePointerPlusOffset(aj, ai[brow]); \
164     ap   = PetscSafePointerPlusOffset(aa, bs2 * ai[brow]); \
165     rmax = aimax[brow]; \
166     nrow = ailen[brow]; \
167     bcol = col / bs; \
168     ridx = row % bs; \
169     cidx = col % bs; \
170     low  = 0; \
171     high = nrow; \
172     while (high - low > 3) { \
173       t = (low + high) / 2; \
174       if (rp[t] > bcol) high = t; \
175       else low = t; \
176     } \
177     for (_i = low; _i < high; _i++) { \
178       if (rp[_i] > bcol) break; \
179       if (rp[_i] == bcol) { \
180         bap = ap + bs2 * _i + bs * cidx + ridx; \
181         if (addv == ADD_VALUES) *bap += value; \
182         else *bap = value; \
183         goto a_noinsert; \
184       } \
185     } \
186     if (a->nonew == 1) goto a_noinsert; \
187     PetscCheck(a->nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", orow, ocol); \
188     MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, brow, bcol, rmax, aa, ai, aj, rp, ap, aimax, a->nonew, MatScalar); \
189     N = nrow++ - 1; \
190     /* shift up all the later entries in this row */ \
191     PetscCall(PetscArraymove(rp + _i + 1, rp + _i, N - _i + 1)); \
192     PetscCall(PetscArraymove(ap + bs2 * (_i + 1), ap + bs2 * _i, bs2 * (N - _i + 1))); \
193     PetscCall(PetscArrayzero(ap + bs2 * _i, bs2)); \
194     rp[_i]                          = bcol; \
195     ap[bs2 * _i + bs * cidx + ridx] = value; \
196   a_noinsert:; \
197     ailen[brow] = nrow; \
198   } while (0)
199 
200 #define MatSetValues_SeqBAIJ_B_Private(row, col, value, addv, orow, ocol) \
201   do { \
202     brow = row / bs; \
203     rp   = PetscSafePointerPlusOffset(bj, bi[brow]); \
204     ap   = PetscSafePointerPlusOffset(ba, bs2 * bi[brow]); \
205     rmax = bimax[brow]; \
206     nrow = bilen[brow]; \
207     bcol = col / bs; \
208     ridx = row % bs; \
209     cidx = col % bs; \
210     low  = 0; \
211     high = nrow; \
212     while (high - low > 3) { \
213       t = (low + high) / 2; \
214       if (rp[t] > bcol) high = t; \
215       else low = t; \
216     } \
217     for (_i = low; _i < high; _i++) { \
218       if (rp[_i] > bcol) break; \
219       if (rp[_i] == bcol) { \
220         bap = ap + bs2 * _i + bs * cidx + ridx; \
221         if (addv == ADD_VALUES) *bap += value; \
222         else *bap = value; \
223         goto b_noinsert; \
224       } \
225     } \
226     if (b->nonew == 1) goto b_noinsert; \
227     PetscCheck(b->nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero at global row/column  (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", orow, ocol); \
228     MatSeqXAIJReallocateAIJ(B, b->mbs, bs2, nrow, brow, bcol, rmax, ba, bi, bj, rp, ap, bimax, b->nonew, MatScalar); \
229     N = nrow++ - 1; \
230     /* shift up all the later entries in this row */ \
231     PetscCall(PetscArraymove(rp + _i + 1, rp + _i, N - _i + 1)); \
232     PetscCall(PetscArraymove(ap + bs2 * (_i + 1), ap + bs2 * _i, bs2 * (N - _i + 1))); \
233     PetscCall(PetscArrayzero(ap + bs2 * _i, bs2)); \
234     rp[_i]                          = bcol; \
235     ap[bs2 * _i + bs * cidx + ridx] = value; \
236   b_noinsert:; \
237     bilen[brow] = nrow; \
238   } while (0)
239 
240 PetscErrorCode MatSetValues_MPIBAIJ(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv)
241 {
242   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
243   MatScalar    value;
244   PetscBool    roworiented = baij->roworiented;
245   PetscInt     i, j, row, col;
246   PetscInt     rstart_orig = mat->rmap->rstart;
247   PetscInt     rend_orig = mat->rmap->rend, cstart_orig = mat->cmap->rstart;
248   PetscInt     cend_orig = mat->cmap->rend, bs = mat->rmap->bs;
249 
250   /* Some Variables required in the macro */
251   Mat          A     = baij->A;
252   Mat_SeqBAIJ *a     = (Mat_SeqBAIJ *)(A)->data;
253   PetscInt    *aimax = a->imax, *ai = a->i, *ailen = a->ilen, *aj = a->j;
254   MatScalar   *aa = a->a;
255 
256   Mat          B     = baij->B;
257   Mat_SeqBAIJ *b     = (Mat_SeqBAIJ *)(B)->data;
258   PetscInt    *bimax = b->imax, *bi = b->i, *bilen = b->ilen, *bj = b->j;
259   MatScalar   *ba = b->a;
260 
261   PetscInt  *rp, ii, nrow, _i, rmax, N, brow, bcol;
262   PetscInt   low, high, t, ridx, cidx, bs2 = a->bs2;
263   MatScalar *ap, *bap;
264 
265   PetscFunctionBegin;
266   for (i = 0; i < m; i++) {
267     if (im[i] < 0) continue;
268     PetscCheck(im[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, im[i], mat->rmap->N - 1);
269     if (im[i] >= rstart_orig && im[i] < rend_orig) {
270       row = im[i] - rstart_orig;
271       for (j = 0; j < n; j++) {
272         if (in[j] >= cstart_orig && in[j] < cend_orig) {
273           col = in[j] - cstart_orig;
274           if (roworiented) value = v[i * n + j];
275           else value = v[i + j * m];
276           MatSetValues_SeqBAIJ_A_Private(row, col, value, addv, im[i], in[j]);
277         } else if (in[j] < 0) {
278           continue;
279         } else {
280           PetscCheck(in[j] < mat->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, in[j], mat->cmap->N - 1);
281           if (mat->was_assembled) {
282             if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
283 #if defined(PETSC_USE_CTABLE)
284             PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] / bs + 1, 0, &col));
285             col = col - 1;
286 #else
287             col = baij->colmap[in[j] / bs] - 1;
288 #endif
289             if (col < 0 && !((Mat_SeqBAIJ *)baij->B->data)->nonew) {
290               PetscCall(MatDisAssemble_MPIBAIJ(mat));
291               col = in[j];
292               /* Reinitialize the variables required by MatSetValues_SeqBAIJ_B_Private() */
293               B     = baij->B;
294               b     = (Mat_SeqBAIJ *)(B)->data;
295               bimax = b->imax;
296               bi    = b->i;
297               bilen = b->ilen;
298               bj    = b->j;
299               ba    = b->a;
300             } else {
301               PetscCheck(col >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new nonzero (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", im[i], in[j]);
302               col += in[j] % bs;
303             }
304           } else col = in[j];
305           if (roworiented) value = v[i * n + j];
306           else value = v[i + j * m];
307           MatSetValues_SeqBAIJ_B_Private(row, col, value, addv, im[i], in[j]);
308           /* PetscCall(MatSetValues_SeqBAIJ(baij->B,1,&row,1,&col,&value,addv)); */
309         }
310       }
311     } else {
312       PetscCheck(!mat->nooffprocentries, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Setting off process row %" PetscInt_FMT " even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set", im[i]);
313       if (!baij->donotstash) {
314         mat->assembled = PETSC_FALSE;
315         if (roworiented) {
316           PetscCall(MatStashValuesRow_Private(&mat->stash, im[i], n, in, v + i * n, PETSC_FALSE));
317         } else {
318           PetscCall(MatStashValuesCol_Private(&mat->stash, im[i], n, in, v + i, m, PETSC_FALSE));
319         }
320       }
321     }
322   }
323   PetscFunctionReturn(PETSC_SUCCESS);
324 }
325 
326 static inline PetscErrorCode MatSetValuesBlocked_SeqBAIJ_Inlined(Mat A, PetscInt row, PetscInt col, const PetscScalar v[], InsertMode is, PetscInt orow, PetscInt ocol)
327 {
328   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ *)A->data;
329   PetscInt          *rp, low, high, t, ii, jj, nrow, i, rmax, N;
330   PetscInt          *imax = a->imax, *ai = a->i, *ailen = a->ilen;
331   PetscInt          *aj = a->j, nonew = a->nonew, bs2 = a->bs2, bs = A->rmap->bs;
332   PetscBool          roworiented = a->roworiented;
333   const PetscScalar *value       = v;
334   MatScalar         *ap, *aa = a->a, *bap;
335 
336   PetscFunctionBegin;
337   rp    = aj + ai[row];
338   ap    = aa + bs2 * ai[row];
339   rmax  = imax[row];
340   nrow  = ailen[row];
341   value = v;
342   low   = 0;
343   high  = nrow;
344   while (high - low > 7) {
345     t = (low + high) / 2;
346     if (rp[t] > col) high = t;
347     else low = t;
348   }
349   for (i = low; i < high; i++) {
350     if (rp[i] > col) break;
351     if (rp[i] == col) {
352       bap = ap + bs2 * i;
353       if (roworiented) {
354         if (is == ADD_VALUES) {
355           for (ii = 0; ii < bs; ii++) {
356             for (jj = ii; jj < bs2; jj += bs) bap[jj] += *value++;
357           }
358         } else {
359           for (ii = 0; ii < bs; ii++) {
360             for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
361           }
362         }
363       } else {
364         if (is == ADD_VALUES) {
365           for (ii = 0; ii < bs; ii++, value += bs) {
366             for (jj = 0; jj < bs; jj++) bap[jj] += value[jj];
367             bap += bs;
368           }
369         } else {
370           for (ii = 0; ii < bs; ii++, value += bs) {
371             for (jj = 0; jj < bs; jj++) bap[jj] = value[jj];
372             bap += bs;
373           }
374         }
375       }
376       goto noinsert2;
377     }
378   }
379   if (nonew == 1) goto noinsert2;
380   PetscCheck(nonew != -1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new global block indexed nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") in the matrix", orow, ocol);
381   MatSeqXAIJReallocateAIJ(A, a->mbs, bs2, nrow, row, col, rmax, aa, ai, aj, rp, ap, imax, nonew, MatScalar);
382   N = nrow++ - 1;
383   high++;
384   /* shift up all the later entries in this row */
385   PetscCall(PetscArraymove(rp + i + 1, rp + i, N - i + 1));
386   PetscCall(PetscArraymove(ap + bs2 * (i + 1), ap + bs2 * i, bs2 * (N - i + 1)));
387   rp[i] = col;
388   bap   = ap + bs2 * i;
389   if (roworiented) {
390     for (ii = 0; ii < bs; ii++) {
391       for (jj = ii; jj < bs2; jj += bs) bap[jj] = *value++;
392     }
393   } else {
394     for (ii = 0; ii < bs; ii++) {
395       for (jj = 0; jj < bs; jj++) *bap++ = *value++;
396     }
397   }
398 noinsert2:;
399   ailen[row] = nrow;
400   PetscFunctionReturn(PETSC_SUCCESS);
401 }
402 
403 /*
404     This routine should be optimized so that the block copy at ** Here a copy is required ** below is not needed
405     by passing additional stride information into the MatSetValuesBlocked_SeqBAIJ_Inlined() routine
406 */
407 static PetscErrorCode MatSetValuesBlocked_MPIBAIJ(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv)
408 {
409   Mat_MPIBAIJ       *baij = (Mat_MPIBAIJ *)mat->data;
410   const PetscScalar *value;
411   MatScalar         *barray      = baij->barray;
412   PetscBool          roworiented = baij->roworiented;
413   PetscInt           i, j, ii, jj, row, col, rstart = baij->rstartbs;
414   PetscInt           rend = baij->rendbs, cstart = baij->cstartbs, stepval;
415   PetscInt           cend = baij->cendbs, bs = mat->rmap->bs, bs2 = baij->bs2;
416 
417   PetscFunctionBegin;
418   if (!barray) {
419     PetscCall(PetscMalloc1(bs2, &barray));
420     baij->barray = barray;
421   }
422 
423   if (roworiented) stepval = (n - 1) * bs;
424   else stepval = (m - 1) * bs;
425 
426   for (i = 0; i < m; i++) {
427     if (im[i] < 0) continue;
428     PetscCheck(im[i] < baij->Mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block indexed row too large %" PetscInt_FMT " max %" PetscInt_FMT, im[i], baij->Mbs - 1);
429     if (im[i] >= rstart && im[i] < rend) {
430       row = im[i] - rstart;
431       for (j = 0; j < n; j++) {
432         /* If NumCol = 1 then a copy is not required */
433         if ((roworiented) && (n == 1)) {
434           barray = (MatScalar *)v + i * bs2;
435         } else if ((!roworiented) && (m == 1)) {
436           barray = (MatScalar *)v + j * bs2;
437         } else { /* Here a copy is required */
438           if (roworiented) {
439             value = v + (i * (stepval + bs) + j) * bs;
440           } else {
441             value = v + (j * (stepval + bs) + i) * bs;
442           }
443           for (ii = 0; ii < bs; ii++, value += bs + stepval) {
444             for (jj = 0; jj < bs; jj++) barray[jj] = value[jj];
445             barray += bs;
446           }
447           barray -= bs2;
448         }
449 
450         if (in[j] >= cstart && in[j] < cend) {
451           col = in[j] - cstart;
452           PetscCall(MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A, row, col, barray, addv, im[i], in[j]));
453         } else if (in[j] < 0) {
454           continue;
455         } else {
456           PetscCheck(in[j] < baij->Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Block indexed column too large %" PetscInt_FMT " max %" PetscInt_FMT, in[j], baij->Nbs - 1);
457           if (mat->was_assembled) {
458             if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
459 
460 #if defined(PETSC_USE_CTABLE)
461             PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] + 1, 0, &col));
462             col = col < 1 ? -1 : (col - 1) / bs;
463 #else
464             col = baij->colmap[in[j]] < 1 ? -1 : (baij->colmap[in[j]] - 1) / bs;
465 #endif
466             if (col < 0 && !((Mat_SeqBAIJ *)baij->B->data)->nonew) {
467               PetscCall(MatDisAssemble_MPIBAIJ(mat));
468               col = in[j];
469             } else PetscCheck(col >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Inserting a new blocked indexed nonzero block (%" PetscInt_FMT ", %" PetscInt_FMT ") into matrix", im[i], in[j]);
470           } else col = in[j];
471           PetscCall(MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B, row, col, barray, addv, im[i], in[j]));
472         }
473       }
474     } else {
475       PetscCheck(!mat->nooffprocentries, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONG, "Setting off process block indexed row %" PetscInt_FMT " even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set", im[i]);
476       if (!baij->donotstash) {
477         if (roworiented) {
478           PetscCall(MatStashValuesRowBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
479         } else {
480           PetscCall(MatStashValuesColBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
481         }
482       }
483     }
484   }
485   PetscFunctionReturn(PETSC_SUCCESS);
486 }
487 
488 #define HASH_KEY             0.6180339887
489 #define HASH(size, key, tmp) (tmp = (key) * HASH_KEY, (PetscInt)((size) * (tmp - (PetscInt)tmp)))
490 /* #define HASH(size,key) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
491 /* #define HASH(size,key,tmp) ((PetscInt)((size)*fmod(((key)*HASH_KEY),1))) */
492 static PetscErrorCode MatSetValues_MPIBAIJ_HT(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv)
493 {
494   Mat_MPIBAIJ *baij        = (Mat_MPIBAIJ *)mat->data;
495   PetscBool    roworiented = baij->roworiented;
496   PetscInt     i, j, row, col;
497   PetscInt     rstart_orig = mat->rmap->rstart;
498   PetscInt     rend_orig = mat->rmap->rend, Nbs = baij->Nbs;
499   PetscInt     h1, key, size = baij->ht_size, bs = mat->rmap->bs, *HT = baij->ht, idx;
500   PetscReal    tmp;
501   MatScalar  **HD       = baij->hd, value;
502   PetscInt     total_ct = baij->ht_total_ct, insert_ct = baij->ht_insert_ct;
503 
504   PetscFunctionBegin;
505   for (i = 0; i < m; i++) {
506     if (PetscDefined(USE_DEBUG)) {
507       PetscCheck(im[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row");
508       PetscCheck(im[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, im[i], mat->rmap->N - 1);
509     }
510     row = im[i];
511     if (row >= rstart_orig && row < rend_orig) {
512       for (j = 0; j < n; j++) {
513         col = in[j];
514         if (roworiented) value = v[i * n + j];
515         else value = v[i + j * m];
516         /* Look up PetscInto the Hash Table */
517         key = (row / bs) * Nbs + (col / bs) + 1;
518         h1  = HASH(size, key, tmp);
519 
520         idx = h1;
521         if (PetscDefined(USE_DEBUG)) {
522           insert_ct++;
523           total_ct++;
524           if (HT[idx] != key) {
525             for (idx = h1; (idx < size) && (HT[idx] != key); idx++, total_ct++);
526             if (idx == size) {
527               for (idx = 0; (idx < h1) && (HT[idx] != key); idx++, total_ct++);
528               PetscCheck(idx != h1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "(%" PetscInt_FMT ",%" PetscInt_FMT ") has no entry in the hash table", row, col);
529             }
530           }
531         } else if (HT[idx] != key) {
532           for (idx = h1; (idx < size) && (HT[idx] != key); idx++);
533           if (idx == size) {
534             for (idx = 0; (idx < h1) && (HT[idx] != key); idx++);
535             PetscCheck(idx != h1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "(%" PetscInt_FMT ",%" PetscInt_FMT ") has no entry in the hash table", row, col);
536           }
537         }
538         /* A HASH table entry is found, so insert the values at the correct address */
539         if (addv == ADD_VALUES) *(HD[idx] + (col % bs) * bs + (row % bs)) += value;
540         else *(HD[idx] + (col % bs) * bs + (row % bs)) = value;
541       }
542     } else if (!baij->donotstash) {
543       if (roworiented) {
544         PetscCall(MatStashValuesRow_Private(&mat->stash, im[i], n, in, v + i * n, PETSC_FALSE));
545       } else {
546         PetscCall(MatStashValuesCol_Private(&mat->stash, im[i], n, in, v + i, m, PETSC_FALSE));
547       }
548     }
549   }
550   if (PetscDefined(USE_DEBUG)) {
551     baij->ht_total_ct += total_ct;
552     baij->ht_insert_ct += insert_ct;
553   }
554   PetscFunctionReturn(PETSC_SUCCESS);
555 }
556 
557 static PetscErrorCode MatSetValuesBlocked_MPIBAIJ_HT(Mat mat, PetscInt m, const PetscInt im[], PetscInt n, const PetscInt in[], const PetscScalar v[], InsertMode addv)
558 {
559   Mat_MPIBAIJ       *baij        = (Mat_MPIBAIJ *)mat->data;
560   PetscBool          roworiented = baij->roworiented;
561   PetscInt           i, j, ii, jj, row, col;
562   PetscInt           rstart = baij->rstartbs;
563   PetscInt           rend = mat->rmap->rend, stepval, bs = mat->rmap->bs, bs2 = baij->bs2, nbs2 = n * bs2;
564   PetscInt           h1, key, size = baij->ht_size, idx, *HT = baij->ht, Nbs = baij->Nbs;
565   PetscReal          tmp;
566   MatScalar        **HD = baij->hd, *baij_a;
567   const PetscScalar *v_t, *value;
568   PetscInt           total_ct = baij->ht_total_ct, insert_ct = baij->ht_insert_ct;
569 
570   PetscFunctionBegin;
571   if (roworiented) stepval = (n - 1) * bs;
572   else stepval = (m - 1) * bs;
573 
574   for (i = 0; i < m; i++) {
575     if (PetscDefined(USE_DEBUG)) {
576       PetscCheck(im[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Negative row: %" PetscInt_FMT, im[i]);
577       PetscCheck(im[i] < baij->Mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, im[i], baij->Mbs - 1);
578     }
579     row = im[i];
580     v_t = v + i * nbs2;
581     if (row >= rstart && row < rend) {
582       for (j = 0; j < n; j++) {
583         col = in[j];
584 
585         /* Look up into the Hash Table */
586         key = row * Nbs + col + 1;
587         h1  = HASH(size, key, tmp);
588 
589         idx = h1;
590         if (PetscDefined(USE_DEBUG)) {
591           total_ct++;
592           insert_ct++;
593           if (HT[idx] != key) {
594             for (idx = h1; (idx < size) && (HT[idx] != key); idx++, total_ct++);
595             if (idx == size) {
596               for (idx = 0; (idx < h1) && (HT[idx] != key); idx++, total_ct++);
597               PetscCheck(idx != h1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "(%" PetscInt_FMT ",%" PetscInt_FMT ") has no entry in the hash table", row, col);
598             }
599           }
600         } else if (HT[idx] != key) {
601           for (idx = h1; (idx < size) && (HT[idx] != key); idx++);
602           if (idx == size) {
603             for (idx = 0; (idx < h1) && (HT[idx] != key); idx++);
604             PetscCheck(idx != h1, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "(%" PetscInt_FMT ",%" PetscInt_FMT ") has no entry in the hash table", row, col);
605           }
606         }
607         baij_a = HD[idx];
608         if (roworiented) {
609           /*value = v + i*(stepval+bs)*bs + j*bs;*/
610           /* value = v + (i*(stepval+bs)+j)*bs; */
611           value = v_t;
612           v_t += bs;
613           if (addv == ADD_VALUES) {
614             for (ii = 0; ii < bs; ii++, value += stepval) {
615               for (jj = ii; jj < bs2; jj += bs) baij_a[jj] += *value++;
616             }
617           } else {
618             for (ii = 0; ii < bs; ii++, value += stepval) {
619               for (jj = ii; jj < bs2; jj += bs) baij_a[jj] = *value++;
620             }
621           }
622         } else {
623           value = v + j * (stepval + bs) * bs + i * bs;
624           if (addv == ADD_VALUES) {
625             for (ii = 0; ii < bs; ii++, value += stepval, baij_a += bs) {
626               for (jj = 0; jj < bs; jj++) baij_a[jj] += *value++;
627             }
628           } else {
629             for (ii = 0; ii < bs; ii++, value += stepval, baij_a += bs) {
630               for (jj = 0; jj < bs; jj++) baij_a[jj] = *value++;
631             }
632           }
633         }
634       }
635     } else {
636       if (!baij->donotstash) {
637         if (roworiented) {
638           PetscCall(MatStashValuesRowBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
639         } else {
640           PetscCall(MatStashValuesColBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
641         }
642       }
643     }
644   }
645   if (PetscDefined(USE_DEBUG)) {
646     baij->ht_total_ct += total_ct;
647     baij->ht_insert_ct += insert_ct;
648   }
649   PetscFunctionReturn(PETSC_SUCCESS);
650 }
651 
652 static PetscErrorCode MatGetValues_MPIBAIJ(Mat mat, PetscInt m, const PetscInt idxm[], PetscInt n, const PetscInt idxn[], PetscScalar v[])
653 {
654   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
655   PetscInt     bs = mat->rmap->bs, i, j, bsrstart = mat->rmap->rstart, bsrend = mat->rmap->rend;
656   PetscInt     bscstart = mat->cmap->rstart, bscend = mat->cmap->rend, row, col, data;
657 
658   PetscFunctionBegin;
659   for (i = 0; i < m; i++) {
660     if (idxm[i] < 0) continue; /* negative row */
661     PetscCheck(idxm[i] < mat->rmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large: row %" PetscInt_FMT " max %" PetscInt_FMT, idxm[i], mat->rmap->N - 1);
662     if (idxm[i] >= bsrstart && idxm[i] < bsrend) {
663       row = idxm[i] - bsrstart;
664       for (j = 0; j < n; j++) {
665         if (idxn[j] < 0) continue; /* negative column */
666         PetscCheck(idxn[j] < mat->cmap->N, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large: col %" PetscInt_FMT " max %" PetscInt_FMT, idxn[j], mat->cmap->N - 1);
667         if (idxn[j] >= bscstart && idxn[j] < bscend) {
668           col = idxn[j] - bscstart;
669           PetscCall(MatGetValues_SeqBAIJ(baij->A, 1, &row, 1, &col, v + i * n + j));
670         } else {
671           if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
672 #if defined(PETSC_USE_CTABLE)
673           PetscCall(PetscHMapIGetWithDefault(baij->colmap, idxn[j] / bs + 1, 0, &data));
674           data--;
675 #else
676           data = baij->colmap[idxn[j] / bs] - 1;
677 #endif
678           if ((data < 0) || (baij->garray[data / bs] != idxn[j] / bs)) *(v + i * n + j) = 0.0;
679           else {
680             col = data + idxn[j] % bs;
681             PetscCall(MatGetValues_SeqBAIJ(baij->B, 1, &row, 1, &col, v + i * n + j));
682           }
683         }
684       }
685     } else SETERRQ(PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local values currently supported");
686   }
687   PetscFunctionReturn(PETSC_SUCCESS);
688 }
689 
690 static PetscErrorCode MatNorm_MPIBAIJ(Mat mat, NormType type, PetscReal *nrm)
691 {
692   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
693   Mat_SeqBAIJ *amat = (Mat_SeqBAIJ *)baij->A->data, *bmat = (Mat_SeqBAIJ *)baij->B->data;
694   PetscInt     i, j, bs2 = baij->bs2, bs = baij->A->rmap->bs, nz, row, col;
695   PetscReal    sum = 0.0;
696   MatScalar   *v;
697 
698   PetscFunctionBegin;
699   if (baij->size == 1) {
700     PetscCall(MatNorm(baij->A, type, nrm));
701   } else {
702     if (type == NORM_FROBENIUS) {
703       v  = amat->a;
704       nz = amat->nz * bs2;
705       for (i = 0; i < nz; i++) {
706         sum += PetscRealPart(PetscConj(*v) * (*v));
707         v++;
708       }
709       v  = bmat->a;
710       nz = bmat->nz * bs2;
711       for (i = 0; i < nz; i++) {
712         sum += PetscRealPart(PetscConj(*v) * (*v));
713         v++;
714       }
715       PetscCallMPI(MPIU_Allreduce(&sum, nrm, 1, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)mat)));
716       *nrm = PetscSqrtReal(*nrm);
717     } else if (type == NORM_1) { /* max column sum */
718       PetscReal  *tmp, *tmp2;
719       PetscInt   *jj, *garray = baij->garray, cstart = baij->rstartbs;
720       PetscMPIInt iN;
721 
722       PetscCall(PetscCalloc1(mat->cmap->N, &tmp));
723       PetscCall(PetscMalloc1(mat->cmap->N, &tmp2));
724       v  = amat->a;
725       jj = amat->j;
726       for (i = 0; i < amat->nz; i++) {
727         for (j = 0; j < bs; j++) {
728           col = bs * (cstart + *jj) + j; /* column index */
729           for (row = 0; row < bs; row++) {
730             tmp[col] += PetscAbsScalar(*v);
731             v++;
732           }
733         }
734         jj++;
735       }
736       v  = bmat->a;
737       jj = bmat->j;
738       for (i = 0; i < bmat->nz; i++) {
739         for (j = 0; j < bs; j++) {
740           col = bs * garray[*jj] + j;
741           for (row = 0; row < bs; row++) {
742             tmp[col] += PetscAbsScalar(*v);
743             v++;
744           }
745         }
746         jj++;
747       }
748       PetscCall(PetscMPIIntCast(mat->cmap->N, &iN));
749       PetscCallMPI(MPIU_Allreduce(tmp, tmp2, iN, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)mat)));
750       *nrm = 0.0;
751       for (j = 0; j < mat->cmap->N; j++) {
752         if (tmp2[j] > *nrm) *nrm = tmp2[j];
753       }
754       PetscCall(PetscFree(tmp));
755       PetscCall(PetscFree(tmp2));
756     } else if (type == NORM_INFINITY) { /* max row sum */
757       PetscReal *sums;
758       PetscCall(PetscMalloc1(bs, &sums));
759       sum = 0.0;
760       for (j = 0; j < amat->mbs; j++) {
761         for (row = 0; row < bs; row++) sums[row] = 0.0;
762         v  = amat->a + bs2 * amat->i[j];
763         nz = amat->i[j + 1] - amat->i[j];
764         for (i = 0; i < nz; i++) {
765           for (col = 0; col < bs; col++) {
766             for (row = 0; row < bs; row++) {
767               sums[row] += PetscAbsScalar(*v);
768               v++;
769             }
770           }
771         }
772         v  = bmat->a + bs2 * bmat->i[j];
773         nz = bmat->i[j + 1] - bmat->i[j];
774         for (i = 0; i < nz; i++) {
775           for (col = 0; col < bs; col++) {
776             for (row = 0; row < bs; row++) {
777               sums[row] += PetscAbsScalar(*v);
778               v++;
779             }
780           }
781         }
782         for (row = 0; row < bs; row++) {
783           if (sums[row] > sum) sum = sums[row];
784         }
785       }
786       PetscCallMPI(MPIU_Allreduce(&sum, nrm, 1, MPIU_REAL, MPIU_MAX, PetscObjectComm((PetscObject)mat)));
787       PetscCall(PetscFree(sums));
788     } else SETERRQ(PetscObjectComm((PetscObject)mat), PETSC_ERR_SUP, "No support for this norm yet");
789   }
790   PetscFunctionReturn(PETSC_SUCCESS);
791 }
792 
793 /*
794   Creates the hash table, and sets the table
795   This table is created only once.
796   If new entried need to be added to the matrix
797   then the hash table has to be destroyed and
798   recreated.
799 */
800 static PetscErrorCode MatCreateHashTable_MPIBAIJ_Private(Mat mat, PetscReal factor)
801 {
802   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
803   Mat          A = baij->A, B = baij->B;
804   Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)A->data, *b = (Mat_SeqBAIJ *)B->data;
805   PetscInt     i, j, k, nz = a->nz + b->nz, h1, *ai = a->i, *aj = a->j, *bi = b->i, *bj = b->j;
806   PetscInt     ht_size, bs2 = baij->bs2, rstart = baij->rstartbs;
807   PetscInt     cstart = baij->cstartbs, *garray = baij->garray, row, col, Nbs = baij->Nbs;
808   PetscInt    *HT, key;
809   MatScalar  **HD;
810   PetscReal    tmp;
811 #if defined(PETSC_USE_INFO)
812   PetscInt ct = 0, max = 0;
813 #endif
814 
815   PetscFunctionBegin;
816   if (baij->ht) PetscFunctionReturn(PETSC_SUCCESS);
817 
818   baij->ht_size = (PetscInt)(factor * nz);
819   ht_size       = baij->ht_size;
820 
821   /* Allocate Memory for Hash Table */
822   PetscCall(PetscCalloc2(ht_size, &baij->hd, ht_size, &baij->ht));
823   HD = baij->hd;
824   HT = baij->ht;
825 
826   /* Loop Over A */
827   for (i = 0; i < a->mbs; i++) {
828     for (j = ai[i]; j < ai[i + 1]; j++) {
829       row = i + rstart;
830       col = aj[j] + cstart;
831 
832       key = row * Nbs + col + 1;
833       h1  = HASH(ht_size, key, tmp);
834       for (k = 0; k < ht_size; k++) {
835         if (!HT[(h1 + k) % ht_size]) {
836           HT[(h1 + k) % ht_size] = key;
837           HD[(h1 + k) % ht_size] = a->a + j * bs2;
838           break;
839 #if defined(PETSC_USE_INFO)
840         } else {
841           ct++;
842 #endif
843         }
844       }
845 #if defined(PETSC_USE_INFO)
846       if (k > max) max = k;
847 #endif
848     }
849   }
850   /* Loop Over B */
851   for (i = 0; i < b->mbs; i++) {
852     for (j = bi[i]; j < bi[i + 1]; j++) {
853       row = i + rstart;
854       col = garray[bj[j]];
855       key = row * Nbs + col + 1;
856       h1  = HASH(ht_size, key, tmp);
857       for (k = 0; k < ht_size; k++) {
858         if (!HT[(h1 + k) % ht_size]) {
859           HT[(h1 + k) % ht_size] = key;
860           HD[(h1 + k) % ht_size] = b->a + j * bs2;
861           break;
862 #if defined(PETSC_USE_INFO)
863         } else {
864           ct++;
865 #endif
866         }
867       }
868 #if defined(PETSC_USE_INFO)
869       if (k > max) max = k;
870 #endif
871     }
872   }
873 
874   /* Print Summary */
875 #if defined(PETSC_USE_INFO)
876   for (i = 0, j = 0; i < ht_size; i++) {
877     if (HT[i]) j++;
878   }
879   PetscCall(PetscInfo(mat, "Average Search = %5.2g,max search = %" PetscInt_FMT "\n", (!j) ? (double)0.0 : (double)(((PetscReal)(ct + j)) / (double)j), max));
880 #endif
881   PetscFunctionReturn(PETSC_SUCCESS);
882 }
883 
884 static PetscErrorCode MatAssemblyBegin_MPIBAIJ(Mat mat, MatAssemblyType mode)
885 {
886   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
887   PetscInt     nstash, reallocs;
888 
889   PetscFunctionBegin;
890   if (baij->donotstash || mat->nooffprocentries) PetscFunctionReturn(PETSC_SUCCESS);
891 
892   PetscCall(MatStashScatterBegin_Private(mat, &mat->stash, mat->rmap->range));
893   PetscCall(MatStashScatterBegin_Private(mat, &mat->bstash, baij->rangebs));
894   PetscCall(MatStashGetInfo_Private(&mat->stash, &nstash, &reallocs));
895   PetscCall(PetscInfo(mat, "Stash has %" PetscInt_FMT " entries,uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs));
896   PetscCall(MatStashGetInfo_Private(&mat->bstash, &nstash, &reallocs));
897   PetscCall(PetscInfo(mat, "Block-Stash has %" PetscInt_FMT " entries, uses %" PetscInt_FMT " mallocs.\n", nstash, reallocs));
898   PetscFunctionReturn(PETSC_SUCCESS);
899 }
900 
901 static PetscErrorCode MatAssemblyEnd_MPIBAIJ(Mat mat, MatAssemblyType mode)
902 {
903   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
904   Mat_SeqBAIJ *a    = (Mat_SeqBAIJ *)baij->A->data;
905   PetscInt     i, j, rstart, ncols, flg, bs2 = baij->bs2;
906   PetscInt    *row, *col;
907   PetscBool    r1, r2, r3, other_disassembled;
908   MatScalar   *val;
909   PetscMPIInt  n;
910 
911   PetscFunctionBegin;
912   /* do not use 'b=(Mat_SeqBAIJ*)baij->B->data' as B can be reset in disassembly */
913   if (!baij->donotstash && !mat->nooffprocentries) {
914     while (1) {
915       PetscCall(MatStashScatterGetMesg_Private(&mat->stash, &n, &row, &col, &val, &flg));
916       if (!flg) break;
917 
918       for (i = 0; i < n;) {
919         /* Now identify the consecutive vals belonging to the same row */
920         for (j = i, rstart = row[j]; j < n; j++) {
921           if (row[j] != rstart) break;
922         }
923         if (j < n) ncols = j - i;
924         else ncols = n - i;
925         /* Now assemble all these values with a single function call */
926         PetscCall(MatSetValues_MPIBAIJ(mat, 1, row + i, ncols, col + i, val + i, mat->insertmode));
927         i = j;
928       }
929     }
930     PetscCall(MatStashScatterEnd_Private(&mat->stash));
931     /* Now process the block-stash. Since the values are stashed column-oriented,
932        set the row-oriented flag to column-oriented, and after MatSetValues()
933        restore the original flags */
934     r1 = baij->roworiented;
935     r2 = a->roworiented;
936     r3 = ((Mat_SeqBAIJ *)baij->B->data)->roworiented;
937 
938     baij->roworiented                           = PETSC_FALSE;
939     a->roworiented                              = PETSC_FALSE;
940     ((Mat_SeqBAIJ *)baij->B->data)->roworiented = PETSC_FALSE;
941     while (1) {
942       PetscCall(MatStashScatterGetMesg_Private(&mat->bstash, &n, &row, &col, &val, &flg));
943       if (!flg) break;
944 
945       for (i = 0; i < n;) {
946         /* Now identify the consecutive vals belonging to the same row */
947         for (j = i, rstart = row[j]; j < n; j++) {
948           if (row[j] != rstart) break;
949         }
950         if (j < n) ncols = j - i;
951         else ncols = n - i;
952         PetscCall(MatSetValuesBlocked_MPIBAIJ(mat, 1, row + i, ncols, col + i, val + i * bs2, mat->insertmode));
953         i = j;
954       }
955     }
956     PetscCall(MatStashScatterEnd_Private(&mat->bstash));
957 
958     baij->roworiented                           = r1;
959     a->roworiented                              = r2;
960     ((Mat_SeqBAIJ *)baij->B->data)->roworiented = r3;
961   }
962 
963   PetscCall(MatAssemblyBegin(baij->A, mode));
964   PetscCall(MatAssemblyEnd(baij->A, mode));
965 
966   /* determine if any processor has disassembled, if so we must
967      also disassemble ourselves, in order that we may reassemble. */
968   /*
969      if nonzero structure of submatrix B cannot change then we know that
970      no processor disassembled thus we can skip this stuff
971   */
972   if (!((Mat_SeqBAIJ *)baij->B->data)->nonew) {
973     PetscCallMPI(MPIU_Allreduce(&mat->was_assembled, &other_disassembled, 1, MPIU_BOOL, MPI_LAND, PetscObjectComm((PetscObject)mat)));
974     if (mat->was_assembled && !other_disassembled) PetscCall(MatDisAssemble_MPIBAIJ(mat));
975   }
976 
977   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) PetscCall(MatSetUpMultiply_MPIBAIJ(mat));
978   PetscCall(MatAssemblyBegin(baij->B, mode));
979   PetscCall(MatAssemblyEnd(baij->B, mode));
980 
981 #if defined(PETSC_USE_INFO)
982   if (baij->ht && mode == MAT_FINAL_ASSEMBLY) {
983     PetscCall(PetscInfo(mat, "Average Hash Table Search in MatSetValues = %5.2f\n", (double)((PetscReal)baij->ht_total_ct) / baij->ht_insert_ct));
984 
985     baij->ht_total_ct  = 0;
986     baij->ht_insert_ct = 0;
987   }
988 #endif
989   if (baij->ht_flag && !baij->ht && mode == MAT_FINAL_ASSEMBLY) {
990     PetscCall(MatCreateHashTable_MPIBAIJ_Private(mat, baij->ht_fact));
991 
992     mat->ops->setvalues        = MatSetValues_MPIBAIJ_HT;
993     mat->ops->setvaluesblocked = MatSetValuesBlocked_MPIBAIJ_HT;
994   }
995 
996   PetscCall(PetscFree2(baij->rowvalues, baij->rowindices));
997 
998   baij->rowvalues = NULL;
999 
1000   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
1001   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqBAIJ *)baij->A->data)->nonew) {
1002     PetscObjectState state = baij->A->nonzerostate + baij->B->nonzerostate;
1003     PetscCallMPI(MPIU_Allreduce(&state, &mat->nonzerostate, 1, MPIU_INT64, MPI_SUM, PetscObjectComm((PetscObject)mat)));
1004   }
1005   PetscFunctionReturn(PETSC_SUCCESS);
1006 }
1007 
1008 extern PetscErrorCode MatView_SeqBAIJ(Mat, PetscViewer);
1009 #include <petscdraw.h>
1010 static PetscErrorCode MatView_MPIBAIJ_ASCIIorDraworSocket(Mat mat, PetscViewer viewer)
1011 {
1012   Mat_MPIBAIJ      *baij = (Mat_MPIBAIJ *)mat->data;
1013   PetscMPIInt       rank = baij->rank;
1014   PetscInt          bs   = mat->rmap->bs;
1015   PetscBool         iascii, isdraw;
1016   PetscViewer       sviewer;
1017   PetscViewerFormat format;
1018 
1019   PetscFunctionBegin;
1020   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
1021   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
1022   if (iascii) {
1023     PetscCall(PetscViewerGetFormat(viewer, &format));
1024     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1025       MatInfo info;
1026       PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)mat), &rank));
1027       PetscCall(MatGetInfo(mat, MAT_LOCAL, &info));
1028       PetscCall(PetscViewerASCIIPushSynchronized(viewer));
1029       PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] Local rows %" PetscInt_FMT " nz %" PetscInt_FMT " nz alloced %" PetscInt_FMT " bs %" PetscInt_FMT " mem %g\n", rank, mat->rmap->n, (PetscInt)info.nz_used, (PetscInt)info.nz_allocated,
1030                                                    mat->rmap->bs, (double)info.memory));
1031       PetscCall(MatGetInfo(baij->A, MAT_LOCAL, &info));
1032       PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] on-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used));
1033       PetscCall(MatGetInfo(baij->B, MAT_LOCAL, &info));
1034       PetscCall(PetscViewerASCIISynchronizedPrintf(viewer, "[%d] off-diagonal part: nz %" PetscInt_FMT " \n", rank, (PetscInt)info.nz_used));
1035       PetscCall(PetscViewerFlush(viewer));
1036       PetscCall(PetscViewerASCIIPopSynchronized(viewer));
1037       PetscCall(PetscViewerASCIIPrintf(viewer, "Information on VecScatter used in matrix-vector product: \n"));
1038       PetscCall(VecScatterView(baij->Mvctx, viewer));
1039       PetscFunctionReturn(PETSC_SUCCESS);
1040     } else if (format == PETSC_VIEWER_ASCII_INFO) {
1041       PetscCall(PetscViewerASCIIPrintf(viewer, "  block size is %" PetscInt_FMT "\n", bs));
1042       PetscFunctionReturn(PETSC_SUCCESS);
1043     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1044       PetscFunctionReturn(PETSC_SUCCESS);
1045     }
1046   }
1047 
1048   if (isdraw) {
1049     PetscDraw draw;
1050     PetscBool isnull;
1051     PetscCall(PetscViewerDrawGetDraw(viewer, 0, &draw));
1052     PetscCall(PetscDrawIsNull(draw, &isnull));
1053     if (isnull) PetscFunctionReturn(PETSC_SUCCESS);
1054   }
1055 
1056   {
1057     /* assemble the entire matrix onto first processor. */
1058     Mat          A;
1059     Mat_SeqBAIJ *Aloc;
1060     PetscInt     M = mat->rmap->N, N = mat->cmap->N, *ai, *aj, col, i, j, k, *rvals, mbs = baij->mbs;
1061     MatScalar   *a;
1062     const char  *matname;
1063 
1064     /* Here we are creating a temporary matrix, so will assume MPIBAIJ is acceptable */
1065     /* Perhaps this should be the type of mat? */
1066     PetscCall(MatCreate(PetscObjectComm((PetscObject)mat), &A));
1067     if (rank == 0) {
1068       PetscCall(MatSetSizes(A, M, N, M, N));
1069     } else {
1070       PetscCall(MatSetSizes(A, 0, 0, M, N));
1071     }
1072     PetscCall(MatSetType(A, MATMPIBAIJ));
1073     PetscCall(MatMPIBAIJSetPreallocation(A, mat->rmap->bs, 0, NULL, 0, NULL));
1074     PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_FALSE));
1075 
1076     /* copy over the A part */
1077     Aloc = (Mat_SeqBAIJ *)baij->A->data;
1078     ai   = Aloc->i;
1079     aj   = Aloc->j;
1080     a    = Aloc->a;
1081     PetscCall(PetscMalloc1(bs, &rvals));
1082 
1083     for (i = 0; i < mbs; i++) {
1084       rvals[0] = bs * (baij->rstartbs + i);
1085       for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1;
1086       for (j = ai[i]; j < ai[i + 1]; j++) {
1087         col = (baij->cstartbs + aj[j]) * bs;
1088         for (k = 0; k < bs; k++) {
1089           PetscCall(MatSetValues_MPIBAIJ(A, bs, rvals, 1, &col, a, INSERT_VALUES));
1090           col++;
1091           a += bs;
1092         }
1093       }
1094     }
1095     /* copy over the B part */
1096     Aloc = (Mat_SeqBAIJ *)baij->B->data;
1097     ai   = Aloc->i;
1098     aj   = Aloc->j;
1099     a    = Aloc->a;
1100     for (i = 0; i < mbs; i++) {
1101       rvals[0] = bs * (baij->rstartbs + i);
1102       for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1;
1103       for (j = ai[i]; j < ai[i + 1]; j++) {
1104         col = baij->garray[aj[j]] * bs;
1105         for (k = 0; k < bs; k++) {
1106           PetscCall(MatSetValues_MPIBAIJ(A, bs, rvals, 1, &col, a, INSERT_VALUES));
1107           col++;
1108           a += bs;
1109         }
1110       }
1111     }
1112     PetscCall(PetscFree(rvals));
1113     PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
1114     PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
1115     /*
1116        Everyone has to call to draw the matrix since the graphics waits are
1117        synchronized across all processors that share the PetscDraw object
1118     */
1119     PetscCall(PetscViewerGetSubViewer(viewer, PETSC_COMM_SELF, &sviewer));
1120     if (((PetscObject)mat)->name) PetscCall(PetscObjectGetName((PetscObject)mat, &matname));
1121     if (rank == 0) {
1122       if (((PetscObject)mat)->name) PetscCall(PetscObjectSetName((PetscObject)((Mat_MPIBAIJ *)A->data)->A, matname));
1123       PetscCall(MatView_SeqBAIJ(((Mat_MPIBAIJ *)A->data)->A, sviewer));
1124     }
1125     PetscCall(PetscViewerRestoreSubViewer(viewer, PETSC_COMM_SELF, &sviewer));
1126     PetscCall(MatDestroy(&A));
1127   }
1128   PetscFunctionReturn(PETSC_SUCCESS);
1129 }
1130 
1131 /* Used for both MPIBAIJ and MPISBAIJ matrices */
1132 PetscErrorCode MatView_MPIBAIJ_Binary(Mat mat, PetscViewer viewer)
1133 {
1134   Mat_MPIBAIJ    *aij    = (Mat_MPIBAIJ *)mat->data;
1135   Mat_SeqBAIJ    *A      = (Mat_SeqBAIJ *)aij->A->data;
1136   Mat_SeqBAIJ    *B      = (Mat_SeqBAIJ *)aij->B->data;
1137   const PetscInt *garray = aij->garray;
1138   PetscInt        header[4], M, N, m, rs, cs, bs, cnt, i, j, ja, jb, k, l;
1139   PetscCount      nz, hnz;
1140   PetscInt       *rowlens, *colidxs;
1141   PetscScalar    *matvals;
1142   PetscMPIInt     rank;
1143 
1144   PetscFunctionBegin;
1145   PetscCall(PetscViewerSetUp(viewer));
1146 
1147   M  = mat->rmap->N;
1148   N  = mat->cmap->N;
1149   m  = mat->rmap->n;
1150   rs = mat->rmap->rstart;
1151   cs = mat->cmap->rstart;
1152   bs = mat->rmap->bs;
1153   nz = bs * bs * (A->nz + B->nz);
1154 
1155   /* write matrix header */
1156   header[0] = MAT_FILE_CLASSID;
1157   header[1] = M;
1158   header[2] = N;
1159   PetscCallMPI(MPI_Reduce(&nz, &hnz, 1, MPIU_COUNT, MPI_SUM, 0, PetscObjectComm((PetscObject)mat)));
1160   PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)mat), &rank));
1161   if (rank == 0) PetscCall(PetscIntCast(hnz, &header[3]));
1162   PetscCall(PetscViewerBinaryWrite(viewer, header, 4, PETSC_INT));
1163 
1164   /* fill in and store row lengths */
1165   PetscCall(PetscMalloc1(m, &rowlens));
1166   for (cnt = 0, i = 0; i < A->mbs; i++)
1167     for (j = 0; j < bs; j++) rowlens[cnt++] = bs * (A->i[i + 1] - A->i[i] + B->i[i + 1] - B->i[i]);
1168   PetscCall(PetscViewerBinaryWriteAll(viewer, rowlens, m, rs, M, PETSC_INT));
1169   PetscCall(PetscFree(rowlens));
1170 
1171   /* fill in and store column indices */
1172   PetscCall(PetscMalloc1(nz, &colidxs));
1173   for (cnt = 0, i = 0; i < A->mbs; i++) {
1174     for (k = 0; k < bs; k++) {
1175       for (jb = B->i[i]; jb < B->i[i + 1]; jb++) {
1176         if (garray[B->j[jb]] > cs / bs) break;
1177         for (l = 0; l < bs; l++) colidxs[cnt++] = bs * garray[B->j[jb]] + l;
1178       }
1179       for (ja = A->i[i]; ja < A->i[i + 1]; ja++)
1180         for (l = 0; l < bs; l++) colidxs[cnt++] = bs * A->j[ja] + l + cs;
1181       for (; jb < B->i[i + 1]; jb++)
1182         for (l = 0; l < bs; l++) colidxs[cnt++] = bs * garray[B->j[jb]] + l;
1183     }
1184   }
1185   PetscCheck(cnt == nz, PETSC_COMM_SELF, PETSC_ERR_LIB, "Internal PETSc error: cnt = %" PetscInt_FMT " nz = %" PetscCount_FMT, cnt, nz);
1186   PetscCall(PetscViewerBinaryWriteAll(viewer, colidxs, nz, PETSC_DECIDE, PETSC_DECIDE, PETSC_INT));
1187   PetscCall(PetscFree(colidxs));
1188 
1189   /* fill in and store nonzero values */
1190   PetscCall(PetscMalloc1(nz, &matvals));
1191   for (cnt = 0, i = 0; i < A->mbs; i++) {
1192     for (k = 0; k < bs; k++) {
1193       for (jb = B->i[i]; jb < B->i[i + 1]; jb++) {
1194         if (garray[B->j[jb]] > cs / bs) break;
1195         for (l = 0; l < bs; l++) matvals[cnt++] = B->a[bs * (bs * jb + l) + k];
1196       }
1197       for (ja = A->i[i]; ja < A->i[i + 1]; ja++)
1198         for (l = 0; l < bs; l++) matvals[cnt++] = A->a[bs * (bs * ja + l) + k];
1199       for (; jb < B->i[i + 1]; jb++)
1200         for (l = 0; l < bs; l++) matvals[cnt++] = B->a[bs * (bs * jb + l) + k];
1201     }
1202   }
1203   PetscCall(PetscViewerBinaryWriteAll(viewer, matvals, nz, PETSC_DECIDE, PETSC_DECIDE, PETSC_SCALAR));
1204   PetscCall(PetscFree(matvals));
1205 
1206   /* write block size option to the viewer's .info file */
1207   PetscCall(MatView_Binary_BlockSizes(mat, viewer));
1208   PetscFunctionReturn(PETSC_SUCCESS);
1209 }
1210 
1211 PetscErrorCode MatView_MPIBAIJ(Mat mat, PetscViewer viewer)
1212 {
1213   PetscBool iascii, isdraw, issocket, isbinary;
1214 
1215   PetscFunctionBegin;
1216   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &iascii));
1217   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERDRAW, &isdraw));
1218   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERSOCKET, &issocket));
1219   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
1220   if (iascii || isdraw || issocket) {
1221     PetscCall(MatView_MPIBAIJ_ASCIIorDraworSocket(mat, viewer));
1222   } else if (isbinary) PetscCall(MatView_MPIBAIJ_Binary(mat, viewer));
1223   PetscFunctionReturn(PETSC_SUCCESS);
1224 }
1225 
1226 static PetscErrorCode MatMult_MPIBAIJ(Mat A, Vec xx, Vec yy)
1227 {
1228   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1229   PetscInt     nt;
1230 
1231   PetscFunctionBegin;
1232   PetscCall(VecGetLocalSize(xx, &nt));
1233   PetscCheck(nt == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible partition of A and xx");
1234   PetscCall(VecGetLocalSize(yy, &nt));
1235   PetscCheck(nt == A->rmap->n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Incompatible partition of A and yy");
1236   PetscCall(VecScatterBegin(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD));
1237   PetscCall((*a->A->ops->mult)(a->A, xx, yy));
1238   PetscCall(VecScatterEnd(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD));
1239   PetscCall((*a->B->ops->multadd)(a->B, a->lvec, yy, yy));
1240   PetscFunctionReturn(PETSC_SUCCESS);
1241 }
1242 
1243 static PetscErrorCode MatMultAdd_MPIBAIJ(Mat A, Vec xx, Vec yy, Vec zz)
1244 {
1245   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1246 
1247   PetscFunctionBegin;
1248   PetscCall(VecScatterBegin(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD));
1249   PetscCall((*a->A->ops->multadd)(a->A, xx, yy, zz));
1250   PetscCall(VecScatterEnd(a->Mvctx, xx, a->lvec, INSERT_VALUES, SCATTER_FORWARD));
1251   PetscCall((*a->B->ops->multadd)(a->B, a->lvec, zz, zz));
1252   PetscFunctionReturn(PETSC_SUCCESS);
1253 }
1254 
1255 static PetscErrorCode MatMultTranspose_MPIBAIJ(Mat A, Vec xx, Vec yy)
1256 {
1257   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1258 
1259   PetscFunctionBegin;
1260   /* do nondiagonal part */
1261   PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->lvec));
1262   /* do local part */
1263   PetscCall((*a->A->ops->multtranspose)(a->A, xx, yy));
1264   /* add partial results together */
1265   PetscCall(VecScatterBegin(a->Mvctx, a->lvec, yy, ADD_VALUES, SCATTER_REVERSE));
1266   PetscCall(VecScatterEnd(a->Mvctx, a->lvec, yy, ADD_VALUES, SCATTER_REVERSE));
1267   PetscFunctionReturn(PETSC_SUCCESS);
1268 }
1269 
1270 static PetscErrorCode MatMultTransposeAdd_MPIBAIJ(Mat A, Vec xx, Vec yy, Vec zz)
1271 {
1272   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1273 
1274   PetscFunctionBegin;
1275   /* do nondiagonal part */
1276   PetscCall((*a->B->ops->multtranspose)(a->B, xx, a->lvec));
1277   /* do local part */
1278   PetscCall((*a->A->ops->multtransposeadd)(a->A, xx, yy, zz));
1279   /* add partial results together */
1280   PetscCall(VecScatterBegin(a->Mvctx, a->lvec, zz, ADD_VALUES, SCATTER_REVERSE));
1281   PetscCall(VecScatterEnd(a->Mvctx, a->lvec, zz, ADD_VALUES, SCATTER_REVERSE));
1282   PetscFunctionReturn(PETSC_SUCCESS);
1283 }
1284 
1285 /*
1286   This only works correctly for square matrices where the subblock A->A is the
1287    diagonal block
1288 */
1289 static PetscErrorCode MatGetDiagonal_MPIBAIJ(Mat A, Vec v)
1290 {
1291   PetscFunctionBegin;
1292   PetscCheck(A->rmap->N == A->cmap->N, PETSC_COMM_SELF, PETSC_ERR_SUP, "Supports only square matrix where A->A is diag block");
1293   PetscCall(MatGetDiagonal(((Mat_MPIBAIJ *)A->data)->A, v));
1294   PetscFunctionReturn(PETSC_SUCCESS);
1295 }
1296 
1297 static PetscErrorCode MatScale_MPIBAIJ(Mat A, PetscScalar aa)
1298 {
1299   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1300 
1301   PetscFunctionBegin;
1302   PetscCall(MatScale(a->A, aa));
1303   PetscCall(MatScale(a->B, aa));
1304   PetscFunctionReturn(PETSC_SUCCESS);
1305 }
1306 
1307 PetscErrorCode MatGetRow_MPIBAIJ(Mat matin, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
1308 {
1309   Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *)matin->data;
1310   PetscScalar *vworkA, *vworkB, **pvA, **pvB, *v_p;
1311   PetscInt     bs = matin->rmap->bs, bs2 = mat->bs2, i, *cworkA, *cworkB, **pcA, **pcB;
1312   PetscInt     nztot, nzA, nzB, lrow, brstart = matin->rmap->rstart, brend = matin->rmap->rend;
1313   PetscInt    *cmap, *idx_p, cstart = mat->cstartbs;
1314 
1315   PetscFunctionBegin;
1316   PetscCheck(row >= brstart && row < brend, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only local rows");
1317   PetscCheck(!mat->getrowactive, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Already active");
1318   mat->getrowactive = PETSC_TRUE;
1319 
1320   if (!mat->rowvalues && (idx || v)) {
1321     /*
1322         allocate enough space to hold information from the longest row.
1323     */
1324     Mat_SeqBAIJ *Aa = (Mat_SeqBAIJ *)mat->A->data, *Ba = (Mat_SeqBAIJ *)mat->B->data;
1325     PetscInt     max = 1, mbs = mat->mbs, tmp;
1326     for (i = 0; i < mbs; i++) {
1327       tmp = Aa->i[i + 1] - Aa->i[i] + Ba->i[i + 1] - Ba->i[i];
1328       if (max < tmp) max = tmp;
1329     }
1330     PetscCall(PetscMalloc2(max * bs2, &mat->rowvalues, max * bs2, &mat->rowindices));
1331   }
1332   lrow = row - brstart;
1333 
1334   pvA = &vworkA;
1335   pcA = &cworkA;
1336   pvB = &vworkB;
1337   pcB = &cworkB;
1338   if (!v) {
1339     pvA = NULL;
1340     pvB = NULL;
1341   }
1342   if (!idx) {
1343     pcA = NULL;
1344     if (!v) pcB = NULL;
1345   }
1346   PetscCall((*mat->A->ops->getrow)(mat->A, lrow, &nzA, pcA, pvA));
1347   PetscCall((*mat->B->ops->getrow)(mat->B, lrow, &nzB, pcB, pvB));
1348   nztot = nzA + nzB;
1349 
1350   cmap = mat->garray;
1351   if (v || idx) {
1352     if (nztot) {
1353       /* Sort by increasing column numbers, assuming A and B already sorted */
1354       PetscInt imark = -1;
1355       if (v) {
1356         *v = v_p = mat->rowvalues;
1357         for (i = 0; i < nzB; i++) {
1358           if (cmap[cworkB[i] / bs] < cstart) v_p[i] = vworkB[i];
1359           else break;
1360         }
1361         imark = i;
1362         for (i = 0; i < nzA; i++) v_p[imark + i] = vworkA[i];
1363         for (i = imark; i < nzB; i++) v_p[nzA + i] = vworkB[i];
1364       }
1365       if (idx) {
1366         *idx = idx_p = mat->rowindices;
1367         if (imark > -1) {
1368           for (i = 0; i < imark; i++) idx_p[i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs;
1369         } else {
1370           for (i = 0; i < nzB; i++) {
1371             if (cmap[cworkB[i] / bs] < cstart) idx_p[i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs;
1372             else break;
1373           }
1374           imark = i;
1375         }
1376         for (i = 0; i < nzA; i++) idx_p[imark + i] = cstart * bs + cworkA[i];
1377         for (i = imark; i < nzB; i++) idx_p[nzA + i] = cmap[cworkB[i] / bs] * bs + cworkB[i] % bs;
1378       }
1379     } else {
1380       if (idx) *idx = NULL;
1381       if (v) *v = NULL;
1382     }
1383   }
1384   *nz = nztot;
1385   PetscCall((*mat->A->ops->restorerow)(mat->A, lrow, &nzA, pcA, pvA));
1386   PetscCall((*mat->B->ops->restorerow)(mat->B, lrow, &nzB, pcB, pvB));
1387   PetscFunctionReturn(PETSC_SUCCESS);
1388 }
1389 
1390 PetscErrorCode MatRestoreRow_MPIBAIJ(Mat mat, PetscInt row, PetscInt *nz, PetscInt **idx, PetscScalar **v)
1391 {
1392   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
1393 
1394   PetscFunctionBegin;
1395   PetscCheck(baij->getrowactive, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "MatGetRow not called");
1396   baij->getrowactive = PETSC_FALSE;
1397   PetscFunctionReturn(PETSC_SUCCESS);
1398 }
1399 
1400 static PetscErrorCode MatZeroEntries_MPIBAIJ(Mat A)
1401 {
1402   Mat_MPIBAIJ *l = (Mat_MPIBAIJ *)A->data;
1403 
1404   PetscFunctionBegin;
1405   PetscCall(MatZeroEntries(l->A));
1406   PetscCall(MatZeroEntries(l->B));
1407   PetscFunctionReturn(PETSC_SUCCESS);
1408 }
1409 
1410 static PetscErrorCode MatGetInfo_MPIBAIJ(Mat matin, MatInfoType flag, MatInfo *info)
1411 {
1412   Mat_MPIBAIJ   *a = (Mat_MPIBAIJ *)matin->data;
1413   Mat            A = a->A, B = a->B;
1414   PetscLogDouble isend[5], irecv[5];
1415 
1416   PetscFunctionBegin;
1417   info->block_size = (PetscReal)matin->rmap->bs;
1418 
1419   PetscCall(MatGetInfo(A, MAT_LOCAL, info));
1420 
1421   isend[0] = info->nz_used;
1422   isend[1] = info->nz_allocated;
1423   isend[2] = info->nz_unneeded;
1424   isend[3] = info->memory;
1425   isend[4] = info->mallocs;
1426 
1427   PetscCall(MatGetInfo(B, MAT_LOCAL, info));
1428 
1429   isend[0] += info->nz_used;
1430   isend[1] += info->nz_allocated;
1431   isend[2] += info->nz_unneeded;
1432   isend[3] += info->memory;
1433   isend[4] += info->mallocs;
1434 
1435   if (flag == MAT_LOCAL) {
1436     info->nz_used      = isend[0];
1437     info->nz_allocated = isend[1];
1438     info->nz_unneeded  = isend[2];
1439     info->memory       = isend[3];
1440     info->mallocs      = isend[4];
1441   } else if (flag == MAT_GLOBAL_MAX) {
1442     PetscCallMPI(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_MAX, PetscObjectComm((PetscObject)matin)));
1443 
1444     info->nz_used      = irecv[0];
1445     info->nz_allocated = irecv[1];
1446     info->nz_unneeded  = irecv[2];
1447     info->memory       = irecv[3];
1448     info->mallocs      = irecv[4];
1449   } else if (flag == MAT_GLOBAL_SUM) {
1450     PetscCallMPI(MPIU_Allreduce(isend, irecv, 5, MPIU_PETSCLOGDOUBLE, MPI_SUM, PetscObjectComm((PetscObject)matin)));
1451 
1452     info->nz_used      = irecv[0];
1453     info->nz_allocated = irecv[1];
1454     info->nz_unneeded  = irecv[2];
1455     info->memory       = irecv[3];
1456     info->mallocs      = irecv[4];
1457   } else SETERRQ(PetscObjectComm((PetscObject)matin), PETSC_ERR_ARG_WRONG, "Unknown MatInfoType argument %d", (int)flag);
1458   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
1459   info->fill_ratio_needed = 0;
1460   info->factor_mallocs    = 0;
1461   PetscFunctionReturn(PETSC_SUCCESS);
1462 }
1463 
1464 static PetscErrorCode MatSetOption_MPIBAIJ(Mat A, MatOption op, PetscBool flg)
1465 {
1466   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1467 
1468   PetscFunctionBegin;
1469   switch (op) {
1470   case MAT_NEW_NONZERO_LOCATIONS:
1471   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1472   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1473   case MAT_KEEP_NONZERO_PATTERN:
1474   case MAT_NEW_NONZERO_LOCATION_ERR:
1475     MatCheckPreallocated(A, 1);
1476     PetscCall(MatSetOption(a->A, op, flg));
1477     PetscCall(MatSetOption(a->B, op, flg));
1478     break;
1479   case MAT_ROW_ORIENTED:
1480     MatCheckPreallocated(A, 1);
1481     a->roworiented = flg;
1482 
1483     PetscCall(MatSetOption(a->A, op, flg));
1484     PetscCall(MatSetOption(a->B, op, flg));
1485     break;
1486   case MAT_FORCE_DIAGONAL_ENTRIES:
1487   case MAT_SORTED_FULL:
1488     PetscCall(PetscInfo(A, "Option %s ignored\n", MatOptions[op]));
1489     break;
1490   case MAT_IGNORE_OFF_PROC_ENTRIES:
1491     a->donotstash = flg;
1492     break;
1493   case MAT_USE_HASH_TABLE:
1494     a->ht_flag = flg;
1495     a->ht_fact = 1.39;
1496     break;
1497   case MAT_SYMMETRIC:
1498   case MAT_STRUCTURALLY_SYMMETRIC:
1499   case MAT_HERMITIAN:
1500   case MAT_SUBMAT_SINGLEIS:
1501   case MAT_SYMMETRY_ETERNAL:
1502   case MAT_STRUCTURAL_SYMMETRY_ETERNAL:
1503   case MAT_SPD_ETERNAL:
1504     /* if the diagonal matrix is square it inherits some of the properties above */
1505     break;
1506   default:
1507     SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "unknown option %d", op);
1508   }
1509   PetscFunctionReturn(PETSC_SUCCESS);
1510 }
1511 
1512 static PetscErrorCode MatTranspose_MPIBAIJ(Mat A, MatReuse reuse, Mat *matout)
1513 {
1514   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)A->data;
1515   Mat_SeqBAIJ *Aloc;
1516   Mat          B;
1517   PetscInt     M = A->rmap->N, N = A->cmap->N, *ai, *aj, i, *rvals, j, k, col;
1518   PetscInt     bs = A->rmap->bs, mbs = baij->mbs;
1519   MatScalar   *a;
1520 
1521   PetscFunctionBegin;
1522   if (reuse == MAT_REUSE_MATRIX) PetscCall(MatTransposeCheckNonzeroState_Private(A, *matout));
1523   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) {
1524     PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
1525     PetscCall(MatSetSizes(B, A->cmap->n, A->rmap->n, N, M));
1526     PetscCall(MatSetType(B, ((PetscObject)A)->type_name));
1527     /* Do not know preallocation information, but must set block size */
1528     PetscCall(MatMPIBAIJSetPreallocation(B, A->rmap->bs, PETSC_DECIDE, NULL, PETSC_DECIDE, NULL));
1529   } else {
1530     B = *matout;
1531   }
1532 
1533   /* copy over the A part */
1534   Aloc = (Mat_SeqBAIJ *)baij->A->data;
1535   ai   = Aloc->i;
1536   aj   = Aloc->j;
1537   a    = Aloc->a;
1538   PetscCall(PetscMalloc1(bs, &rvals));
1539 
1540   for (i = 0; i < mbs; i++) {
1541     rvals[0] = bs * (baij->rstartbs + i);
1542     for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1;
1543     for (j = ai[i]; j < ai[i + 1]; j++) {
1544       col = (baij->cstartbs + aj[j]) * bs;
1545       for (k = 0; k < bs; k++) {
1546         PetscCall(MatSetValues_MPIBAIJ(B, 1, &col, bs, rvals, a, INSERT_VALUES));
1547 
1548         col++;
1549         a += bs;
1550       }
1551     }
1552   }
1553   /* copy over the B part */
1554   Aloc = (Mat_SeqBAIJ *)baij->B->data;
1555   ai   = Aloc->i;
1556   aj   = Aloc->j;
1557   a    = Aloc->a;
1558   for (i = 0; i < mbs; i++) {
1559     rvals[0] = bs * (baij->rstartbs + i);
1560     for (j = 1; j < bs; j++) rvals[j] = rvals[j - 1] + 1;
1561     for (j = ai[i]; j < ai[i + 1]; j++) {
1562       col = baij->garray[aj[j]] * bs;
1563       for (k = 0; k < bs; k++) {
1564         PetscCall(MatSetValues_MPIBAIJ(B, 1, &col, bs, rvals, a, INSERT_VALUES));
1565         col++;
1566         a += bs;
1567       }
1568     }
1569   }
1570   PetscCall(PetscFree(rvals));
1571   PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
1572   PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
1573 
1574   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) *matout = B;
1575   else PetscCall(MatHeaderMerge(A, &B));
1576   PetscFunctionReturn(PETSC_SUCCESS);
1577 }
1578 
1579 static PetscErrorCode MatDiagonalScale_MPIBAIJ(Mat mat, Vec ll, Vec rr)
1580 {
1581   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
1582   Mat          a = baij->A, b = baij->B;
1583   PetscInt     s1, s2, s3;
1584 
1585   PetscFunctionBegin;
1586   PetscCall(MatGetLocalSize(mat, &s2, &s3));
1587   if (rr) {
1588     PetscCall(VecGetLocalSize(rr, &s1));
1589     PetscCheck(s1 == s3, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "right vector non-conforming local size");
1590     /* Overlap communication with computation. */
1591     PetscCall(VecScatterBegin(baij->Mvctx, rr, baij->lvec, INSERT_VALUES, SCATTER_FORWARD));
1592   }
1593   if (ll) {
1594     PetscCall(VecGetLocalSize(ll, &s1));
1595     PetscCheck(s1 == s2, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "left vector non-conforming local size");
1596     PetscUseTypeMethod(b, diagonalscale, ll, NULL);
1597   }
1598   /* scale  the diagonal block */
1599   PetscUseTypeMethod(a, diagonalscale, ll, rr);
1600 
1601   if (rr) {
1602     /* Do a scatter end and then right scale the off-diagonal block */
1603     PetscCall(VecScatterEnd(baij->Mvctx, rr, baij->lvec, INSERT_VALUES, SCATTER_FORWARD));
1604     PetscUseTypeMethod(b, diagonalscale, NULL, baij->lvec);
1605   }
1606   PetscFunctionReturn(PETSC_SUCCESS);
1607 }
1608 
1609 static PetscErrorCode MatZeroRows_MPIBAIJ(Mat A, PetscInt N, const PetscInt rows[], PetscScalar diag, Vec x, Vec b)
1610 {
1611   Mat_MPIBAIJ *l = (Mat_MPIBAIJ *)A->data;
1612   PetscInt    *lrows;
1613   PetscInt     r, len;
1614   PetscBool    cong;
1615 
1616   PetscFunctionBegin;
1617   /* get locally owned rows */
1618   PetscCall(MatZeroRowsMapLocal_Private(A, N, rows, &len, &lrows));
1619   /* fix right-hand side if needed */
1620   if (x && b) {
1621     const PetscScalar *xx;
1622     PetscScalar       *bb;
1623 
1624     PetscCall(VecGetArrayRead(x, &xx));
1625     PetscCall(VecGetArray(b, &bb));
1626     for (r = 0; r < len; ++r) bb[lrows[r]] = diag * xx[lrows[r]];
1627     PetscCall(VecRestoreArrayRead(x, &xx));
1628     PetscCall(VecRestoreArray(b, &bb));
1629   }
1630 
1631   /* actually zap the local rows */
1632   /*
1633         Zero the required rows. If the "diagonal block" of the matrix
1634      is square and the user wishes to set the diagonal we use separate
1635      code so that MatSetValues() is not called for each diagonal allocating
1636      new memory, thus calling lots of mallocs and slowing things down.
1637 
1638   */
1639   /* must zero l->B before l->A because the (diag) case below may put values into l->B*/
1640   PetscCall(MatZeroRows_SeqBAIJ(l->B, len, lrows, 0.0, NULL, NULL));
1641   PetscCall(MatHasCongruentLayouts(A, &cong));
1642   if ((diag != 0.0) && cong) {
1643     PetscCall(MatZeroRows_SeqBAIJ(l->A, len, lrows, diag, NULL, NULL));
1644   } else if (diag != 0.0) {
1645     PetscCall(MatZeroRows_SeqBAIJ(l->A, len, lrows, 0.0, NULL, NULL));
1646     PetscCheck(!((Mat_SeqBAIJ *)l->A->data)->nonew, PETSC_COMM_SELF, PETSC_ERR_SUP, "MatZeroRows() on rectangular matrices cannot be used with the Mat options MAT_NEW_NONZERO_LOCATIONS, MAT_NEW_NONZERO_LOCATION_ERR, and MAT_NEW_NONZERO_ALLOCATION_ERR");
1647     for (r = 0; r < len; ++r) {
1648       const PetscInt row = lrows[r] + A->rmap->rstart;
1649       PetscCall(MatSetValues(A, 1, &row, 1, &row, &diag, INSERT_VALUES));
1650     }
1651     PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
1652     PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
1653   } else {
1654     PetscCall(MatZeroRows_SeqBAIJ(l->A, len, lrows, 0.0, NULL, NULL));
1655   }
1656   PetscCall(PetscFree(lrows));
1657 
1658   /* only change matrix nonzero state if pattern was allowed to be changed */
1659   if (!((Mat_SeqBAIJ *)l->A->data)->keepnonzeropattern || !((Mat_SeqBAIJ *)l->A->data)->nonew) {
1660     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1661     PetscCallMPI(MPIU_Allreduce(&state, &A->nonzerostate, 1, MPIU_INT64, MPI_SUM, PetscObjectComm((PetscObject)A)));
1662   }
1663   PetscFunctionReturn(PETSC_SUCCESS);
1664 }
1665 
1666 static PetscErrorCode MatZeroRowsColumns_MPIBAIJ(Mat A, PetscInt N, const PetscInt rows[], PetscScalar diag, Vec x, Vec b)
1667 {
1668   Mat_MPIBAIJ       *l = (Mat_MPIBAIJ *)A->data;
1669   PetscMPIInt        n, p = 0;
1670   PetscInt           i, j, k, r, len = 0, row, col, count;
1671   PetscInt          *lrows, *owners = A->rmap->range;
1672   PetscSFNode       *rrows;
1673   PetscSF            sf;
1674   const PetscScalar *xx;
1675   PetscScalar       *bb, *mask;
1676   Vec                xmask, lmask;
1677   Mat_SeqBAIJ       *baij = (Mat_SeqBAIJ *)l->B->data;
1678   PetscInt           bs = A->rmap->bs, bs2 = baij->bs2;
1679   PetscScalar       *aa;
1680 
1681   PetscFunctionBegin;
1682   PetscCall(PetscMPIIntCast(A->rmap->n, &n));
1683   /* Create SF where leaves are input rows and roots are owned rows */
1684   PetscCall(PetscMalloc1(n, &lrows));
1685   for (r = 0; r < n; ++r) lrows[r] = -1;
1686   PetscCall(PetscMalloc1(N, &rrows));
1687   for (r = 0; r < N; ++r) {
1688     const PetscInt idx = rows[r];
1689     PetscCheck(idx >= 0 && A->rmap->N > idx, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row %" PetscInt_FMT " out of range [0,%" PetscInt_FMT ")", idx, A->rmap->N);
1690     if (idx < owners[p] || owners[p + 1] <= idx) { /* short-circuit the search if the last p owns this row too */
1691       PetscCall(PetscLayoutFindOwner(A->rmap, idx, &p));
1692     }
1693     rrows[r].rank  = p;
1694     rrows[r].index = rows[r] - owners[p];
1695   }
1696   PetscCall(PetscSFCreate(PetscObjectComm((PetscObject)A), &sf));
1697   PetscCall(PetscSFSetGraph(sf, n, N, NULL, PETSC_OWN_POINTER, rrows, PETSC_OWN_POINTER));
1698   /* Collect flags for rows to be zeroed */
1699   PetscCall(PetscSFReduceBegin(sf, MPIU_INT, (PetscInt *)rows, lrows, MPI_LOR));
1700   PetscCall(PetscSFReduceEnd(sf, MPIU_INT, (PetscInt *)rows, lrows, MPI_LOR));
1701   PetscCall(PetscSFDestroy(&sf));
1702   /* Compress and put in row numbers */
1703   for (r = 0; r < n; ++r)
1704     if (lrows[r] >= 0) lrows[len++] = r;
1705   /* zero diagonal part of matrix */
1706   PetscCall(MatZeroRowsColumns(l->A, len, lrows, diag, x, b));
1707   /* handle off-diagonal part of matrix */
1708   PetscCall(MatCreateVecs(A, &xmask, NULL));
1709   PetscCall(VecDuplicate(l->lvec, &lmask));
1710   PetscCall(VecGetArray(xmask, &bb));
1711   for (i = 0; i < len; i++) bb[lrows[i]] = 1;
1712   PetscCall(VecRestoreArray(xmask, &bb));
1713   PetscCall(VecScatterBegin(l->Mvctx, xmask, lmask, ADD_VALUES, SCATTER_FORWARD));
1714   PetscCall(VecScatterEnd(l->Mvctx, xmask, lmask, ADD_VALUES, SCATTER_FORWARD));
1715   PetscCall(VecDestroy(&xmask));
1716   if (x) {
1717     PetscCall(VecScatterBegin(l->Mvctx, x, l->lvec, INSERT_VALUES, SCATTER_FORWARD));
1718     PetscCall(VecScatterEnd(l->Mvctx, x, l->lvec, INSERT_VALUES, SCATTER_FORWARD));
1719     PetscCall(VecGetArrayRead(l->lvec, &xx));
1720     PetscCall(VecGetArray(b, &bb));
1721   }
1722   PetscCall(VecGetArray(lmask, &mask));
1723   /* remove zeroed rows of off-diagonal matrix */
1724   for (i = 0; i < len; ++i) {
1725     row   = lrows[i];
1726     count = (baij->i[row / bs + 1] - baij->i[row / bs]) * bs;
1727     aa    = ((MatScalar *)baij->a) + baij->i[row / bs] * bs2 + (row % bs);
1728     for (k = 0; k < count; ++k) {
1729       aa[0] = 0.0;
1730       aa += bs;
1731     }
1732   }
1733   /* loop over all elements of off process part of matrix zeroing removed columns*/
1734   for (i = 0; i < l->B->rmap->N; ++i) {
1735     row = i / bs;
1736     for (j = baij->i[row]; j < baij->i[row + 1]; ++j) {
1737       for (k = 0; k < bs; ++k) {
1738         col = bs * baij->j[j] + k;
1739         if (PetscAbsScalar(mask[col])) {
1740           aa = ((MatScalar *)baij->a) + j * bs2 + (i % bs) + bs * k;
1741           if (x) bb[i] -= aa[0] * xx[col];
1742           aa[0] = 0.0;
1743         }
1744       }
1745     }
1746   }
1747   if (x) {
1748     PetscCall(VecRestoreArray(b, &bb));
1749     PetscCall(VecRestoreArrayRead(l->lvec, &xx));
1750   }
1751   PetscCall(VecRestoreArray(lmask, &mask));
1752   PetscCall(VecDestroy(&lmask));
1753   PetscCall(PetscFree(lrows));
1754 
1755   /* only change matrix nonzero state if pattern was allowed to be changed */
1756   if (!((Mat_SeqBAIJ *)l->A->data)->nonew) {
1757     PetscObjectState state = l->A->nonzerostate + l->B->nonzerostate;
1758     PetscCallMPI(MPIU_Allreduce(&state, &A->nonzerostate, 1, MPIU_INT64, MPI_SUM, PetscObjectComm((PetscObject)A)));
1759   }
1760   PetscFunctionReturn(PETSC_SUCCESS);
1761 }
1762 
1763 static PetscErrorCode MatSetUnfactored_MPIBAIJ(Mat A)
1764 {
1765   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1766 
1767   PetscFunctionBegin;
1768   PetscCall(MatSetUnfactored(a->A));
1769   PetscFunctionReturn(PETSC_SUCCESS);
1770 }
1771 
1772 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat, MatDuplicateOption, Mat *);
1773 
1774 static PetscErrorCode MatEqual_MPIBAIJ(Mat A, Mat B, PetscBool *flag)
1775 {
1776   Mat_MPIBAIJ *matB = (Mat_MPIBAIJ *)B->data, *matA = (Mat_MPIBAIJ *)A->data;
1777   Mat          a, b, c, d;
1778   PetscBool    flg;
1779 
1780   PetscFunctionBegin;
1781   a = matA->A;
1782   b = matA->B;
1783   c = matB->A;
1784   d = matB->B;
1785 
1786   PetscCall(MatEqual(a, c, &flg));
1787   if (flg) PetscCall(MatEqual(b, d, &flg));
1788   PetscCallMPI(MPIU_Allreduce(&flg, flag, 1, MPIU_BOOL, MPI_LAND, PetscObjectComm((PetscObject)A)));
1789   PetscFunctionReturn(PETSC_SUCCESS);
1790 }
1791 
1792 static PetscErrorCode MatCopy_MPIBAIJ(Mat A, Mat B, MatStructure str)
1793 {
1794   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1795   Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data;
1796 
1797   PetscFunctionBegin;
1798   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
1799   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
1800     PetscCall(MatCopy_Basic(A, B, str));
1801   } else {
1802     PetscCall(MatCopy(a->A, b->A, str));
1803     PetscCall(MatCopy(a->B, b->B, str));
1804   }
1805   PetscCall(PetscObjectStateIncrease((PetscObject)B));
1806   PetscFunctionReturn(PETSC_SUCCESS);
1807 }
1808 
1809 PetscErrorCode MatAXPYGetPreallocation_MPIBAIJ(Mat Y, const PetscInt *yltog, Mat X, const PetscInt *xltog, PetscInt *nnz)
1810 {
1811   PetscInt     bs = Y->rmap->bs, m = Y->rmap->N / bs;
1812   Mat_SeqBAIJ *x = (Mat_SeqBAIJ *)X->data;
1813   Mat_SeqBAIJ *y = (Mat_SeqBAIJ *)Y->data;
1814 
1815   PetscFunctionBegin;
1816   PetscCall(MatAXPYGetPreallocation_MPIX_private(m, x->i, x->j, xltog, y->i, y->j, yltog, nnz));
1817   PetscFunctionReturn(PETSC_SUCCESS);
1818 }
1819 
1820 static PetscErrorCode MatAXPY_MPIBAIJ(Mat Y, PetscScalar a, Mat X, MatStructure str)
1821 {
1822   Mat_MPIBAIJ *xx = (Mat_MPIBAIJ *)X->data, *yy = (Mat_MPIBAIJ *)Y->data;
1823   PetscBLASInt bnz, one                         = 1;
1824   Mat_SeqBAIJ *x, *y;
1825   PetscInt     bs2 = Y->rmap->bs * Y->rmap->bs;
1826 
1827   PetscFunctionBegin;
1828   if (str == SAME_NONZERO_PATTERN) {
1829     PetscScalar alpha = a;
1830     x                 = (Mat_SeqBAIJ *)xx->A->data;
1831     y                 = (Mat_SeqBAIJ *)yy->A->data;
1832     PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz));
1833     PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
1834     x = (Mat_SeqBAIJ *)xx->B->data;
1835     y = (Mat_SeqBAIJ *)yy->B->data;
1836     PetscCall(PetscBLASIntCast(x->nz * bs2, &bnz));
1837     PetscCallBLAS("BLASaxpy", BLASaxpy_(&bnz, &alpha, x->a, &one, y->a, &one));
1838     PetscCall(PetscObjectStateIncrease((PetscObject)Y));
1839   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
1840     PetscCall(MatAXPY_Basic(Y, a, X, str));
1841   } else {
1842     Mat       B;
1843     PetscInt *nnz_d, *nnz_o, bs = Y->rmap->bs;
1844     PetscCall(PetscMalloc1(yy->A->rmap->N, &nnz_d));
1845     PetscCall(PetscMalloc1(yy->B->rmap->N, &nnz_o));
1846     PetscCall(MatCreate(PetscObjectComm((PetscObject)Y), &B));
1847     PetscCall(PetscObjectSetName((PetscObject)B, ((PetscObject)Y)->name));
1848     PetscCall(MatSetSizes(B, Y->rmap->n, Y->cmap->n, Y->rmap->N, Y->cmap->N));
1849     PetscCall(MatSetBlockSizesFromMats(B, Y, Y));
1850     PetscCall(MatSetType(B, MATMPIBAIJ));
1851     PetscCall(MatAXPYGetPreallocation_SeqBAIJ(yy->A, xx->A, nnz_d));
1852     PetscCall(MatAXPYGetPreallocation_MPIBAIJ(yy->B, yy->garray, xx->B, xx->garray, nnz_o));
1853     PetscCall(MatMPIBAIJSetPreallocation(B, bs, 0, nnz_d, 0, nnz_o));
1854     /* MatAXPY_BasicWithPreallocation() for BAIJ matrix is much slower than AIJ, even for bs=1 ! */
1855     PetscCall(MatAXPY_BasicWithPreallocation(B, Y, a, X, str));
1856     PetscCall(MatHeaderMerge(Y, &B));
1857     PetscCall(PetscFree(nnz_d));
1858     PetscCall(PetscFree(nnz_o));
1859   }
1860   PetscFunctionReturn(PETSC_SUCCESS);
1861 }
1862 
1863 static PetscErrorCode MatConjugate_MPIBAIJ(Mat mat)
1864 {
1865   PetscFunctionBegin;
1866   if (PetscDefined(USE_COMPLEX)) {
1867     Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)mat->data;
1868 
1869     PetscCall(MatConjugate_SeqBAIJ(a->A));
1870     PetscCall(MatConjugate_SeqBAIJ(a->B));
1871   }
1872   PetscFunctionReturn(PETSC_SUCCESS);
1873 }
1874 
1875 static PetscErrorCode MatRealPart_MPIBAIJ(Mat A)
1876 {
1877   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1878 
1879   PetscFunctionBegin;
1880   PetscCall(MatRealPart(a->A));
1881   PetscCall(MatRealPart(a->B));
1882   PetscFunctionReturn(PETSC_SUCCESS);
1883 }
1884 
1885 static PetscErrorCode MatImaginaryPart_MPIBAIJ(Mat A)
1886 {
1887   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
1888 
1889   PetscFunctionBegin;
1890   PetscCall(MatImaginaryPart(a->A));
1891   PetscCall(MatImaginaryPart(a->B));
1892   PetscFunctionReturn(PETSC_SUCCESS);
1893 }
1894 
1895 static PetscErrorCode MatCreateSubMatrix_MPIBAIJ(Mat mat, IS isrow, IS iscol, MatReuse call, Mat *newmat)
1896 {
1897   IS       iscol_local;
1898   PetscInt csize;
1899 
1900   PetscFunctionBegin;
1901   PetscCall(ISGetLocalSize(iscol, &csize));
1902   if (call == MAT_REUSE_MATRIX) {
1903     PetscCall(PetscObjectQuery((PetscObject)*newmat, "ISAllGather", (PetscObject *)&iscol_local));
1904     PetscCheck(iscol_local, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Submatrix passed in was not used before, cannot reuse");
1905   } else {
1906     PetscCall(ISAllGather(iscol, &iscol_local));
1907   }
1908   PetscCall(MatCreateSubMatrix_MPIBAIJ_Private(mat, isrow, iscol_local, csize, call, newmat, PETSC_FALSE));
1909   if (call == MAT_INITIAL_MATRIX) {
1910     PetscCall(PetscObjectCompose((PetscObject)*newmat, "ISAllGather", (PetscObject)iscol_local));
1911     PetscCall(ISDestroy(&iscol_local));
1912   }
1913   PetscFunctionReturn(PETSC_SUCCESS);
1914 }
1915 
1916 /*
1917   Not great since it makes two copies of the submatrix, first an SeqBAIJ
1918   in local and then by concatenating the local matrices the end result.
1919   Writing it directly would be much like MatCreateSubMatrices_MPIBAIJ().
1920   This routine is used for BAIJ and SBAIJ matrices (unfortunate dependency).
1921 */
1922 PetscErrorCode MatCreateSubMatrix_MPIBAIJ_Private(Mat mat, IS isrow, IS iscol, PetscInt csize, MatReuse call, Mat *newmat, PetscBool sym)
1923 {
1924   PetscMPIInt  rank, size;
1925   PetscInt     i, m, n, rstart, row, rend, nz, *cwork, j, bs;
1926   PetscInt    *ii, *jj, nlocal, *dlens, *olens, dlen, olen, jend, mglobal;
1927   Mat          M, Mreuse;
1928   MatScalar   *vwork, *aa;
1929   MPI_Comm     comm;
1930   IS           isrow_new, iscol_new;
1931   Mat_SeqBAIJ *aij;
1932 
1933   PetscFunctionBegin;
1934   PetscCall(PetscObjectGetComm((PetscObject)mat, &comm));
1935   PetscCallMPI(MPI_Comm_rank(comm, &rank));
1936   PetscCallMPI(MPI_Comm_size(comm, &size));
1937   /* The compression and expansion should be avoided. Doesn't point
1938      out errors, might change the indices, hence buggey */
1939   PetscCall(ISCompressIndicesGeneral(mat->rmap->N, mat->rmap->n, mat->rmap->bs, 1, &isrow, &isrow_new));
1940   if (isrow == iscol) {
1941     iscol_new = isrow_new;
1942     PetscCall(PetscObjectReference((PetscObject)iscol_new));
1943   } else PetscCall(ISCompressIndicesGeneral(mat->cmap->N, mat->cmap->n, mat->cmap->bs, 1, &iscol, &iscol_new));
1944 
1945   if (call == MAT_REUSE_MATRIX) {
1946     PetscCall(PetscObjectQuery((PetscObject)*newmat, "SubMatrix", (PetscObject *)&Mreuse));
1947     PetscCheck(Mreuse, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Submatrix passed in was not used before, cannot reuse");
1948     PetscCall(MatCreateSubMatrices_MPIBAIJ_local(mat, 1, &isrow_new, &iscol_new, MAT_REUSE_MATRIX, &Mreuse, sym));
1949   } else {
1950     PetscCall(MatCreateSubMatrices_MPIBAIJ_local(mat, 1, &isrow_new, &iscol_new, MAT_INITIAL_MATRIX, &Mreuse, sym));
1951   }
1952   PetscCall(ISDestroy(&isrow_new));
1953   PetscCall(ISDestroy(&iscol_new));
1954   /*
1955       m - number of local rows
1956       n - number of columns (same on all processors)
1957       rstart - first row in new global matrix generated
1958   */
1959   PetscCall(MatGetBlockSize(mat, &bs));
1960   PetscCall(MatGetSize(Mreuse, &m, &n));
1961   m = m / bs;
1962   n = n / bs;
1963 
1964   if (call == MAT_INITIAL_MATRIX) {
1965     aij = (Mat_SeqBAIJ *)(Mreuse)->data;
1966     ii  = aij->i;
1967     jj  = aij->j;
1968 
1969     /*
1970         Determine the number of non-zeros in the diagonal and off-diagonal
1971         portions of the matrix in order to do correct preallocation
1972     */
1973 
1974     /* first get start and end of "diagonal" columns */
1975     if (csize == PETSC_DECIDE) {
1976       PetscCall(ISGetSize(isrow, &mglobal));
1977       if (mglobal == n * bs) { /* square matrix */
1978         nlocal = m;
1979       } else {
1980         nlocal = n / size + ((n % size) > rank);
1981       }
1982     } else {
1983       nlocal = csize / bs;
1984     }
1985     PetscCallMPI(MPI_Scan(&nlocal, &rend, 1, MPIU_INT, MPI_SUM, comm));
1986     rstart = rend - nlocal;
1987     PetscCheck(rank != size - 1 || rend == n, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Local column sizes %" PetscInt_FMT " do not add up to total number of columns %" PetscInt_FMT, rend, n);
1988 
1989     /* next, compute all the lengths */
1990     PetscCall(PetscMalloc2(m + 1, &dlens, m + 1, &olens));
1991     for (i = 0; i < m; i++) {
1992       jend = ii[i + 1] - ii[i];
1993       olen = 0;
1994       dlen = 0;
1995       for (j = 0; j < jend; j++) {
1996         if (*jj < rstart || *jj >= rend) olen++;
1997         else dlen++;
1998         jj++;
1999       }
2000       olens[i] = olen;
2001       dlens[i] = dlen;
2002     }
2003     PetscCall(MatCreate(comm, &M));
2004     PetscCall(MatSetSizes(M, bs * m, bs * nlocal, PETSC_DECIDE, bs * n));
2005     PetscCall(MatSetType(M, sym ? ((PetscObject)mat)->type_name : MATMPIBAIJ));
2006     PetscCall(MatMPIBAIJSetPreallocation(M, bs, 0, dlens, 0, olens));
2007     PetscCall(MatMPISBAIJSetPreallocation(M, bs, 0, dlens, 0, olens));
2008     PetscCall(PetscFree2(dlens, olens));
2009   } else {
2010     PetscInt ml, nl;
2011 
2012     M = *newmat;
2013     PetscCall(MatGetLocalSize(M, &ml, &nl));
2014     PetscCheck(ml == m, PETSC_COMM_SELF, PETSC_ERR_ARG_SIZ, "Previous matrix must be same size/layout as request");
2015     PetscCall(MatZeroEntries(M));
2016     /*
2017          The next two lines are needed so we may call MatSetValues_MPIAIJ() below directly,
2018        rather than the slower MatSetValues().
2019     */
2020     M->was_assembled = PETSC_TRUE;
2021     M->assembled     = PETSC_FALSE;
2022   }
2023   PetscCall(MatSetOption(M, MAT_ROW_ORIENTED, PETSC_FALSE));
2024   PetscCall(MatGetOwnershipRange(M, &rstart, &rend));
2025   aij = (Mat_SeqBAIJ *)(Mreuse)->data;
2026   ii  = aij->i;
2027   jj  = aij->j;
2028   aa  = aij->a;
2029   for (i = 0; i < m; i++) {
2030     row   = rstart / bs + i;
2031     nz    = ii[i + 1] - ii[i];
2032     cwork = jj;
2033     jj    = PetscSafePointerPlusOffset(jj, nz);
2034     vwork = aa;
2035     aa    = PetscSafePointerPlusOffset(aa, nz * bs * bs);
2036     PetscCall(MatSetValuesBlocked_MPIBAIJ(M, 1, &row, nz, cwork, vwork, INSERT_VALUES));
2037   }
2038 
2039   PetscCall(MatAssemblyBegin(M, MAT_FINAL_ASSEMBLY));
2040   PetscCall(MatAssemblyEnd(M, MAT_FINAL_ASSEMBLY));
2041   *newmat = M;
2042 
2043   /* save submatrix used in processor for next request */
2044   if (call == MAT_INITIAL_MATRIX) {
2045     PetscCall(PetscObjectCompose((PetscObject)M, "SubMatrix", (PetscObject)Mreuse));
2046     PetscCall(PetscObjectDereference((PetscObject)Mreuse));
2047   }
2048   PetscFunctionReturn(PETSC_SUCCESS);
2049 }
2050 
2051 static PetscErrorCode MatPermute_MPIBAIJ(Mat A, IS rowp, IS colp, Mat *B)
2052 {
2053   MPI_Comm        comm, pcomm;
2054   PetscInt        clocal_size, nrows;
2055   const PetscInt *rows;
2056   PetscMPIInt     size;
2057   IS              crowp, lcolp;
2058 
2059   PetscFunctionBegin;
2060   PetscCall(PetscObjectGetComm((PetscObject)A, &comm));
2061   /* make a collective version of 'rowp' */
2062   PetscCall(PetscObjectGetComm((PetscObject)rowp, &pcomm));
2063   if (pcomm == comm) {
2064     crowp = rowp;
2065   } else {
2066     PetscCall(ISGetSize(rowp, &nrows));
2067     PetscCall(ISGetIndices(rowp, &rows));
2068     PetscCall(ISCreateGeneral(comm, nrows, rows, PETSC_COPY_VALUES, &crowp));
2069     PetscCall(ISRestoreIndices(rowp, &rows));
2070   }
2071   PetscCall(ISSetPermutation(crowp));
2072   /* make a local version of 'colp' */
2073   PetscCall(PetscObjectGetComm((PetscObject)colp, &pcomm));
2074   PetscCallMPI(MPI_Comm_size(pcomm, &size));
2075   if (size == 1) {
2076     lcolp = colp;
2077   } else {
2078     PetscCall(ISAllGather(colp, &lcolp));
2079   }
2080   PetscCall(ISSetPermutation(lcolp));
2081   /* now we just get the submatrix */
2082   PetscCall(MatGetLocalSize(A, NULL, &clocal_size));
2083   PetscCall(MatCreateSubMatrix_MPIBAIJ_Private(A, crowp, lcolp, clocal_size, MAT_INITIAL_MATRIX, B, PETSC_FALSE));
2084   /* clean up */
2085   if (pcomm != comm) PetscCall(ISDestroy(&crowp));
2086   if (size > 1) PetscCall(ISDestroy(&lcolp));
2087   PetscFunctionReturn(PETSC_SUCCESS);
2088 }
2089 
2090 static PetscErrorCode MatGetGhosts_MPIBAIJ(Mat mat, PetscInt *nghosts, const PetscInt *ghosts[])
2091 {
2092   Mat_MPIBAIJ *baij = (Mat_MPIBAIJ *)mat->data;
2093   Mat_SeqBAIJ *B    = (Mat_SeqBAIJ *)baij->B->data;
2094 
2095   PetscFunctionBegin;
2096   if (nghosts) *nghosts = B->nbs;
2097   if (ghosts) *ghosts = baij->garray;
2098   PetscFunctionReturn(PETSC_SUCCESS);
2099 }
2100 
2101 static PetscErrorCode MatGetSeqNonzeroStructure_MPIBAIJ(Mat A, Mat *newmat)
2102 {
2103   Mat          B;
2104   Mat_MPIBAIJ *a  = (Mat_MPIBAIJ *)A->data;
2105   Mat_SeqBAIJ *ad = (Mat_SeqBAIJ *)a->A->data, *bd = (Mat_SeqBAIJ *)a->B->data;
2106   Mat_SeqAIJ  *b;
2107   PetscMPIInt  size, rank, *recvcounts = NULL, *displs = NULL;
2108   PetscInt     sendcount, i, *rstarts = A->rmap->range, n, cnt, j, bs = A->rmap->bs;
2109   PetscInt     m, *garray = a->garray, *lens, *jsendbuf, *a_jsendbuf, *b_jsendbuf;
2110 
2111   PetscFunctionBegin;
2112   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)A), &size));
2113   PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)A), &rank));
2114 
2115   /*   Tell every processor the number of nonzeros per row  */
2116   PetscCall(PetscMalloc1(A->rmap->N / bs, &lens));
2117   for (i = A->rmap->rstart / bs; i < A->rmap->rend / bs; i++) lens[i] = ad->i[i - A->rmap->rstart / bs + 1] - ad->i[i - A->rmap->rstart / bs] + bd->i[i - A->rmap->rstart / bs + 1] - bd->i[i - A->rmap->rstart / bs];
2118   PetscCall(PetscMalloc1(2 * size, &recvcounts));
2119   displs = recvcounts + size;
2120   for (i = 0; i < size; i++) {
2121     PetscCall(PetscMPIIntCast(A->rmap->range[i + 1] / bs - A->rmap->range[i] / bs, &recvcounts[i]));
2122     PetscCall(PetscMPIIntCast(A->rmap->range[i] / bs, &displs[i]));
2123   }
2124   PetscCallMPI(MPI_Allgatherv(MPI_IN_PLACE, 0, MPI_DATATYPE_NULL, lens, recvcounts, displs, MPIU_INT, PetscObjectComm((PetscObject)A)));
2125   /* Create the sequential matrix of the same type as the local block diagonal  */
2126   PetscCall(MatCreate(PETSC_COMM_SELF, &B));
2127   PetscCall(MatSetSizes(B, A->rmap->N / bs, A->cmap->N / bs, PETSC_DETERMINE, PETSC_DETERMINE));
2128   PetscCall(MatSetType(B, MATSEQAIJ));
2129   PetscCall(MatSeqAIJSetPreallocation(B, 0, lens));
2130   b = (Mat_SeqAIJ *)B->data;
2131 
2132   /*     Copy my part of matrix column indices over  */
2133   sendcount  = ad->nz + bd->nz;
2134   jsendbuf   = b->j + b->i[rstarts[rank] / bs];
2135   a_jsendbuf = ad->j;
2136   b_jsendbuf = bd->j;
2137   n          = A->rmap->rend / bs - A->rmap->rstart / bs;
2138   cnt        = 0;
2139   for (i = 0; i < n; i++) {
2140     /* put in lower diagonal portion */
2141     m = bd->i[i + 1] - bd->i[i];
2142     while (m > 0) {
2143       /* is it above diagonal (in bd (compressed) numbering) */
2144       if (garray[*b_jsendbuf] > A->rmap->rstart / bs + i) break;
2145       jsendbuf[cnt++] = garray[*b_jsendbuf++];
2146       m--;
2147     }
2148 
2149     /* put in diagonal portion */
2150     for (j = ad->i[i]; j < ad->i[i + 1]; j++) jsendbuf[cnt++] = A->rmap->rstart / bs + *a_jsendbuf++;
2151 
2152     /* put in upper diagonal portion */
2153     while (m-- > 0) jsendbuf[cnt++] = garray[*b_jsendbuf++];
2154   }
2155   PetscCheck(cnt == sendcount, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Corrupted PETSc matrix: nz given %" PetscInt_FMT " actual nz %" PetscInt_FMT, sendcount, cnt);
2156 
2157   /*  Gather all column indices to all processors  */
2158   for (i = 0; i < size; i++) {
2159     recvcounts[i] = 0;
2160     for (j = A->rmap->range[i] / bs; j < A->rmap->range[i + 1] / bs; j++) recvcounts[i] += lens[j];
2161   }
2162   displs[0] = 0;
2163   for (i = 1; i < size; i++) displs[i] = displs[i - 1] + recvcounts[i - 1];
2164   PetscCallMPI(MPI_Allgatherv(MPI_IN_PLACE, 0, MPI_DATATYPE_NULL, b->j, recvcounts, displs, MPIU_INT, PetscObjectComm((PetscObject)A)));
2165   /*  Assemble the matrix into usable form (note numerical values not yet set)  */
2166   /* set the b->ilen (length of each row) values */
2167   PetscCall(PetscArraycpy(b->ilen, lens, A->rmap->N / bs));
2168   /* set the b->i indices */
2169   b->i[0] = 0;
2170   for (i = 1; i <= A->rmap->N / bs; i++) b->i[i] = b->i[i - 1] + lens[i - 1];
2171   PetscCall(PetscFree(lens));
2172   PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
2173   PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
2174   PetscCall(PetscFree(recvcounts));
2175 
2176   PetscCall(MatPropagateSymmetryOptions(A, B));
2177   *newmat = B;
2178   PetscFunctionReturn(PETSC_SUCCESS);
2179 }
2180 
2181 static PetscErrorCode MatSOR_MPIBAIJ(Mat matin, Vec bb, PetscReal omega, MatSORType flag, PetscReal fshift, PetscInt its, PetscInt lits, Vec xx)
2182 {
2183   Mat_MPIBAIJ *mat = (Mat_MPIBAIJ *)matin->data;
2184   Vec          bb1 = NULL;
2185 
2186   PetscFunctionBegin;
2187   if (flag == SOR_APPLY_UPPER) {
2188     PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2189     PetscFunctionReturn(PETSC_SUCCESS);
2190   }
2191 
2192   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS) PetscCall(VecDuplicate(bb, &bb1));
2193 
2194   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
2195     if (flag & SOR_ZERO_INITIAL_GUESS) {
2196       PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2197       its--;
2198     }
2199 
2200     while (its--) {
2201       PetscCall(VecScatterBegin(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD));
2202       PetscCall(VecScatterEnd(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD));
2203 
2204       /* update rhs: bb1 = bb - B*x */
2205       PetscCall(VecScale(mat->lvec, -1.0));
2206       PetscCall((*mat->B->ops->multadd)(mat->B, mat->lvec, bb, bb1));
2207 
2208       /* local sweep */
2209       PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_SYMMETRIC_SWEEP, fshift, lits, 1, xx));
2210     }
2211   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
2212     if (flag & SOR_ZERO_INITIAL_GUESS) {
2213       PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2214       its--;
2215     }
2216     while (its--) {
2217       PetscCall(VecScatterBegin(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD));
2218       PetscCall(VecScatterEnd(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD));
2219 
2220       /* update rhs: bb1 = bb - B*x */
2221       PetscCall(VecScale(mat->lvec, -1.0));
2222       PetscCall((*mat->B->ops->multadd)(mat->B, mat->lvec, bb, bb1));
2223 
2224       /* local sweep */
2225       PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_FORWARD_SWEEP, fshift, lits, 1, xx));
2226     }
2227   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
2228     if (flag & SOR_ZERO_INITIAL_GUESS) {
2229       PetscCall((*mat->A->ops->sor)(mat->A, bb, omega, flag, fshift, lits, 1, xx));
2230       its--;
2231     }
2232     while (its--) {
2233       PetscCall(VecScatterBegin(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD));
2234       PetscCall(VecScatterEnd(mat->Mvctx, xx, mat->lvec, INSERT_VALUES, SCATTER_FORWARD));
2235 
2236       /* update rhs: bb1 = bb - B*x */
2237       PetscCall(VecScale(mat->lvec, -1.0));
2238       PetscCall((*mat->B->ops->multadd)(mat->B, mat->lvec, bb, bb1));
2239 
2240       /* local sweep */
2241       PetscCall((*mat->A->ops->sor)(mat->A, bb1, omega, SOR_BACKWARD_SWEEP, fshift, lits, 1, xx));
2242     }
2243   } else SETERRQ(PetscObjectComm((PetscObject)matin), PETSC_ERR_SUP, "Parallel version of SOR requested not supported");
2244 
2245   PetscCall(VecDestroy(&bb1));
2246   PetscFunctionReturn(PETSC_SUCCESS);
2247 }
2248 
2249 static PetscErrorCode MatGetColumnReductions_MPIBAIJ(Mat A, PetscInt type, PetscReal *reductions)
2250 {
2251   Mat_MPIBAIJ *aij = (Mat_MPIBAIJ *)A->data;
2252   PetscInt     m, N, i, *garray = aij->garray;
2253   PetscInt     ib, jb, bs = A->rmap->bs;
2254   Mat_SeqBAIJ *a_aij = (Mat_SeqBAIJ *)aij->A->data;
2255   MatScalar   *a_val = a_aij->a;
2256   Mat_SeqBAIJ *b_aij = (Mat_SeqBAIJ *)aij->B->data;
2257   MatScalar   *b_val = b_aij->a;
2258   PetscReal   *work;
2259   PetscMPIInt  iN;
2260 
2261   PetscFunctionBegin;
2262   PetscCall(MatGetSize(A, &m, &N));
2263   PetscCall(PetscCalloc1(N, &work));
2264   if (type == NORM_2) {
2265     for (i = a_aij->i[0]; i < a_aij->i[aij->A->rmap->n / bs]; i++) {
2266       for (jb = 0; jb < bs; jb++) {
2267         for (ib = 0; ib < bs; ib++) {
2268           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val * *a_val);
2269           a_val++;
2270         }
2271       }
2272     }
2273     for (i = b_aij->i[0]; i < b_aij->i[aij->B->rmap->n / bs]; i++) {
2274       for (jb = 0; jb < bs; jb++) {
2275         for (ib = 0; ib < bs; ib++) {
2276           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val * *b_val);
2277           b_val++;
2278         }
2279       }
2280     }
2281   } else if (type == NORM_1) {
2282     for (i = a_aij->i[0]; i < a_aij->i[aij->A->rmap->n / bs]; i++) {
2283       for (jb = 0; jb < bs; jb++) {
2284         for (ib = 0; ib < bs; ib++) {
2285           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscAbsScalar(*a_val);
2286           a_val++;
2287         }
2288       }
2289     }
2290     for (i = b_aij->i[0]; i < b_aij->i[aij->B->rmap->n / bs]; i++) {
2291       for (jb = 0; jb < bs; jb++) {
2292         for (ib = 0; ib < bs; ib++) {
2293           work[garray[b_aij->j[i]] * bs + jb] += PetscAbsScalar(*b_val);
2294           b_val++;
2295         }
2296       }
2297     }
2298   } else if (type == NORM_INFINITY) {
2299     for (i = a_aij->i[0]; i < a_aij->i[aij->A->rmap->n / bs]; i++) {
2300       for (jb = 0; jb < bs; jb++) {
2301         for (ib = 0; ib < bs; ib++) {
2302           PetscInt col = A->cmap->rstart + a_aij->j[i] * bs + jb;
2303           work[col]    = PetscMax(PetscAbsScalar(*a_val), work[col]);
2304           a_val++;
2305         }
2306       }
2307     }
2308     for (i = b_aij->i[0]; i < b_aij->i[aij->B->rmap->n / bs]; i++) {
2309       for (jb = 0; jb < bs; jb++) {
2310         for (ib = 0; ib < bs; ib++) {
2311           PetscInt col = garray[b_aij->j[i]] * bs + jb;
2312           work[col]    = PetscMax(PetscAbsScalar(*b_val), work[col]);
2313           b_val++;
2314         }
2315       }
2316     }
2317   } else if (type == REDUCTION_SUM_REALPART || type == REDUCTION_MEAN_REALPART) {
2318     for (i = a_aij->i[0]; i < a_aij->i[aij->A->rmap->n / bs]; i++) {
2319       for (jb = 0; jb < bs; jb++) {
2320         for (ib = 0; ib < bs; ib++) {
2321           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscRealPart(*a_val);
2322           a_val++;
2323         }
2324       }
2325     }
2326     for (i = b_aij->i[0]; i < b_aij->i[aij->B->rmap->n / bs]; i++) {
2327       for (jb = 0; jb < bs; jb++) {
2328         for (ib = 0; ib < bs; ib++) {
2329           work[garray[b_aij->j[i]] * bs + jb] += PetscRealPart(*b_val);
2330           b_val++;
2331         }
2332       }
2333     }
2334   } else if (type == REDUCTION_SUM_IMAGINARYPART || type == REDUCTION_MEAN_IMAGINARYPART) {
2335     for (i = a_aij->i[0]; i < a_aij->i[aij->A->rmap->n / bs]; i++) {
2336       for (jb = 0; jb < bs; jb++) {
2337         for (ib = 0; ib < bs; ib++) {
2338           work[A->cmap->rstart + a_aij->j[i] * bs + jb] += PetscImaginaryPart(*a_val);
2339           a_val++;
2340         }
2341       }
2342     }
2343     for (i = b_aij->i[0]; i < b_aij->i[aij->B->rmap->n / bs]; i++) {
2344       for (jb = 0; jb < bs; jb++) {
2345         for (ib = 0; ib < bs; ib++) {
2346           work[garray[b_aij->j[i]] * bs + jb] += PetscImaginaryPart(*b_val);
2347           b_val++;
2348         }
2349       }
2350     }
2351   } else SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_ARG_WRONG, "Unknown reduction type");
2352   PetscCall(PetscMPIIntCast(N, &iN));
2353   if (type == NORM_INFINITY) {
2354     PetscCallMPI(MPIU_Allreduce(work, reductions, iN, MPIU_REAL, MPIU_MAX, PetscObjectComm((PetscObject)A)));
2355   } else {
2356     PetscCallMPI(MPIU_Allreduce(work, reductions, iN, MPIU_REAL, MPIU_SUM, PetscObjectComm((PetscObject)A)));
2357   }
2358   PetscCall(PetscFree(work));
2359   if (type == NORM_2) {
2360     for (i = 0; i < N; i++) reductions[i] = PetscSqrtReal(reductions[i]);
2361   } else if (type == REDUCTION_MEAN_REALPART || type == REDUCTION_MEAN_IMAGINARYPART) {
2362     for (i = 0; i < N; i++) reductions[i] /= m;
2363   }
2364   PetscFunctionReturn(PETSC_SUCCESS);
2365 }
2366 
2367 static PetscErrorCode MatInvertBlockDiagonal_MPIBAIJ(Mat A, const PetscScalar **values)
2368 {
2369   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
2370 
2371   PetscFunctionBegin;
2372   PetscCall(MatInvertBlockDiagonal(a->A, values));
2373   A->factorerrortype             = a->A->factorerrortype;
2374   A->factorerror_zeropivot_value = a->A->factorerror_zeropivot_value;
2375   A->factorerror_zeropivot_row   = a->A->factorerror_zeropivot_row;
2376   PetscFunctionReturn(PETSC_SUCCESS);
2377 }
2378 
2379 static PetscErrorCode MatShift_MPIBAIJ(Mat Y, PetscScalar a)
2380 {
2381   Mat_MPIBAIJ *maij = (Mat_MPIBAIJ *)Y->data;
2382   Mat_SeqBAIJ *aij  = (Mat_SeqBAIJ *)maij->A->data;
2383 
2384   PetscFunctionBegin;
2385   if (!Y->preallocated) {
2386     PetscCall(MatMPIBAIJSetPreallocation(Y, Y->rmap->bs, 1, NULL, 0, NULL));
2387   } else if (!aij->nz) {
2388     PetscInt nonew = aij->nonew;
2389     PetscCall(MatSeqBAIJSetPreallocation(maij->A, Y->rmap->bs, 1, NULL));
2390     aij->nonew = nonew;
2391   }
2392   PetscCall(MatShift_Basic(Y, a));
2393   PetscFunctionReturn(PETSC_SUCCESS);
2394 }
2395 
2396 static PetscErrorCode MatMissingDiagonal_MPIBAIJ(Mat A, PetscBool *missing, PetscInt *d)
2397 {
2398   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
2399 
2400   PetscFunctionBegin;
2401   PetscCheck(A->rmap->n == A->cmap->n, PETSC_COMM_SELF, PETSC_ERR_SUP, "Only works for square matrices");
2402   PetscCall(MatMissingDiagonal(a->A, missing, d));
2403   if (d) {
2404     PetscInt rstart;
2405     PetscCall(MatGetOwnershipRange(A, &rstart, NULL));
2406     *d += rstart / A->rmap->bs;
2407   }
2408   PetscFunctionReturn(PETSC_SUCCESS);
2409 }
2410 
2411 static PetscErrorCode MatGetDiagonalBlock_MPIBAIJ(Mat A, Mat *a)
2412 {
2413   PetscFunctionBegin;
2414   *a = ((Mat_MPIBAIJ *)A->data)->A;
2415   PetscFunctionReturn(PETSC_SUCCESS);
2416 }
2417 
2418 static PetscErrorCode MatEliminateZeros_MPIBAIJ(Mat A, PetscBool keep)
2419 {
2420   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
2421 
2422   PetscFunctionBegin;
2423   PetscCall(MatEliminateZeros_SeqBAIJ(a->A, keep));        // possibly keep zero diagonal coefficients
2424   PetscCall(MatEliminateZeros_SeqBAIJ(a->B, PETSC_FALSE)); // never keep zero diagonal coefficients
2425   PetscFunctionReturn(PETSC_SUCCESS);
2426 }
2427 
2428 static struct _MatOps MatOps_Values = {MatSetValues_MPIBAIJ,
2429                                        MatGetRow_MPIBAIJ,
2430                                        MatRestoreRow_MPIBAIJ,
2431                                        MatMult_MPIBAIJ,
2432                                        /* 4*/ MatMultAdd_MPIBAIJ,
2433                                        MatMultTranspose_MPIBAIJ,
2434                                        MatMultTransposeAdd_MPIBAIJ,
2435                                        NULL,
2436                                        NULL,
2437                                        NULL,
2438                                        /*10*/ NULL,
2439                                        NULL,
2440                                        NULL,
2441                                        MatSOR_MPIBAIJ,
2442                                        MatTranspose_MPIBAIJ,
2443                                        /*15*/ MatGetInfo_MPIBAIJ,
2444                                        MatEqual_MPIBAIJ,
2445                                        MatGetDiagonal_MPIBAIJ,
2446                                        MatDiagonalScale_MPIBAIJ,
2447                                        MatNorm_MPIBAIJ,
2448                                        /*20*/ MatAssemblyBegin_MPIBAIJ,
2449                                        MatAssemblyEnd_MPIBAIJ,
2450                                        MatSetOption_MPIBAIJ,
2451                                        MatZeroEntries_MPIBAIJ,
2452                                        /*24*/ MatZeroRows_MPIBAIJ,
2453                                        NULL,
2454                                        NULL,
2455                                        NULL,
2456                                        NULL,
2457                                        /*29*/ MatSetUp_MPI_Hash,
2458                                        NULL,
2459                                        NULL,
2460                                        MatGetDiagonalBlock_MPIBAIJ,
2461                                        NULL,
2462                                        /*34*/ MatDuplicate_MPIBAIJ,
2463                                        NULL,
2464                                        NULL,
2465                                        NULL,
2466                                        NULL,
2467                                        /*39*/ MatAXPY_MPIBAIJ,
2468                                        MatCreateSubMatrices_MPIBAIJ,
2469                                        MatIncreaseOverlap_MPIBAIJ,
2470                                        MatGetValues_MPIBAIJ,
2471                                        MatCopy_MPIBAIJ,
2472                                        /*44*/ NULL,
2473                                        MatScale_MPIBAIJ,
2474                                        MatShift_MPIBAIJ,
2475                                        NULL,
2476                                        MatZeroRowsColumns_MPIBAIJ,
2477                                        /*49*/ NULL,
2478                                        NULL,
2479                                        NULL,
2480                                        NULL,
2481                                        NULL,
2482                                        /*54*/ MatFDColoringCreate_MPIXAIJ,
2483                                        NULL,
2484                                        MatSetUnfactored_MPIBAIJ,
2485                                        MatPermute_MPIBAIJ,
2486                                        MatSetValuesBlocked_MPIBAIJ,
2487                                        /*59*/ MatCreateSubMatrix_MPIBAIJ,
2488                                        MatDestroy_MPIBAIJ,
2489                                        MatView_MPIBAIJ,
2490                                        NULL,
2491                                        NULL,
2492                                        /*64*/ NULL,
2493                                        NULL,
2494                                        NULL,
2495                                        NULL,
2496                                        NULL,
2497                                        /*69*/ MatGetRowMaxAbs_MPIBAIJ,
2498                                        NULL,
2499                                        NULL,
2500                                        NULL,
2501                                        NULL,
2502                                        /*74*/ NULL,
2503                                        MatFDColoringApply_BAIJ,
2504                                        NULL,
2505                                        NULL,
2506                                        NULL,
2507                                        /*79*/ NULL,
2508                                        NULL,
2509                                        NULL,
2510                                        NULL,
2511                                        MatLoad_MPIBAIJ,
2512                                        /*84*/ NULL,
2513                                        NULL,
2514                                        NULL,
2515                                        NULL,
2516                                        NULL,
2517                                        /*89*/ NULL,
2518                                        NULL,
2519                                        NULL,
2520                                        NULL,
2521                                        NULL,
2522                                        /*94*/ NULL,
2523                                        NULL,
2524                                        NULL,
2525                                        NULL,
2526                                        NULL,
2527                                        /*99*/ NULL,
2528                                        NULL,
2529                                        NULL,
2530                                        MatConjugate_MPIBAIJ,
2531                                        NULL,
2532                                        /*104*/ NULL,
2533                                        MatRealPart_MPIBAIJ,
2534                                        MatImaginaryPart_MPIBAIJ,
2535                                        NULL,
2536                                        NULL,
2537                                        /*109*/ NULL,
2538                                        NULL,
2539                                        NULL,
2540                                        NULL,
2541                                        MatMissingDiagonal_MPIBAIJ,
2542                                        /*114*/ MatGetSeqNonzeroStructure_MPIBAIJ,
2543                                        NULL,
2544                                        MatGetGhosts_MPIBAIJ,
2545                                        NULL,
2546                                        NULL,
2547                                        /*119*/ NULL,
2548                                        NULL,
2549                                        NULL,
2550                                        NULL,
2551                                        MatGetMultiProcBlock_MPIBAIJ,
2552                                        /*124*/ NULL,
2553                                        MatGetColumnReductions_MPIBAIJ,
2554                                        MatInvertBlockDiagonal_MPIBAIJ,
2555                                        NULL,
2556                                        NULL,
2557                                        /*129*/ NULL,
2558                                        NULL,
2559                                        NULL,
2560                                        NULL,
2561                                        NULL,
2562                                        /*134*/ NULL,
2563                                        NULL,
2564                                        NULL,
2565                                        NULL,
2566                                        NULL,
2567                                        /*139*/ MatSetBlockSizes_Default,
2568                                        NULL,
2569                                        NULL,
2570                                        MatFDColoringSetUp_MPIXAIJ,
2571                                        NULL,
2572                                        /*144*/ MatCreateMPIMatConcatenateSeqMat_MPIBAIJ,
2573                                        NULL,
2574                                        NULL,
2575                                        NULL,
2576                                        NULL,
2577                                        NULL,
2578                                        /*150*/ NULL,
2579                                        MatEliminateZeros_MPIBAIJ,
2580                                        MatGetRowSumAbs_MPIBAIJ,
2581                                        NULL,
2582                                        NULL,
2583                                        NULL};
2584 
2585 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPISBAIJ(Mat, MatType, MatReuse, Mat *);
2586 PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat, MatType, MatReuse, Mat *);
2587 
2588 static PetscErrorCode MatMPIBAIJSetPreallocationCSR_MPIBAIJ(Mat B, PetscInt bs, const PetscInt ii[], const PetscInt jj[], const PetscScalar V[])
2589 {
2590   PetscInt        m, rstart, cstart, cend;
2591   PetscInt        i, j, dlen, olen, nz, nz_max = 0, *d_nnz = NULL, *o_nnz = NULL;
2592   const PetscInt *JJ          = NULL;
2593   PetscScalar    *values      = NULL;
2594   PetscBool       roworiented = ((Mat_MPIBAIJ *)B->data)->roworiented;
2595   PetscBool       nooffprocentries;
2596 
2597   PetscFunctionBegin;
2598   PetscCall(PetscLayoutSetBlockSize(B->rmap, bs));
2599   PetscCall(PetscLayoutSetBlockSize(B->cmap, bs));
2600   PetscCall(PetscLayoutSetUp(B->rmap));
2601   PetscCall(PetscLayoutSetUp(B->cmap));
2602   PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
2603   m      = B->rmap->n / bs;
2604   rstart = B->rmap->rstart / bs;
2605   cstart = B->cmap->rstart / bs;
2606   cend   = B->cmap->rend / bs;
2607 
2608   PetscCheck(!ii[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %" PetscInt_FMT, ii[0]);
2609   PetscCall(PetscMalloc2(m, &d_nnz, m, &o_nnz));
2610   for (i = 0; i < m; i++) {
2611     nz = ii[i + 1] - ii[i];
2612     PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Local row %" PetscInt_FMT " has a negative number of columns %" PetscInt_FMT, i, nz);
2613     nz_max = PetscMax(nz_max, nz);
2614     dlen   = 0;
2615     olen   = 0;
2616     JJ     = jj + ii[i];
2617     for (j = 0; j < nz; j++) {
2618       if (*JJ < cstart || *JJ >= cend) olen++;
2619       else dlen++;
2620       JJ++;
2621     }
2622     d_nnz[i] = dlen;
2623     o_nnz[i] = olen;
2624   }
2625   PetscCall(MatMPIBAIJSetPreallocation(B, bs, 0, d_nnz, 0, o_nnz));
2626   PetscCall(PetscFree2(d_nnz, o_nnz));
2627 
2628   values = (PetscScalar *)V;
2629   if (!values) PetscCall(PetscCalloc1(bs * bs * nz_max, &values));
2630   for (i = 0; i < m; i++) {
2631     PetscInt        row   = i + rstart;
2632     PetscInt        ncols = ii[i + 1] - ii[i];
2633     const PetscInt *icols = jj + ii[i];
2634     if (bs == 1 || !roworiented) { /* block ordering matches the non-nested layout of MatSetValues so we can insert entire rows */
2635       const PetscScalar *svals = values + (V ? (bs * bs * ii[i]) : 0);
2636       PetscCall(MatSetValuesBlocked_MPIBAIJ(B, 1, &row, ncols, icols, svals, INSERT_VALUES));
2637     } else { /* block ordering does not match so we can only insert one block at a time. */
2638       PetscInt j;
2639       for (j = 0; j < ncols; j++) {
2640         const PetscScalar *svals = values + (V ? (bs * bs * (ii[i] + j)) : 0);
2641         PetscCall(MatSetValuesBlocked_MPIBAIJ(B, 1, &row, 1, &icols[j], svals, INSERT_VALUES));
2642       }
2643     }
2644   }
2645 
2646   if (!V) PetscCall(PetscFree(values));
2647   nooffprocentries    = B->nooffprocentries;
2648   B->nooffprocentries = PETSC_TRUE;
2649   PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
2650   PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
2651   B->nooffprocentries = nooffprocentries;
2652 
2653   PetscCall(MatSetOption(B, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
2654   PetscFunctionReturn(PETSC_SUCCESS);
2655 }
2656 
2657 /*@C
2658   MatMPIBAIJSetPreallocationCSR - Creates a sparse parallel matrix in `MATBAIJ` format using the given nonzero structure and (optional) numerical values
2659 
2660   Collective
2661 
2662   Input Parameters:
2663 + B  - the matrix
2664 . bs - the block size
2665 . i  - the indices into `j` for the start of each local row (starts with zero)
2666 . j  - the column indices for each local row (starts with zero) these must be sorted for each row
2667 - v  - optional values in the matrix, use `NULL` if not provided
2668 
2669   Level: advanced
2670 
2671   Notes:
2672   The `i`, `j`, and `v` arrays ARE copied by this routine into the internal format used by PETSc;
2673   thus you CANNOT change the matrix entries by changing the values of `v` after you have
2674   called this routine.
2675 
2676   The order of the entries in values is specified by the `MatOption` `MAT_ROW_ORIENTED`.  For example, C programs
2677   may want to use the default `MAT_ROW_ORIENTED` with value `PETSC_TRUE` and use an array v[nnz][bs][bs] where the second index is
2678   over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
2679   `MAT_ROW_ORIENTED` with value `PETSC_FALSE` and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
2680   block column and the second index is over columns within a block.
2681 
2682   Though this routine has Preallocation() in the name it also sets the exact nonzero locations of the matrix entries and usually the numerical values as well
2683 
2684 .seealso: `Mat`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatMPIBAIJSetPreallocation()`, `MatCreateAIJ()`, `MATMPIAIJ`, `MatCreateMPIBAIJWithArrays()`, `MATMPIBAIJ`
2685 @*/
2686 PetscErrorCode MatMPIBAIJSetPreallocationCSR(Mat B, PetscInt bs, const PetscInt i[], const PetscInt j[], const PetscScalar v[])
2687 {
2688   PetscFunctionBegin;
2689   PetscValidHeaderSpecific(B, MAT_CLASSID, 1);
2690   PetscValidType(B, 1);
2691   PetscValidLogicalCollectiveInt(B, bs, 2);
2692   PetscTryMethod(B, "MatMPIBAIJSetPreallocationCSR_C", (Mat, PetscInt, const PetscInt[], const PetscInt[], const PetscScalar[]), (B, bs, i, j, v));
2693   PetscFunctionReturn(PETSC_SUCCESS);
2694 }
2695 
2696 PetscErrorCode MatMPIBAIJSetPreallocation_MPIBAIJ(Mat B, PetscInt bs, PetscInt d_nz, const PetscInt *d_nnz, PetscInt o_nz, const PetscInt *o_nnz)
2697 {
2698   Mat_MPIBAIJ *b = (Mat_MPIBAIJ *)B->data;
2699   PetscInt     i;
2700   PetscMPIInt  size;
2701 
2702   PetscFunctionBegin;
2703   if (B->hash_active) {
2704     B->ops[0]      = b->cops;
2705     B->hash_active = PETSC_FALSE;
2706   }
2707   if (!B->preallocated) PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), bs, &B->bstash));
2708   PetscCall(MatSetBlockSize(B, PetscAbs(bs)));
2709   PetscCall(PetscLayoutSetUp(B->rmap));
2710   PetscCall(PetscLayoutSetUp(B->cmap));
2711   PetscCall(PetscLayoutGetBlockSize(B->rmap, &bs));
2712 
2713   if (d_nnz) {
2714     for (i = 0; i < B->rmap->n / bs; i++) PetscCheck(d_nnz[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "d_nnz cannot be less than -1: local row %" PetscInt_FMT " value %" PetscInt_FMT, i, d_nnz[i]);
2715   }
2716   if (o_nnz) {
2717     for (i = 0; i < B->rmap->n / bs; i++) PetscCheck(o_nnz[i] >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "o_nnz cannot be less than -1: local row %" PetscInt_FMT " value %" PetscInt_FMT, i, o_nnz[i]);
2718   }
2719 
2720   b->bs2 = bs * bs;
2721   b->mbs = B->rmap->n / bs;
2722   b->nbs = B->cmap->n / bs;
2723   b->Mbs = B->rmap->N / bs;
2724   b->Nbs = B->cmap->N / bs;
2725 
2726   for (i = 0; i <= b->size; i++) b->rangebs[i] = B->rmap->range[i] / bs;
2727   b->rstartbs = B->rmap->rstart / bs;
2728   b->rendbs   = B->rmap->rend / bs;
2729   b->cstartbs = B->cmap->rstart / bs;
2730   b->cendbs   = B->cmap->rend / bs;
2731 
2732 #if defined(PETSC_USE_CTABLE)
2733   PetscCall(PetscHMapIDestroy(&b->colmap));
2734 #else
2735   PetscCall(PetscFree(b->colmap));
2736 #endif
2737   PetscCall(PetscFree(b->garray));
2738   PetscCall(VecDestroy(&b->lvec));
2739   PetscCall(VecScatterDestroy(&b->Mvctx));
2740 
2741   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &size));
2742 
2743   MatSeqXAIJGetOptions_Private(b->B);
2744   PetscCall(MatDestroy(&b->B));
2745   PetscCall(MatCreate(PETSC_COMM_SELF, &b->B));
2746   PetscCall(MatSetSizes(b->B, B->rmap->n, size > 1 ? B->cmap->N : 0, B->rmap->n, size > 1 ? B->cmap->N : 0));
2747   PetscCall(MatSetType(b->B, MATSEQBAIJ));
2748   MatSeqXAIJRestoreOptions_Private(b->B);
2749 
2750   MatSeqXAIJGetOptions_Private(b->A);
2751   PetscCall(MatDestroy(&b->A));
2752   PetscCall(MatCreate(PETSC_COMM_SELF, &b->A));
2753   PetscCall(MatSetSizes(b->A, B->rmap->n, B->cmap->n, B->rmap->n, B->cmap->n));
2754   PetscCall(MatSetType(b->A, MATSEQBAIJ));
2755   MatSeqXAIJRestoreOptions_Private(b->A);
2756 
2757   PetscCall(MatSeqBAIJSetPreallocation(b->A, bs, d_nz, d_nnz));
2758   PetscCall(MatSeqBAIJSetPreallocation(b->B, bs, o_nz, o_nnz));
2759   B->preallocated  = PETSC_TRUE;
2760   B->was_assembled = PETSC_FALSE;
2761   B->assembled     = PETSC_FALSE;
2762   PetscFunctionReturn(PETSC_SUCCESS);
2763 }
2764 
2765 extern PetscErrorCode MatDiagonalScaleLocal_MPIBAIJ(Mat, Vec);
2766 extern PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat, PetscReal);
2767 
2768 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAdj(Mat B, MatType newtype, MatReuse reuse, Mat *adj)
2769 {
2770   Mat_MPIBAIJ    *b = (Mat_MPIBAIJ *)B->data;
2771   Mat_SeqBAIJ    *d = (Mat_SeqBAIJ *)b->A->data, *o = (Mat_SeqBAIJ *)b->B->data;
2772   PetscInt        M = B->rmap->n / B->rmap->bs, i, *ii, *jj, cnt, j, k, rstart = B->rmap->rstart / B->rmap->bs;
2773   const PetscInt *id = d->i, *jd = d->j, *io = o->i, *jo = o->j, *garray = b->garray;
2774 
2775   PetscFunctionBegin;
2776   PetscCall(PetscMalloc1(M + 1, &ii));
2777   ii[0] = 0;
2778   for (i = 0; i < M; i++) {
2779     PetscCheck((id[i + 1] - id[i]) >= 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Indices wrong %" PetscInt_FMT " %" PetscInt_FMT " %" PetscInt_FMT, i, id[i], id[i + 1]);
2780     PetscCheck((io[i + 1] - io[i]) >= 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Indices wrong %" PetscInt_FMT " %" PetscInt_FMT " %" PetscInt_FMT, i, io[i], io[i + 1]);
2781     ii[i + 1] = ii[i] + id[i + 1] - id[i] + io[i + 1] - io[i];
2782     /* remove one from count of matrix has diagonal */
2783     for (j = id[i]; j < id[i + 1]; j++) {
2784       if (jd[j] == i) {
2785         ii[i + 1]--;
2786         break;
2787       }
2788     }
2789   }
2790   PetscCall(PetscMalloc1(ii[M], &jj));
2791   cnt = 0;
2792   for (i = 0; i < M; i++) {
2793     for (j = io[i]; j < io[i + 1]; j++) {
2794       if (garray[jo[j]] > rstart) break;
2795       jj[cnt++] = garray[jo[j]];
2796     }
2797     for (k = id[i]; k < id[i + 1]; k++) {
2798       if (jd[k] != i) jj[cnt++] = rstart + jd[k];
2799     }
2800     for (; j < io[i + 1]; j++) jj[cnt++] = garray[jo[j]];
2801   }
2802   PetscCall(MatCreateMPIAdj(PetscObjectComm((PetscObject)B), M, B->cmap->N / B->rmap->bs, ii, jj, NULL, adj));
2803   PetscFunctionReturn(PETSC_SUCCESS);
2804 }
2805 
2806 #include <../src/mat/impls/aij/mpi/mpiaij.h>
2807 
2808 PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType, MatReuse, Mat *);
2809 
2810 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIAIJ(Mat A, MatType newtype, MatReuse reuse, Mat *newmat)
2811 {
2812   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
2813   Mat_MPIAIJ  *b;
2814   Mat          B;
2815 
2816   PetscFunctionBegin;
2817   PetscCheck(A->assembled, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "Matrix must be assembled");
2818 
2819   if (reuse == MAT_REUSE_MATRIX) {
2820     B = *newmat;
2821   } else {
2822     PetscCall(MatCreate(PetscObjectComm((PetscObject)A), &B));
2823     PetscCall(MatSetType(B, MATMPIAIJ));
2824     PetscCall(MatSetSizes(B, A->rmap->n, A->cmap->n, A->rmap->N, A->cmap->N));
2825     PetscCall(MatSetBlockSizes(B, A->rmap->bs, A->cmap->bs));
2826     PetscCall(MatSeqAIJSetPreallocation(B, 0, NULL));
2827     PetscCall(MatMPIAIJSetPreallocation(B, 0, NULL, 0, NULL));
2828   }
2829   b = (Mat_MPIAIJ *)B->data;
2830 
2831   if (reuse == MAT_REUSE_MATRIX) {
2832     PetscCall(MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A));
2833     PetscCall(MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B));
2834   } else {
2835     PetscInt   *garray = a->garray;
2836     Mat_SeqAIJ *bB;
2837     PetscInt    bs, nnz;
2838     PetscCall(MatDestroy(&b->A));
2839     PetscCall(MatDestroy(&b->B));
2840     /* just clear out the data structure */
2841     PetscCall(MatDisAssemble_MPIAIJ(B));
2842     PetscCall(MatConvert_SeqBAIJ_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A));
2843     PetscCall(MatConvert_SeqBAIJ_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B));
2844 
2845     /* Global numbering for b->B columns */
2846     bB  = (Mat_SeqAIJ *)b->B->data;
2847     bs  = A->rmap->bs;
2848     nnz = bB->i[A->rmap->n];
2849     for (PetscInt k = 0; k < nnz; k++) {
2850       PetscInt bj = bB->j[k] / bs;
2851       PetscInt br = bB->j[k] % bs;
2852       bB->j[k]    = garray[bj] * bs + br;
2853     }
2854   }
2855   PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
2856   PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
2857 
2858   if (reuse == MAT_INPLACE_MATRIX) {
2859     PetscCall(MatHeaderReplace(A, &B));
2860   } else {
2861     *newmat = B;
2862   }
2863   PetscFunctionReturn(PETSC_SUCCESS);
2864 }
2865 
2866 /*MC
2867    MATMPIBAIJ - MATMPIBAIJ = "mpibaij" - A matrix type to be used for distributed block sparse matrices.
2868 
2869    Options Database Keys:
2870 + -mat_type mpibaij - sets the matrix type to `MATMPIBAIJ` during a call to `MatSetFromOptions()`
2871 . -mat_block_size <bs> - set the blocksize used to store the matrix
2872 . -mat_baij_mult_version version - indicate the version of the matrix-vector product to use  (0 often indicates using BLAS)
2873 - -mat_use_hash_table <fact> - set hash table factor
2874 
2875    Level: beginner
2876 
2877    Note:
2878     `MatSetOption(A, MAT_STRUCTURE_ONLY, PETSC_TRUE)` may be called for this matrix type. In this no
2879     space is allocated for the nonzero entries and any entries passed with `MatSetValues()` are ignored
2880 
2881 .seealso: `Mat`, `MATBAIJ`, `MATSEQBAIJ`, `MatCreateBAIJ`
2882 M*/
2883 
2884 PETSC_INTERN PetscErrorCode MatConvert_MPIBAIJ_MPIBSTRM(Mat, MatType, MatReuse, Mat *);
2885 
2886 PETSC_EXTERN PetscErrorCode MatCreate_MPIBAIJ(Mat B)
2887 {
2888   Mat_MPIBAIJ *b;
2889   PetscBool    flg = PETSC_FALSE;
2890 
2891   PetscFunctionBegin;
2892   PetscCall(PetscNew(&b));
2893   B->data      = (void *)b;
2894   B->ops[0]    = MatOps_Values;
2895   B->assembled = PETSC_FALSE;
2896 
2897   B->insertmode = NOT_SET_VALUES;
2898   PetscCallMPI(MPI_Comm_rank(PetscObjectComm((PetscObject)B), &b->rank));
2899   PetscCallMPI(MPI_Comm_size(PetscObjectComm((PetscObject)B), &b->size));
2900 
2901   /* build local table of row and column ownerships */
2902   PetscCall(PetscMalloc1(b->size + 1, &b->rangebs));
2903 
2904   /* build cache for off array entries formed */
2905   PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)B), 1, &B->stash));
2906 
2907   b->donotstash  = PETSC_FALSE;
2908   b->colmap      = NULL;
2909   b->garray      = NULL;
2910   b->roworiented = PETSC_TRUE;
2911 
2912   /* stuff used in block assembly */
2913   b->barray = NULL;
2914 
2915   /* stuff used for matrix vector multiply */
2916   b->lvec  = NULL;
2917   b->Mvctx = NULL;
2918 
2919   /* stuff for MatGetRow() */
2920   b->rowindices   = NULL;
2921   b->rowvalues    = NULL;
2922   b->getrowactive = PETSC_FALSE;
2923 
2924   /* hash table stuff */
2925   b->ht           = NULL;
2926   b->hd           = NULL;
2927   b->ht_size      = 0;
2928   b->ht_flag      = PETSC_FALSE;
2929   b->ht_fact      = 0;
2930   b->ht_total_ct  = 0;
2931   b->ht_insert_ct = 0;
2932 
2933   /* stuff for MatCreateSubMatrices_MPIBAIJ_local() */
2934   b->ijonly = PETSC_FALSE;
2935 
2936   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpibaij_mpiadj_C", MatConvert_MPIBAIJ_MPIAdj));
2937   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpibaij_mpiaij_C", MatConvert_MPIBAIJ_MPIAIJ));
2938   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpibaij_mpisbaij_C", MatConvert_MPIBAIJ_MPISBAIJ));
2939 #if defined(PETSC_HAVE_HYPRE)
2940   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpibaij_hypre_C", MatConvert_AIJ_HYPRE));
2941 #endif
2942   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatStoreValues_C", MatStoreValues_MPIBAIJ));
2943   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatRetrieveValues_C", MatRetrieveValues_MPIBAIJ));
2944   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPIBAIJSetPreallocation_C", MatMPIBAIJSetPreallocation_MPIBAIJ));
2945   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatMPIBAIJSetPreallocationCSR_C", MatMPIBAIJSetPreallocationCSR_MPIBAIJ));
2946   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatDiagonalScaleLocal_C", MatDiagonalScaleLocal_MPIBAIJ));
2947   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatSetHashTableFactor_C", MatSetHashTableFactor_MPIBAIJ));
2948   PetscCall(PetscObjectComposeFunction((PetscObject)B, "MatConvert_mpibaij_is_C", MatConvert_XAIJ_IS));
2949   PetscCall(PetscObjectChangeTypeName((PetscObject)B, MATMPIBAIJ));
2950 
2951   PetscOptionsBegin(PetscObjectComm((PetscObject)B), NULL, "Options for loading MPIBAIJ matrix 1", "Mat");
2952   PetscCall(PetscOptionsName("-mat_use_hash_table", "Use hash table to save time in constructing matrix", "MatSetOption", &flg));
2953   if (flg) {
2954     PetscReal fact = 1.39;
2955     PetscCall(MatSetOption(B, MAT_USE_HASH_TABLE, PETSC_TRUE));
2956     PetscCall(PetscOptionsReal("-mat_use_hash_table", "Use hash table factor", "MatMPIBAIJSetHashTableFactor", fact, &fact, NULL));
2957     if (fact <= 1.0) fact = 1.39;
2958     PetscCall(MatMPIBAIJSetHashTableFactor(B, fact));
2959     PetscCall(PetscInfo(B, "Hash table Factor used %5.2g\n", (double)fact));
2960   }
2961   PetscOptionsEnd();
2962   PetscFunctionReturn(PETSC_SUCCESS);
2963 }
2964 
2965 // PetscClangLinter pragma disable: -fdoc-section-header-unknown
2966 /*MC
2967    MATBAIJ - MATBAIJ = "baij" - A matrix type to be used for block sparse matrices.
2968 
2969    This matrix type is identical to `MATSEQBAIJ` when constructed with a single process communicator,
2970    and `MATMPIBAIJ` otherwise.
2971 
2972    Options Database Keys:
2973 . -mat_type baij - sets the matrix type to `MATBAIJ` during a call to `MatSetFromOptions()`
2974 
2975   Level: beginner
2976 
2977 .seealso: `Mat`, `MatCreateBAIJ()`, `MATSEQBAIJ`, `MATMPIBAIJ`, `MatMPIBAIJSetPreallocation()`, `MatMPIBAIJSetPreallocationCSR()`
2978 M*/
2979 
2980 /*@
2981   MatMPIBAIJSetPreallocation - Allocates memory for a sparse parallel matrix in `MATMPIBAIJ` format
2982   (block compressed row).
2983 
2984   Collective
2985 
2986   Input Parameters:
2987 + B     - the matrix
2988 . bs    - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
2989           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
2990 . d_nz  - number of block nonzeros per block row in diagonal portion of local
2991            submatrix  (same for all local rows)
2992 . d_nnz - array containing the number of block nonzeros in the various block rows
2993            of the in diagonal portion of the local (possibly different for each block
2994            row) or `NULL`.  If you plan to factor the matrix you must leave room for the diagonal entry and
2995            set it even if it is zero.
2996 . o_nz  - number of block nonzeros per block row in the off-diagonal portion of local
2997            submatrix (same for all local rows).
2998 - o_nnz - array containing the number of nonzeros in the various block rows of the
2999            off-diagonal portion of the local submatrix (possibly different for
3000            each block row) or `NULL`.
3001 
3002    If the *_nnz parameter is given then the *_nz parameter is ignored
3003 
3004   Options Database Keys:
3005 + -mat_block_size            - size of the blocks to use
3006 - -mat_use_hash_table <fact> - set hash table factor
3007 
3008   Level: intermediate
3009 
3010   Notes:
3011   For good matrix assembly performance
3012   the user should preallocate the matrix storage by setting the parameters
3013   `d_nz` (or `d_nnz`) and `o_nz` (or `o_nnz`).  By setting these parameters accurately,
3014   performance can be increased by more than a factor of 50.
3015 
3016   If `PETSC_DECIDE` or  `PETSC_DETERMINE` is used for a particular argument on one processor
3017   than it must be used on all processors that share the object for that argument.
3018 
3019   Storage Information:
3020   For a square global matrix we define each processor's diagonal portion
3021   to be its local rows and the corresponding columns (a square submatrix);
3022   each processor's off-diagonal portion encompasses the remainder of the
3023   local matrix (a rectangular submatrix).
3024 
3025   The user can specify preallocated storage for the diagonal part of
3026   the local submatrix with either `d_nz` or `d_nnz` (not both).  Set
3027   `d_nz` = `PETSC_DEFAULT` and `d_nnz` = `NULL` for PETSc to control dynamic
3028   memory allocation.  Likewise, specify preallocated storage for the
3029   off-diagonal part of the local submatrix with `o_nz` or `o_nnz` (not both).
3030 
3031   Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3032   the figure below we depict these three local rows and all columns (0-11).
3033 
3034 .vb
3035            0 1 2 3 4 5 6 7 8 9 10 11
3036           --------------------------
3037    row 3  |o o o d d d o o o o  o  o
3038    row 4  |o o o d d d o o o o  o  o
3039    row 5  |o o o d d d o o o o  o  o
3040           --------------------------
3041 .ve
3042 
3043   Thus, any entries in the d locations are stored in the d (diagonal)
3044   submatrix, and any entries in the o locations are stored in the
3045   o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3046   stored simply in the `MATSEQBAIJ` format for compressed row storage.
3047 
3048   Now `d_nz` should indicate the number of block nonzeros per row in the d matrix,
3049   and `o_nz` should indicate the number of block nonzeros per row in the o matrix.
3050   In general, for PDE problems in which most nonzeros are near the diagonal,
3051   one expects `d_nz` >> `o_nz`.
3052 
3053   You can call `MatGetInfo()` to get information on how effective the preallocation was;
3054   for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3055   You can also run with the option `-info` and look for messages with the string
3056   malloc in them to see if additional memory allocation was needed.
3057 
3058 .seealso: `Mat`, `MATMPIBAIJ`, `MatCreate()`, `MatCreateSeqBAIJ()`, `MatSetValues()`, `MatCreateBAIJ()`, `MatMPIBAIJSetPreallocationCSR()`, `PetscSplitOwnership()`
3059 @*/
3060 PetscErrorCode MatMPIBAIJSetPreallocation(Mat B, PetscInt bs, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[])
3061 {
3062   PetscFunctionBegin;
3063   PetscValidHeaderSpecific(B, MAT_CLASSID, 1);
3064   PetscValidType(B, 1);
3065   PetscValidLogicalCollectiveInt(B, bs, 2);
3066   PetscTryMethod(B, "MatMPIBAIJSetPreallocation_C", (Mat, PetscInt, PetscInt, const PetscInt[], PetscInt, const PetscInt[]), (B, bs, d_nz, d_nnz, o_nz, o_nnz));
3067   PetscFunctionReturn(PETSC_SUCCESS);
3068 }
3069 
3070 // PetscClangLinter pragma disable: -fdoc-section-header-unknown
3071 /*@
3072   MatCreateBAIJ - Creates a sparse parallel matrix in `MATBAIJ` format
3073   (block compressed row).
3074 
3075   Collective
3076 
3077   Input Parameters:
3078 + comm  - MPI communicator
3079 . bs    - size of block, the blocks are ALWAYS square. One can use `MatSetBlockSizes()` to set a different row and column blocksize but the row
3080           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with `MatCreateVecs()`
3081 . m     - number of local rows (or `PETSC_DECIDE` to have calculated if M is given)
3082           This value should be the same as the local size used in creating the
3083           y vector for the matrix-vector product y = Ax.
3084 . n     - number of local columns (or `PETSC_DECIDE` to have calculated if N is given)
3085           This value should be the same as the local size used in creating the
3086           x vector for the matrix-vector product y = Ax.
3087 . M     - number of global rows (or `PETSC_DETERMINE` to have calculated if m is given)
3088 . N     - number of global columns (or `PETSC_DETERMINE` to have calculated if n is given)
3089 . d_nz  - number of nonzero blocks per block row in diagonal portion of local
3090           submatrix  (same for all local rows)
3091 . d_nnz - array containing the number of nonzero blocks in the various block rows
3092           of the in diagonal portion of the local (possibly different for each block
3093           row) or NULL.  If you plan to factor the matrix you must leave room for the diagonal entry
3094           and set it even if it is zero.
3095 . o_nz  - number of nonzero blocks per block row in the off-diagonal portion of local
3096           submatrix (same for all local rows).
3097 - o_nnz - array containing the number of nonzero blocks in the various block rows of the
3098           off-diagonal portion of the local submatrix (possibly different for
3099           each block row) or NULL.
3100 
3101   Output Parameter:
3102 . A - the matrix
3103 
3104   Options Database Keys:
3105 + -mat_block_size            - size of the blocks to use
3106 - -mat_use_hash_table <fact> - set hash table factor
3107 
3108   Level: intermediate
3109 
3110   Notes:
3111   It is recommended that one use `MatCreateFromOptions()` or the `MatCreate()`, `MatSetType()` and/or `MatSetFromOptions()`,
3112   MatXXXXSetPreallocation() paradigm instead of this routine directly.
3113   [MatXXXXSetPreallocation() is, for example, `MatSeqBAIJSetPreallocation()`]
3114 
3115   For good matrix assembly performance
3116   the user should preallocate the matrix storage by setting the parameters
3117   `d_nz` (or `d_nnz`) and `o_nz` (or `o_nnz`).  By setting these parameters accurately,
3118   performance can be increased by more than a factor of 50.
3119 
3120   If the *_nnz parameter is given then the *_nz parameter is ignored
3121 
3122   A nonzero block is any block that as 1 or more nonzeros in it
3123 
3124   The user MUST specify either the local or global matrix dimensions
3125   (possibly both).
3126 
3127   If `PETSC_DECIDE` or  `PETSC_DETERMINE` is used for a particular argument on one processor
3128   than it must be used on all processors that share the object for that argument.
3129 
3130   If `m` and `n` are not `PETSC_DECIDE`, then the values determine the `PetscLayout` of the matrix and the ranges returned by
3131   `MatGetOwnershipRange()`,  `MatGetOwnershipRanges()`, `MatGetOwnershipRangeColumn()`, and `MatGetOwnershipRangesColumn()`.
3132 
3133   Storage Information:
3134   For a square global matrix we define each processor's diagonal portion
3135   to be its local rows and the corresponding columns (a square submatrix);
3136   each processor's off-diagonal portion encompasses the remainder of the
3137   local matrix (a rectangular submatrix).
3138 
3139   The user can specify preallocated storage for the diagonal part of
3140   the local submatrix with either d_nz or d_nnz (not both).  Set
3141   `d_nz` = `PETSC_DEFAULT` and `d_nnz` = `NULL` for PETSc to control dynamic
3142   memory allocation.  Likewise, specify preallocated storage for the
3143   off-diagonal part of the local submatrix with `o_nz` or `o_nnz` (not both).
3144 
3145   Consider a processor that owns rows 3, 4 and 5 of a parallel matrix. In
3146   the figure below we depict these three local rows and all columns (0-11).
3147 
3148 .vb
3149            0 1 2 3 4 5 6 7 8 9 10 11
3150           --------------------------
3151    row 3  |o o o d d d o o o o  o  o
3152    row 4  |o o o d d d o o o o  o  o
3153    row 5  |o o o d d d o o o o  o  o
3154           --------------------------
3155 .ve
3156 
3157   Thus, any entries in the d locations are stored in the d (diagonal)
3158   submatrix, and any entries in the o locations are stored in the
3159   o (off-diagonal) submatrix.  Note that the d and the o submatrices are
3160   stored simply in the `MATSEQBAIJ` format for compressed row storage.
3161 
3162   Now `d_nz` should indicate the number of block nonzeros per row in the d matrix,
3163   and `o_nz` should indicate the number of block nonzeros per row in the o matrix.
3164   In general, for PDE problems in which most nonzeros are near the diagonal,
3165   one expects `d_nz` >> `o_nz`.
3166 
3167 .seealso: `Mat`, `MatCreate()`, `MatCreateSeqBAIJ()`, `MatSetValues()`, `MatMPIBAIJSetPreallocation()`, `MatMPIBAIJSetPreallocationCSR()`,
3168           `MatGetOwnershipRange()`,  `MatGetOwnershipRanges()`, `MatGetOwnershipRangeColumn()`, `MatGetOwnershipRangesColumn()`, `PetscLayout`
3169 @*/
3170 PetscErrorCode MatCreateBAIJ(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt M, PetscInt N, PetscInt d_nz, const PetscInt d_nnz[], PetscInt o_nz, const PetscInt o_nnz[], Mat *A)
3171 {
3172   PetscMPIInt size;
3173 
3174   PetscFunctionBegin;
3175   PetscCall(MatCreate(comm, A));
3176   PetscCall(MatSetSizes(*A, m, n, M, N));
3177   PetscCallMPI(MPI_Comm_size(comm, &size));
3178   if (size > 1) {
3179     PetscCall(MatSetType(*A, MATMPIBAIJ));
3180     PetscCall(MatMPIBAIJSetPreallocation(*A, bs, d_nz, d_nnz, o_nz, o_nnz));
3181   } else {
3182     PetscCall(MatSetType(*A, MATSEQBAIJ));
3183     PetscCall(MatSeqBAIJSetPreallocation(*A, bs, d_nz, d_nnz));
3184   }
3185   PetscFunctionReturn(PETSC_SUCCESS);
3186 }
3187 
3188 static PetscErrorCode MatDuplicate_MPIBAIJ(Mat matin, MatDuplicateOption cpvalues, Mat *newmat)
3189 {
3190   Mat          mat;
3191   Mat_MPIBAIJ *a, *oldmat = (Mat_MPIBAIJ *)matin->data;
3192   PetscInt     len = 0;
3193 
3194   PetscFunctionBegin;
3195   *newmat = NULL;
3196   PetscCall(MatCreate(PetscObjectComm((PetscObject)matin), &mat));
3197   PetscCall(MatSetSizes(mat, matin->rmap->n, matin->cmap->n, matin->rmap->N, matin->cmap->N));
3198   PetscCall(MatSetType(mat, ((PetscObject)matin)->type_name));
3199 
3200   PetscCall(PetscLayoutReference(matin->rmap, &mat->rmap));
3201   PetscCall(PetscLayoutReference(matin->cmap, &mat->cmap));
3202   if (matin->hash_active) {
3203     PetscCall(MatSetUp(mat));
3204   } else {
3205     mat->factortype   = matin->factortype;
3206     mat->preallocated = PETSC_TRUE;
3207     mat->assembled    = PETSC_TRUE;
3208     mat->insertmode   = NOT_SET_VALUES;
3209 
3210     a             = (Mat_MPIBAIJ *)mat->data;
3211     mat->rmap->bs = matin->rmap->bs;
3212     a->bs2        = oldmat->bs2;
3213     a->mbs        = oldmat->mbs;
3214     a->nbs        = oldmat->nbs;
3215     a->Mbs        = oldmat->Mbs;
3216     a->Nbs        = oldmat->Nbs;
3217 
3218     a->size         = oldmat->size;
3219     a->rank         = oldmat->rank;
3220     a->donotstash   = oldmat->donotstash;
3221     a->roworiented  = oldmat->roworiented;
3222     a->rowindices   = NULL;
3223     a->rowvalues    = NULL;
3224     a->getrowactive = PETSC_FALSE;
3225     a->barray       = NULL;
3226     a->rstartbs     = oldmat->rstartbs;
3227     a->rendbs       = oldmat->rendbs;
3228     a->cstartbs     = oldmat->cstartbs;
3229     a->cendbs       = oldmat->cendbs;
3230 
3231     /* hash table stuff */
3232     a->ht           = NULL;
3233     a->hd           = NULL;
3234     a->ht_size      = 0;
3235     a->ht_flag      = oldmat->ht_flag;
3236     a->ht_fact      = oldmat->ht_fact;
3237     a->ht_total_ct  = 0;
3238     a->ht_insert_ct = 0;
3239 
3240     PetscCall(PetscArraycpy(a->rangebs, oldmat->rangebs, a->size + 1));
3241     if (oldmat->colmap) {
3242 #if defined(PETSC_USE_CTABLE)
3243       PetscCall(PetscHMapIDuplicate(oldmat->colmap, &a->colmap));
3244 #else
3245       PetscCall(PetscMalloc1(a->Nbs, &a->colmap));
3246       PetscCall(PetscArraycpy(a->colmap, oldmat->colmap, a->Nbs));
3247 #endif
3248     } else a->colmap = NULL;
3249 
3250     if (oldmat->garray && (len = ((Mat_SeqBAIJ *)oldmat->B->data)->nbs)) {
3251       PetscCall(PetscMalloc1(len, &a->garray));
3252       PetscCall(PetscArraycpy(a->garray, oldmat->garray, len));
3253     } else a->garray = NULL;
3254 
3255     PetscCall(MatStashCreate_Private(PetscObjectComm((PetscObject)matin), matin->rmap->bs, &mat->bstash));
3256     PetscCall(VecDuplicate(oldmat->lvec, &a->lvec));
3257     PetscCall(VecScatterCopy(oldmat->Mvctx, &a->Mvctx));
3258 
3259     PetscCall(MatDuplicate(oldmat->A, cpvalues, &a->A));
3260     PetscCall(MatDuplicate(oldmat->B, cpvalues, &a->B));
3261   }
3262   PetscCall(PetscFunctionListDuplicate(((PetscObject)matin)->qlist, &((PetscObject)mat)->qlist));
3263   *newmat = mat;
3264   PetscFunctionReturn(PETSC_SUCCESS);
3265 }
3266 
3267 /* Used for both MPIBAIJ and MPISBAIJ matrices */
3268 PetscErrorCode MatLoad_MPIBAIJ_Binary(Mat mat, PetscViewer viewer)
3269 {
3270   PetscInt     header[4], M, N, nz, bs, m, n, mbs, nbs, rows, cols, sum, i, j, k;
3271   PetscInt    *rowidxs, *colidxs, rs, cs, ce;
3272   PetscScalar *matvals;
3273 
3274   PetscFunctionBegin;
3275   PetscCall(PetscViewerSetUp(viewer));
3276 
3277   /* read in matrix header */
3278   PetscCall(PetscViewerBinaryRead(viewer, header, 4, NULL, PETSC_INT));
3279   PetscCheck(header[0] == MAT_FILE_CLASSID, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Not a matrix object in file");
3280   M  = header[1];
3281   N  = header[2];
3282   nz = header[3];
3283   PetscCheck(M >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix row size (%" PetscInt_FMT ") in file is negative", M);
3284   PetscCheck(N >= 0, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Matrix column size (%" PetscInt_FMT ") in file is negative", N);
3285   PetscCheck(nz >= 0, PETSC_COMM_SELF, PETSC_ERR_FILE_UNEXPECTED, "Matrix stored in special format on disk, cannot load as MPIBAIJ");
3286 
3287   /* set block sizes from the viewer's .info file */
3288   PetscCall(MatLoad_Binary_BlockSizes(mat, viewer));
3289   /* set local sizes if not set already */
3290   if (mat->rmap->n < 0 && M == N) mat->rmap->n = mat->cmap->n;
3291   if (mat->cmap->n < 0 && M == N) mat->cmap->n = mat->rmap->n;
3292   /* set global sizes if not set already */
3293   if (mat->rmap->N < 0) mat->rmap->N = M;
3294   if (mat->cmap->N < 0) mat->cmap->N = N;
3295   PetscCall(PetscLayoutSetUp(mat->rmap));
3296   PetscCall(PetscLayoutSetUp(mat->cmap));
3297 
3298   /* check if the matrix sizes are correct */
3299   PetscCall(MatGetSize(mat, &rows, &cols));
3300   PetscCheck(M == rows && N == cols, PETSC_COMM_SELF, PETSC_ERR_FILE_UNEXPECTED, "Matrix in file of different sizes (%" PetscInt_FMT ", %" PetscInt_FMT ") than the input matrix (%" PetscInt_FMT ", %" PetscInt_FMT ")", M, N, rows, cols);
3301   PetscCall(MatGetBlockSize(mat, &bs));
3302   PetscCall(MatGetLocalSize(mat, &m, &n));
3303   PetscCall(PetscLayoutGetRange(mat->rmap, &rs, NULL));
3304   PetscCall(PetscLayoutGetRange(mat->cmap, &cs, &ce));
3305   mbs = m / bs;
3306   nbs = n / bs;
3307 
3308   /* read in row lengths and build row indices */
3309   PetscCall(PetscMalloc1(m + 1, &rowidxs));
3310   PetscCall(PetscViewerBinaryReadAll(viewer, rowidxs + 1, m, PETSC_DECIDE, M, PETSC_INT));
3311   rowidxs[0] = 0;
3312   for (i = 0; i < m; i++) rowidxs[i + 1] += rowidxs[i];
3313   PetscCallMPI(MPIU_Allreduce(&rowidxs[m], &sum, 1, MPIU_INT, MPI_SUM, PetscObjectComm((PetscObject)viewer)));
3314   PetscCheck(sum == nz, PetscObjectComm((PetscObject)viewer), PETSC_ERR_FILE_UNEXPECTED, "Inconsistent matrix data in file: nonzeros = %" PetscInt_FMT ", sum-row-lengths = %" PetscInt_FMT, nz, sum);
3315 
3316   /* read in column indices and matrix values */
3317   PetscCall(PetscMalloc2(rowidxs[m], &colidxs, rowidxs[m], &matvals));
3318   PetscCall(PetscViewerBinaryReadAll(viewer, colidxs, rowidxs[m], PETSC_DETERMINE, PETSC_DETERMINE, PETSC_INT));
3319   PetscCall(PetscViewerBinaryReadAll(viewer, matvals, rowidxs[m], PETSC_DETERMINE, PETSC_DETERMINE, PETSC_SCALAR));
3320 
3321   {                /* preallocate matrix storage */
3322     PetscBT    bt; /* helper bit set to count diagonal nonzeros */
3323     PetscHSetI ht; /* helper hash set to count off-diagonal nonzeros */
3324     PetscBool  sbaij, done;
3325     PetscInt  *d_nnz, *o_nnz;
3326 
3327     PetscCall(PetscBTCreate(nbs, &bt));
3328     PetscCall(PetscHSetICreate(&ht));
3329     PetscCall(PetscCalloc2(mbs, &d_nnz, mbs, &o_nnz));
3330     PetscCall(PetscObjectTypeCompare((PetscObject)mat, MATMPISBAIJ, &sbaij));
3331     for (i = 0; i < mbs; i++) {
3332       PetscCall(PetscBTMemzero(nbs, bt));
3333       PetscCall(PetscHSetIClear(ht));
3334       for (k = 0; k < bs; k++) {
3335         PetscInt row = bs * i + k;
3336         for (j = rowidxs[row]; j < rowidxs[row + 1]; j++) {
3337           PetscInt col = colidxs[j];
3338           if (!sbaij || col >= row) {
3339             if (col >= cs && col < ce) {
3340               if (!PetscBTLookupSet(bt, (col - cs) / bs)) d_nnz[i]++;
3341             } else {
3342               PetscCall(PetscHSetIQueryAdd(ht, col / bs, &done));
3343               if (done) o_nnz[i]++;
3344             }
3345           }
3346         }
3347       }
3348     }
3349     PetscCall(PetscBTDestroy(&bt));
3350     PetscCall(PetscHSetIDestroy(&ht));
3351     PetscCall(MatMPIBAIJSetPreallocation(mat, bs, 0, d_nnz, 0, o_nnz));
3352     PetscCall(MatMPISBAIJSetPreallocation(mat, bs, 0, d_nnz, 0, o_nnz));
3353     PetscCall(PetscFree2(d_nnz, o_nnz));
3354   }
3355 
3356   /* store matrix values */
3357   for (i = 0; i < m; i++) {
3358     PetscInt row = rs + i, s = rowidxs[i], e = rowidxs[i + 1];
3359     PetscUseTypeMethod(mat, setvalues, 1, &row, e - s, colidxs + s, matvals + s, INSERT_VALUES);
3360   }
3361 
3362   PetscCall(PetscFree(rowidxs));
3363   PetscCall(PetscFree2(colidxs, matvals));
3364   PetscCall(MatAssemblyBegin(mat, MAT_FINAL_ASSEMBLY));
3365   PetscCall(MatAssemblyEnd(mat, MAT_FINAL_ASSEMBLY));
3366   PetscFunctionReturn(PETSC_SUCCESS);
3367 }
3368 
3369 PetscErrorCode MatLoad_MPIBAIJ(Mat mat, PetscViewer viewer)
3370 {
3371   PetscBool isbinary;
3372 
3373   PetscFunctionBegin;
3374   PetscCall(PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERBINARY, &isbinary));
3375   PetscCheck(isbinary, PetscObjectComm((PetscObject)viewer), PETSC_ERR_SUP, "Viewer type %s not yet supported for reading %s matrices", ((PetscObject)viewer)->type_name, ((PetscObject)mat)->type_name);
3376   PetscCall(MatLoad_MPIBAIJ_Binary(mat, viewer));
3377   PetscFunctionReturn(PETSC_SUCCESS);
3378 }
3379 
3380 /*@
3381   MatMPIBAIJSetHashTableFactor - Sets the factor required to compute the size of the matrices hash table
3382 
3383   Input Parameters:
3384 + mat  - the matrix
3385 - fact - factor
3386 
3387   Options Database Key:
3388 . -mat_use_hash_table <fact> - provide the factor
3389 
3390   Level: advanced
3391 
3392 .seealso: `Mat`, `MATMPIBAIJ`, `MatSetOption()`
3393 @*/
3394 PetscErrorCode MatMPIBAIJSetHashTableFactor(Mat mat, PetscReal fact)
3395 {
3396   PetscFunctionBegin;
3397   PetscTryMethod(mat, "MatSetHashTableFactor_C", (Mat, PetscReal), (mat, fact));
3398   PetscFunctionReturn(PETSC_SUCCESS);
3399 }
3400 
3401 PetscErrorCode MatSetHashTableFactor_MPIBAIJ(Mat mat, PetscReal fact)
3402 {
3403   Mat_MPIBAIJ *baij;
3404 
3405   PetscFunctionBegin;
3406   baij          = (Mat_MPIBAIJ *)mat->data;
3407   baij->ht_fact = fact;
3408   PetscFunctionReturn(PETSC_SUCCESS);
3409 }
3410 
3411 PetscErrorCode MatMPIBAIJGetSeqBAIJ(Mat A, Mat *Ad, Mat *Ao, const PetscInt *colmap[])
3412 {
3413   Mat_MPIBAIJ *a = (Mat_MPIBAIJ *)A->data;
3414   PetscBool    flg;
3415 
3416   PetscFunctionBegin;
3417   PetscCall(PetscObjectTypeCompare((PetscObject)A, MATMPIBAIJ, &flg));
3418   PetscCheck(flg, PetscObjectComm((PetscObject)A), PETSC_ERR_SUP, "This function requires a MATMPIBAIJ matrix as input");
3419   if (Ad) *Ad = a->A;
3420   if (Ao) *Ao = a->B;
3421   if (colmap) *colmap = a->garray;
3422   PetscFunctionReturn(PETSC_SUCCESS);
3423 }
3424 
3425 /*
3426     Special version for direct calls from Fortran (to eliminate two function call overheads
3427 */
3428 #if defined(PETSC_HAVE_FORTRAN_CAPS)
3429   #define matmpibaijsetvaluesblocked_ MATMPIBAIJSETVALUESBLOCKED
3430 #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
3431   #define matmpibaijsetvaluesblocked_ matmpibaijsetvaluesblocked
3432 #endif
3433 
3434 // PetscClangLinter pragma disable: -fdoc-synopsis-matching-symbol-name
3435 /*@C
3436   MatMPIBAIJSetValuesBlocked - Direct Fortran call to replace call to `MatSetValuesBlocked()`
3437 
3438   Collective
3439 
3440   Input Parameters:
3441 + matin  - the matrix
3442 . min    - number of input rows
3443 . im     - input rows
3444 . nin    - number of input columns
3445 . in     - input columns
3446 . v      - numerical values input
3447 - addvin - `INSERT_VALUES` or `ADD_VALUES`
3448 
3449   Level: advanced
3450 
3451   Developer Notes:
3452   This has a complete copy of `MatSetValuesBlocked_MPIBAIJ()` which is terrible code un-reuse.
3453 
3454 .seealso: `Mat`, `MatSetValuesBlocked()`
3455 @*/
3456 PETSC_EXTERN PetscErrorCode matmpibaijsetvaluesblocked_(Mat *matin, PetscInt *min, const PetscInt im[], PetscInt *nin, const PetscInt in[], const MatScalar v[], InsertMode *addvin)
3457 {
3458   /* convert input arguments to C version */
3459   Mat        mat = *matin;
3460   PetscInt   m = *min, n = *nin;
3461   InsertMode addv = *addvin;
3462 
3463   Mat_MPIBAIJ     *baij = (Mat_MPIBAIJ *)mat->data;
3464   const MatScalar *value;
3465   MatScalar       *barray      = baij->barray;
3466   PetscBool        roworiented = baij->roworiented;
3467   PetscInt         i, j, ii, jj, row, col, rstart = baij->rstartbs;
3468   PetscInt         rend = baij->rendbs, cstart = baij->cstartbs, stepval;
3469   PetscInt         cend = baij->cendbs, bs = mat->rmap->bs, bs2 = baij->bs2;
3470 
3471   PetscFunctionBegin;
3472   /* tasks normally handled by MatSetValuesBlocked() */
3473   if (mat->insertmode == NOT_SET_VALUES) mat->insertmode = addv;
3474   else PetscCheck(mat->insertmode == addv, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Cannot mix add values and insert values");
3475   PetscCheck(!mat->factortype, PETSC_COMM_SELF, PETSC_ERR_ARG_WRONGSTATE, "Not for factored matrix");
3476   if (mat->assembled) {
3477     mat->was_assembled = PETSC_TRUE;
3478     mat->assembled     = PETSC_FALSE;
3479   }
3480   PetscCall(PetscLogEventBegin(MAT_SetValues, mat, 0, 0, 0));
3481 
3482   if (!barray) {
3483     PetscCall(PetscMalloc1(bs2, &barray));
3484     baij->barray = barray;
3485   }
3486 
3487   if (roworiented) stepval = (n - 1) * bs;
3488   else stepval = (m - 1) * bs;
3489 
3490   for (i = 0; i < m; i++) {
3491     if (im[i] < 0) continue;
3492     PetscCheck(im[i] < baij->Mbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Row too large, row %" PetscInt_FMT " max %" PetscInt_FMT, im[i], baij->Mbs - 1);
3493     if (im[i] >= rstart && im[i] < rend) {
3494       row = im[i] - rstart;
3495       for (j = 0; j < n; j++) {
3496         /* If NumCol = 1 then a copy is not required */
3497         if ((roworiented) && (n == 1)) {
3498           barray = (MatScalar *)v + i * bs2;
3499         } else if ((!roworiented) && (m == 1)) {
3500           barray = (MatScalar *)v + j * bs2;
3501         } else { /* Here a copy is required */
3502           if (roworiented) {
3503             value = v + i * (stepval + bs) * bs + j * bs;
3504           } else {
3505             value = v + j * (stepval + bs) * bs + i * bs;
3506           }
3507           for (ii = 0; ii < bs; ii++, value += stepval) {
3508             for (jj = 0; jj < bs; jj++) *barray++ = *value++;
3509           }
3510           barray -= bs2;
3511         }
3512 
3513         if (in[j] >= cstart && in[j] < cend) {
3514           col = in[j] - cstart;
3515           PetscCall(MatSetValuesBlocked_SeqBAIJ_Inlined(baij->A, row, col, barray, addv, im[i], in[j]));
3516         } else if (in[j] < 0) {
3517           continue;
3518         } else {
3519           PetscCheck(in[j] < baij->Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "Column too large, col %" PetscInt_FMT " max %" PetscInt_FMT, in[j], baij->Nbs - 1);
3520           if (mat->was_assembled) {
3521             if (!baij->colmap) PetscCall(MatCreateColmap_MPIBAIJ_Private(mat));
3522 
3523 #if defined(PETSC_USE_DEBUG)
3524   #if defined(PETSC_USE_CTABLE)
3525             {
3526               PetscInt data;
3527               PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] + 1, 0, &data));
3528               PetscCheck((data - 1) % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Incorrect colmap");
3529             }
3530   #else
3531             PetscCheck((baij->colmap[in[j]] - 1) % bs == 0, PETSC_COMM_SELF, PETSC_ERR_PLIB, "Incorrect colmap");
3532   #endif
3533 #endif
3534 #if defined(PETSC_USE_CTABLE)
3535             PetscCall(PetscHMapIGetWithDefault(baij->colmap, in[j] + 1, 0, &col));
3536             col = (col - 1) / bs;
3537 #else
3538             col = (baij->colmap[in[j]] - 1) / bs;
3539 #endif
3540             if (col < 0 && !((Mat_SeqBAIJ *)baij->A->data)->nonew) {
3541               PetscCall(MatDisAssemble_MPIBAIJ(mat));
3542               col = in[j];
3543             }
3544           } else col = in[j];
3545           PetscCall(MatSetValuesBlocked_SeqBAIJ_Inlined(baij->B, row, col, barray, addv, im[i], in[j]));
3546         }
3547       }
3548     } else {
3549       if (!baij->donotstash) {
3550         if (roworiented) {
3551           PetscCall(MatStashValuesRowBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
3552         } else {
3553           PetscCall(MatStashValuesColBlocked_Private(&mat->bstash, im[i], n, in, v, m, n, i));
3554         }
3555       }
3556     }
3557   }
3558 
3559   /* task normally handled by MatSetValuesBlocked() */
3560   PetscCall(PetscLogEventEnd(MAT_SetValues, mat, 0, 0, 0));
3561   PetscFunctionReturn(PETSC_SUCCESS);
3562 }
3563 
3564 /*@
3565   MatCreateMPIBAIJWithArrays - creates a `MATMPIBAIJ` matrix using arrays that contain in standard block CSR format for the local rows.
3566 
3567   Collective
3568 
3569   Input Parameters:
3570 + comm - MPI communicator
3571 . bs   - the block size, only a block size of 1 is supported
3572 . m    - number of local rows (Cannot be `PETSC_DECIDE`)
3573 . n    - This value should be the same as the local size used in creating the
3574          x vector for the matrix-vector product $ y = Ax $. (or `PETSC_DECIDE` to have
3575          calculated if `N` is given) For square matrices `n` is almost always `m`.
3576 . M    - number of global rows (or `PETSC_DETERMINE` to have calculated if `m` is given)
3577 . N    - number of global columns (or `PETSC_DETERMINE` to have calculated if `n` is given)
3578 . i    - row indices; that is i[0] = 0, i[row] = i[row-1] + number of block elements in that rowth block row of the matrix
3579 . j    - column indices
3580 - a    - matrix values
3581 
3582   Output Parameter:
3583 . mat - the matrix
3584 
3585   Level: intermediate
3586 
3587   Notes:
3588   The `i`, `j`, and `a` arrays ARE copied by this routine into the internal format used by PETSc;
3589   thus you CANNOT change the matrix entries by changing the values of a[] after you have
3590   called this routine. Use `MatCreateMPIAIJWithSplitArrays()` to avoid needing to copy the arrays.
3591 
3592   The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
3593   the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
3594   block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
3595   with column-major ordering within blocks.
3596 
3597   The `i` and `j` indices are 0 based, and `i` indices are indices corresponding to the local `j` array.
3598 
3599 .seealso: `Mat`, `MatCreate()`, `MatCreateSeqAIJ()`, `MatSetValues()`, `MatMPIAIJSetPreallocation()`, `MatMPIAIJSetPreallocationCSR()`,
3600           `MATMPIAIJ`, `MatCreateAIJ()`, `MatCreateMPIAIJWithSplitArrays()`
3601 @*/
3602 PetscErrorCode MatCreateMPIBAIJWithArrays(MPI_Comm comm, PetscInt bs, PetscInt m, PetscInt n, PetscInt M, PetscInt N, const PetscInt i[], const PetscInt j[], const PetscScalar a[], Mat *mat)
3603 {
3604   PetscFunctionBegin;
3605   PetscCheck(!i[0], PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "i (row indices) must start with 0");
3606   PetscCheck(m >= 0, PETSC_COMM_SELF, PETSC_ERR_ARG_OUTOFRANGE, "local number of rows (m) cannot be PETSC_DECIDE, or negative");
3607   PetscCall(MatCreate(comm, mat));
3608   PetscCall(MatSetSizes(*mat, m, n, M, N));
3609   PetscCall(MatSetType(*mat, MATMPIBAIJ));
3610   PetscCall(MatSetBlockSize(*mat, bs));
3611   PetscCall(MatSetUp(*mat));
3612   PetscCall(MatSetOption(*mat, MAT_ROW_ORIENTED, PETSC_FALSE));
3613   PetscCall(MatMPIBAIJSetPreallocationCSR(*mat, bs, i, j, a));
3614   PetscCall(MatSetOption(*mat, MAT_ROW_ORIENTED, PETSC_TRUE));
3615   PetscFunctionReturn(PETSC_SUCCESS);
3616 }
3617 
3618 PetscErrorCode MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(MPI_Comm comm, Mat inmat, PetscInt n, MatReuse scall, Mat *outmat)
3619 {
3620   PetscInt     m, N, i, rstart, nnz, Ii, bs, cbs;
3621   PetscInt    *indx;
3622   PetscScalar *values;
3623 
3624   PetscFunctionBegin;
3625   PetscCall(MatGetSize(inmat, &m, &N));
3626   if (scall == MAT_INITIAL_MATRIX) { /* symbolic phase */
3627     Mat_SeqBAIJ *a = (Mat_SeqBAIJ *)inmat->data;
3628     PetscInt    *dnz, *onz, mbs, Nbs, nbs;
3629     PetscInt    *bindx, rmax = a->rmax, j;
3630     PetscMPIInt  rank, size;
3631 
3632     PetscCall(MatGetBlockSizes(inmat, &bs, &cbs));
3633     mbs = m / bs;
3634     Nbs = N / cbs;
3635     if (n == PETSC_DECIDE) PetscCall(PetscSplitOwnershipBlock(comm, cbs, &n, &N));
3636     nbs = n / cbs;
3637 
3638     PetscCall(PetscMalloc1(rmax, &bindx));
3639     MatPreallocateBegin(comm, mbs, nbs, dnz, onz); /* inline function, output __end and __rstart are used below */
3640 
3641     PetscCallMPI(MPI_Comm_rank(comm, &rank));
3642     PetscCallMPI(MPI_Comm_rank(comm, &size));
3643     if (rank == size - 1) {
3644       /* Check sum(nbs) = Nbs */
3645       PetscCheck(__end == Nbs, PETSC_COMM_SELF, PETSC_ERR_ARG_INCOMP, "Sum of local block columns %" PetscInt_FMT " != global block columns %" PetscInt_FMT, __end, Nbs);
3646     }
3647 
3648     rstart = __rstart; /* block rstart of *outmat; see inline function MatPreallocateBegin */
3649     for (i = 0; i < mbs; i++) {
3650       PetscCall(MatGetRow_SeqBAIJ(inmat, i * bs, &nnz, &indx, NULL)); /* non-blocked nnz and indx */
3651       nnz = nnz / bs;
3652       for (j = 0; j < nnz; j++) bindx[j] = indx[j * bs] / bs;
3653       PetscCall(MatPreallocateSet(i + rstart, nnz, bindx, dnz, onz));
3654       PetscCall(MatRestoreRow_SeqBAIJ(inmat, i * bs, &nnz, &indx, NULL));
3655     }
3656     PetscCall(PetscFree(bindx));
3657 
3658     PetscCall(MatCreate(comm, outmat));
3659     PetscCall(MatSetSizes(*outmat, m, n, PETSC_DETERMINE, PETSC_DETERMINE));
3660     PetscCall(MatSetBlockSizes(*outmat, bs, cbs));
3661     PetscCall(MatSetType(*outmat, MATBAIJ));
3662     PetscCall(MatSeqBAIJSetPreallocation(*outmat, bs, 0, dnz));
3663     PetscCall(MatMPIBAIJSetPreallocation(*outmat, bs, 0, dnz, 0, onz));
3664     MatPreallocateEnd(dnz, onz);
3665     PetscCall(MatSetOption(*outmat, MAT_NO_OFF_PROC_ENTRIES, PETSC_TRUE));
3666   }
3667 
3668   /* numeric phase */
3669   PetscCall(MatGetBlockSizes(inmat, &bs, &cbs));
3670   PetscCall(MatGetOwnershipRange(*outmat, &rstart, NULL));
3671 
3672   for (i = 0; i < m; i++) {
3673     PetscCall(MatGetRow_SeqBAIJ(inmat, i, &nnz, &indx, &values));
3674     Ii = i + rstart;
3675     PetscCall(MatSetValues(*outmat, 1, &Ii, nnz, indx, values, INSERT_VALUES));
3676     PetscCall(MatRestoreRow_SeqBAIJ(inmat, i, &nnz, &indx, &values));
3677   }
3678   PetscCall(MatAssemblyBegin(*outmat, MAT_FINAL_ASSEMBLY));
3679   PetscCall(MatAssemblyEnd(*outmat, MAT_FINAL_ASSEMBLY));
3680   PetscFunctionReturn(PETSC_SUCCESS);
3681 }
3682