Actual source code: baij.c

petsc-3.11.1 2019-04-17
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  2: /*
  3:     Defines the basic matrix operations for the BAIJ (compressed row)
  4:   matrix storage format.
  5: */
  6:  #include <../src/mat/impls/baij/seq/baij.h>
  7:  #include <petscblaslapack.h>
  8:  #include <petsc/private/kernels/blockinvert.h>
  9:  #include <petsc/private/kernels/blockmatmult.h>

 11: #if defined(PETSC_HAVE_HYPRE)
 12: PETSC_INTERN PetscErrorCode MatConvert_AIJ_HYPRE(Mat,MatType,MatReuse,Mat*);
 13: #endif

 15: #if defined(PETSC_HAVE_MKL_SPARSE_OPTIMIZE)
 16: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBAIJMKL(Mat,MatType,MatReuse,Mat*);
 17: #endif
 18: PETSC_INTERN PetscErrorCode MatConvert_XAIJ_IS(Mat,MatType,MatReuse,Mat*);
 19: PETSC_INTERN PetscErrorCode MatPtAP_IS_XAIJ(Mat,Mat,MatReuse,PetscReal,Mat*);

 21: PetscErrorCode MatInvertBlockDiagonal_SeqBAIJ(Mat A,const PetscScalar **values)
 22: {
 23:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*) A->data;
 25:   PetscInt       *diag_offset,i,bs = A->rmap->bs,mbs = a->mbs,ipvt[5],bs2 = bs*bs,*v_pivots;
 26:   MatScalar      *v    = a->a,*odiag,*diag,work[25],*v_work;
 27:   PetscReal      shift = 0.0;
 28:   PetscBool      allowzeropivot,zeropivotdetected=PETSC_FALSE;

 31:   allowzeropivot = PetscNot(A->erroriffailure);

 33:   if (a->idiagvalid) {
 34:     if (values) *values = a->idiag;
 35:     return(0);
 36:   }
 37:   MatMarkDiagonal_SeqBAIJ(A);
 38:   diag_offset = a->diag;
 39:   if (!a->idiag) {
 40:     PetscMalloc1(bs2*mbs,&a->idiag);
 41:     PetscLogObjectMemory((PetscObject)A,bs2*mbs*sizeof(PetscScalar));
 42:   }
 43:   diag  = a->idiag;
 44:   if (values) *values = a->idiag;
 45:   /* factor and invert each block */
 46:   switch (bs) {
 47:   case 1:
 48:     for (i=0; i<mbs; i++) {
 49:       odiag    = v + 1*diag_offset[i];
 50:       diag[0]  = odiag[0];

 52:       if (PetscAbsScalar(diag[0] + shift) < PETSC_MACHINE_EPSILON) {
 53:         if (allowzeropivot) {
 54:           A->factorerrortype             = MAT_FACTOR_NUMERIC_ZEROPIVOT;
 55:           A->factorerror_zeropivot_value = PetscAbsScalar(diag[0]);
 56:           A->factorerror_zeropivot_row   = i;
 57:           PetscInfo1(A,"Zero pivot, row %D\n",i);
 58:         } else SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_MAT_LU_ZRPVT,"Zero pivot, row %D pivot value %g tolerance %g",i,(double)PetscAbsScalar(diag[0]),(double)PETSC_MACHINE_EPSILON);
 59:       }

 61:       diag[0]  = (PetscScalar)1.0 / (diag[0] + shift);
 62:       diag    += 1;
 63:     }
 64:     break;
 65:   case 2:
 66:     for (i=0; i<mbs; i++) {
 67:       odiag    = v + 4*diag_offset[i];
 68:       diag[0]  = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
 69:       PetscKernel_A_gets_inverse_A_2(diag,shift,allowzeropivot,&zeropivotdetected);
 70:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
 71:       diag    += 4;
 72:     }
 73:     break;
 74:   case 3:
 75:     for (i=0; i<mbs; i++) {
 76:       odiag    = v + 9*diag_offset[i];
 77:       diag[0]  = odiag[0]; diag[1] = odiag[1]; diag[2] = odiag[2]; diag[3] = odiag[3];
 78:       diag[4]  = odiag[4]; diag[5] = odiag[5]; diag[6] = odiag[6]; diag[7] = odiag[7];
 79:       diag[8]  = odiag[8];
 80:       PetscKernel_A_gets_inverse_A_3(diag,shift,allowzeropivot,&zeropivotdetected);
 81:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
 82:       diag    += 9;
 83:     }
 84:     break;
 85:   case 4:
 86:     for (i=0; i<mbs; i++) {
 87:       odiag  = v + 16*diag_offset[i];
 88:       PetscMemcpy(diag,odiag,16*sizeof(PetscScalar));
 89:       PetscKernel_A_gets_inverse_A_4(diag,shift,allowzeropivot,&zeropivotdetected);
 90:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
 91:       diag  += 16;
 92:     }
 93:     break;
 94:   case 5:
 95:     for (i=0; i<mbs; i++) {
 96:       odiag  = v + 25*diag_offset[i];
 97:       PetscMemcpy(diag,odiag,25*sizeof(PetscScalar));
 98:       PetscKernel_A_gets_inverse_A_5(diag,ipvt,work,shift,allowzeropivot,&zeropivotdetected);
 99:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
100:       diag  += 25;
101:     }
102:     break;
103:   case 6:
104:     for (i=0; i<mbs; i++) {
105:       odiag  = v + 36*diag_offset[i];
106:       PetscMemcpy(diag,odiag,36*sizeof(PetscScalar));
107:       PetscKernel_A_gets_inverse_A_6(diag,shift,allowzeropivot,&zeropivotdetected);
108:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
109:       diag  += 36;
110:     }
111:     break;
112:   case 7:
113:     for (i=0; i<mbs; i++) {
114:       odiag  = v + 49*diag_offset[i];
115:       PetscMemcpy(diag,odiag,49*sizeof(PetscScalar));
116:       PetscKernel_A_gets_inverse_A_7(diag,shift,allowzeropivot,&zeropivotdetected);
117:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
118:       diag  += 49;
119:     }
120:     break;
121:   default:
122:     PetscMalloc2(bs,&v_work,bs,&v_pivots);
123:     for (i=0; i<mbs; i++) {
124:       odiag  = v + bs2*diag_offset[i];
125:       PetscMemcpy(diag,odiag,bs2*sizeof(PetscScalar));
126:       PetscKernel_A_gets_inverse_A(bs,diag,v_pivots,v_work,allowzeropivot,&zeropivotdetected);
127:       if (zeropivotdetected) A->factorerrortype = MAT_FACTOR_NUMERIC_ZEROPIVOT;
128:       diag  += bs2;
129:     }
130:     PetscFree2(v_work,v_pivots);
131:   }
132:   a->idiagvalid = PETSC_TRUE;
133:   return(0);
134: }

136: PetscErrorCode MatSOR_SeqBAIJ(Mat A,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
137: {
138:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
139:   PetscScalar       *x,*work,*w,*workt,*t;
140:   const MatScalar   *v,*aa = a->a, *idiag;
141:   const PetscScalar *b,*xb;
142:   PetscScalar       s[7], xw[7]={0}; /* avoid some compilers thinking xw is uninitialized */
143:   PetscErrorCode    ierr;
144:   PetscInt          m = a->mbs,i,i2,nz,bs = A->rmap->bs,bs2 = bs*bs,k,j,idx,it;
145:   const PetscInt    *diag,*ai = a->i,*aj = a->j,*vi;

148:   its = its*lits;
149:   if (flag & SOR_EISENSTAT) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"No support yet for Eisenstat");
150:   if (its <= 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Relaxation requires global its %D and local its %D both positive",its,lits);
151:   if (fshift) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for diagonal shift");
152:   if (omega != 1.0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for non-trivial relaxation factor");
153:   if ((flag & SOR_APPLY_UPPER) || (flag & SOR_APPLY_LOWER)) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Sorry, no support for applying upper or lower triangular parts");

155:   if (!a->idiagvalid) {MatInvertBlockDiagonal(A,NULL);}

157:   if (!m) return(0);
158:   diag  = a->diag;
159:   idiag = a->idiag;
160:   k    = PetscMax(A->rmap->n,A->cmap->n);
161:   if (!a->mult_work) {
162:     PetscMalloc1(k+1,&a->mult_work);
163:   }
164:   if (!a->sor_workt) {
165:     PetscMalloc1(k,&a->sor_workt);
166:   }
167:   if (!a->sor_work) {
168:     PetscMalloc1(bs,&a->sor_work);
169:   }
170:   work = a->mult_work;
171:   t    = a->sor_workt;
172:   w    = a->sor_work;

174:   VecGetArray(xx,&x);
175:   VecGetArrayRead(bb,&b);

177:   if (flag & SOR_ZERO_INITIAL_GUESS) {
178:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
179:       switch (bs) {
180:       case 1:
181:         PetscKernel_v_gets_A_times_w_1(x,idiag,b);
182:         t[0] = b[0];
183:         i2     = 1;
184:         idiag += 1;
185:         for (i=1; i<m; i++) {
186:           v  = aa + ai[i];
187:           vi = aj + ai[i];
188:           nz = diag[i] - ai[i];
189:           s[0] = b[i2];
190:           for (j=0; j<nz; j++) {
191:             xw[0] = x[vi[j]];
192:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
193:           }
194:           t[i2] = s[0];
195:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
196:           x[i2]  = xw[0];
197:           idiag += 1;
198:           i2    += 1;
199:         }
200:         break;
201:       case 2:
202:         PetscKernel_v_gets_A_times_w_2(x,idiag,b);
203:         t[0] = b[0]; t[1] = b[1];
204:         i2     = 2;
205:         idiag += 4;
206:         for (i=1; i<m; i++) {
207:           v  = aa + 4*ai[i];
208:           vi = aj + ai[i];
209:           nz = diag[i] - ai[i];
210:           s[0] = b[i2]; s[1] = b[i2+1];
211:           for (j=0; j<nz; j++) {
212:             idx = 2*vi[j];
213:             it  = 4*j;
214:             xw[0] = x[idx]; xw[1] = x[1+idx];
215:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
216:           }
217:           t[i2] = s[0]; t[i2+1] = s[1];
218:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
219:           x[i2]   = xw[0]; x[i2+1] = xw[1];
220:           idiag  += 4;
221:           i2     += 2;
222:         }
223:         break;
224:       case 3:
225:         PetscKernel_v_gets_A_times_w_3(x,idiag,b);
226:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
227:         i2     = 3;
228:         idiag += 9;
229:         for (i=1; i<m; i++) {
230:           v  = aa + 9*ai[i];
231:           vi = aj + ai[i];
232:           nz = diag[i] - ai[i];
233:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
234:           while (nz--) {
235:             idx = 3*(*vi++);
236:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
237:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
238:             v  += 9;
239:           }
240:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
241:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
242:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
243:           idiag  += 9;
244:           i2     += 3;
245:         }
246:         break;
247:       case 4:
248:         PetscKernel_v_gets_A_times_w_4(x,idiag,b);
249:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3];
250:         i2     = 4;
251:         idiag += 16;
252:         for (i=1; i<m; i++) {
253:           v  = aa + 16*ai[i];
254:           vi = aj + ai[i];
255:           nz = diag[i] - ai[i];
256:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
257:           while (nz--) {
258:             idx = 4*(*vi++);
259:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
260:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
261:             v  += 16;
262:           }
263:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2 + 3] = s[3];
264:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
265:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
266:           idiag  += 16;
267:           i2     += 4;
268:         }
269:         break;
270:       case 5:
271:         PetscKernel_v_gets_A_times_w_5(x,idiag,b);
272:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4];
273:         i2     = 5;
274:         idiag += 25;
275:         for (i=1; i<m; i++) {
276:           v  = aa + 25*ai[i];
277:           vi = aj + ai[i];
278:           nz = diag[i] - ai[i];
279:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
280:           while (nz--) {
281:             idx = 5*(*vi++);
282:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
283:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
284:             v  += 25;
285:           }
286:           t[i2] = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2]; t[i2+3] = s[3]; t[i2+4] = s[4];
287:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
288:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
289:           idiag  += 25;
290:           i2     += 5;
291:         }
292:         break;
293:       case 6:
294:         PetscKernel_v_gets_A_times_w_6(x,idiag,b);
295:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2]; t[3] = b[3]; t[4] = b[4]; t[5] = b[5];
296:         i2     = 6;
297:         idiag += 36;
298:         for (i=1; i<m; i++) {
299:           v  = aa + 36*ai[i];
300:           vi = aj + ai[i];
301:           nz = diag[i] - ai[i];
302:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5];
303:           while (nz--) {
304:             idx = 6*(*vi++);
305:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
306:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
307:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
308:             v  += 36;
309:           }
310:           t[i2]   = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
311:           t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5];
312:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
313:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5];
314:           idiag  += 36;
315:           i2     += 6;
316:         }
317:         break;
318:       case 7:
319:         PetscKernel_v_gets_A_times_w_7(x,idiag,b);
320:         t[0] = b[0]; t[1] = b[1]; t[2] = b[2];
321:         t[3] = b[3]; t[4] = b[4]; t[5] = b[5]; t[6] = b[6];
322:         i2     = 7;
323:         idiag += 49;
324:         for (i=1; i<m; i++) {
325:           v  = aa + 49*ai[i];
326:           vi = aj + ai[i];
327:           nz = diag[i] - ai[i];
328:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
329:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
330:           while (nz--) {
331:             idx = 7*(*vi++);
332:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
333:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
334:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
335:             v  += 49;
336:           }
337:           t[i2]   = s[0]; t[i2+1] = s[1]; t[i2+2] = s[2];
338:           t[i2+3] = s[3]; t[i2+4] = s[4]; t[i2+5] = s[5]; t[i2+6] = s[6];
339:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
340:           x[i2] =   xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
341:           x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
342:           idiag  += 49;
343:           i2     += 7;
344:         }
345:         break;
346:       default:
347:         PetscKernel_w_gets_Ar_times_v(bs,bs,b,idiag,x);
348:         PetscMemcpy(t,b,bs*sizeof(PetscScalar));
349:         i2     = bs;
350:         idiag += bs2;
351:         for (i=1; i<m; i++) {
352:           v  = aa + bs2*ai[i];
353:           vi = aj + ai[i];
354:           nz = diag[i] - ai[i];

356:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
357:           /* copy all rows of x that are needed into contiguous space */
358:           workt = work;
359:           for (j=0; j<nz; j++) {
360:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
361:             workt += bs;
362:           }
363:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
364:           PetscMemcpy(t+i2,w,bs*sizeof(PetscScalar));
365:           PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);

367:           idiag += bs2;
368:           i2    += bs;
369:         }
370:         break;
371:       }
372:       /* for logging purposes assume number of nonzero in lower half is 1/2 of total */
373:       PetscLogFlops(1.0*bs2*a->nz);
374:       xb = t;
375:     }
376:     else xb = b;
377:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
378:       idiag = a->idiag+bs2*(a->mbs-1);
379:       i2 = bs * (m-1);
380:       switch (bs) {
381:       case 1:
382:         s[0]  = xb[i2];
383:         PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
384:         x[i2] = xw[0];
385:         i2   -= 1;
386:         for (i=m-2; i>=0; i--) {
387:           v  = aa + (diag[i]+1);
388:           vi = aj + diag[i] + 1;
389:           nz = ai[i+1] - diag[i] - 1;
390:           s[0] = xb[i2];
391:           for (j=0; j<nz; j++) {
392:             xw[0] = x[vi[j]];
393:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
394:           }
395:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
396:           x[i2]  = xw[0];
397:           idiag -= 1;
398:           i2    -= 1;
399:         }
400:         break;
401:       case 2:
402:         s[0]  = xb[i2]; s[1] = xb[i2+1];
403:         PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
404:         x[i2] = xw[0]; x[i2+1] = xw[1];
405:         i2    -= 2;
406:         idiag -= 4;
407:         for (i=m-2; i>=0; i--) {
408:           v  = aa + 4*(diag[i] + 1);
409:           vi = aj + diag[i] + 1;
410:           nz = ai[i+1] - diag[i] - 1;
411:           s[0] = xb[i2]; s[1] = xb[i2+1];
412:           for (j=0; j<nz; j++) {
413:             idx = 2*vi[j];
414:             it  = 4*j;
415:             xw[0] = x[idx]; xw[1] = x[1+idx];
416:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
417:           }
418:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
419:           x[i2]   = xw[0]; x[i2+1] = xw[1];
420:           idiag  -= 4;
421:           i2     -= 2;
422:         }
423:         break;
424:       case 3:
425:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
426:         PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
427:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
428:         i2    -= 3;
429:         idiag -= 9;
430:         for (i=m-2; i>=0; i--) {
431:           v  = aa + 9*(diag[i]+1);
432:           vi = aj + diag[i] + 1;
433:           nz = ai[i+1] - diag[i] - 1;
434:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2];
435:           while (nz--) {
436:             idx = 3*(*vi++);
437:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
438:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
439:             v  += 9;
440:           }
441:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
442:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
443:           idiag  -= 9;
444:           i2     -= 3;
445:         }
446:         break;
447:       case 4:
448:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
449:         PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
450:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
451:         i2    -= 4;
452:         idiag -= 16;
453:         for (i=m-2; i>=0; i--) {
454:           v  = aa + 16*(diag[i]+1);
455:           vi = aj + diag[i] + 1;
456:           nz = ai[i+1] - diag[i] - 1;
457:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3];
458:           while (nz--) {
459:             idx = 4*(*vi++);
460:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
461:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
462:             v  += 16;
463:           }
464:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
465:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3];
466:           idiag  -= 16;
467:           i2     -= 4;
468:         }
469:         break;
470:       case 5:
471:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
472:         PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
473:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
474:         i2    -= 5;
475:         idiag -= 25;
476:         for (i=m-2; i>=0; i--) {
477:           v  = aa + 25*(diag[i]+1);
478:           vi = aj + diag[i] + 1;
479:           nz = ai[i+1] - diag[i] - 1;
480:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4];
481:           while (nz--) {
482:             idx = 5*(*vi++);
483:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
484:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
485:             v  += 25;
486:           }
487:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
488:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4];
489:           idiag  -= 25;
490:           i2     -= 5;
491:         }
492:         break;
493:       case 6:
494:         s[0]  = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5];
495:         PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
496:         x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5];
497:         i2    -= 6;
498:         idiag -= 36;
499:         for (i=m-2; i>=0; i--) {
500:           v  = aa + 36*(diag[i]+1);
501:           vi = aj + diag[i] + 1;
502:           nz = ai[i+1] - diag[i] - 1;
503:           s[0] = xb[i2]; s[1] = xb[i2+1]; s[2] = xb[i2+2]; s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5];
504:           while (nz--) {
505:             idx = 6*(*vi++);
506:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
507:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
508:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
509:             v  += 36;
510:           }
511:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
512:           x[i2] = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2]; x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5];
513:           idiag  -= 36;
514:           i2     -= 6;
515:         }
516:         break;
517:       case 7:
518:         s[0] = xb[i2];   s[1] = xb[i2+1]; s[2] = xb[i2+2];
519:         s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
520:         PetscKernel_v_gets_A_times_w_7(x,idiag,b);
521:         x[i2]   = xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
522:         x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
523:         i2    -= 7;
524:         idiag -= 49;
525:         for (i=m-2; i>=0; i--) {
526:           v  = aa + 49*(diag[i]+1);
527:           vi = aj + diag[i] + 1;
528:           nz = ai[i+1] - diag[i] - 1;
529:           s[0] = xb[i2];   s[1] = xb[i2+1]; s[2] = xb[i2+2];
530:           s[3] = xb[i2+3]; s[4] = xb[i2+4]; s[5] = xb[i2+5]; s[6] = xb[i2+6];
531:           while (nz--) {
532:             idx = 7*(*vi++);
533:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
534:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
535:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
536:             v  += 49;
537:           }
538:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
539:           x[i2] =   xw[0]; x[i2+1] = xw[1]; x[i2+2] = xw[2];
540:           x[i2+3] = xw[3]; x[i2+4] = xw[4]; x[i2+5] = xw[5]; x[i2+6] = xw[6];
541:           idiag  -= 49;
542:           i2     -= 7;
543:         }
544:         break;
545:       default:
546:         PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
547:         PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);
548:         i2    -= bs;
549:         idiag -= bs2;
550:         for (i=m-2; i>=0; i--) {
551:           v  = aa + bs2*(diag[i]+1);
552:           vi = aj + diag[i] + 1;
553:           nz = ai[i+1] - diag[i] - 1;

555:           PetscMemcpy(w,xb+i2,bs*sizeof(PetscScalar));
556:           /* copy all rows of x that are needed into contiguous space */
557:           workt = work;
558:           for (j=0; j<nz; j++) {
559:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
560:             workt += bs;
561:           }
562:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
563:           PetscKernel_w_gets_Ar_times_v(bs,bs,w,idiag,x+i2);

565:           idiag -= bs2;
566:           i2    -= bs;
567:         }
568:         break;
569:       }
570:       PetscLogFlops(1.0*bs2*(a->nz));
571:     }
572:     its--;
573:   }
574:   while (its--) {
575:     if (flag & SOR_FORWARD_SWEEP || flag & SOR_LOCAL_FORWARD_SWEEP) {
576:       idiag = a->idiag;
577:       i2 = 0;
578:       switch (bs) {
579:       case 1:
580:         for (i=0; i<m; i++) {
581:           v  = aa + ai[i];
582:           vi = aj + ai[i];
583:           nz = ai[i+1] - ai[i];
584:           s[0] = b[i2];
585:           for (j=0; j<nz; j++) {
586:             xw[0] = x[vi[j]];
587:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
588:           }
589:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
590:           x[i2] += xw[0];
591:           idiag += 1;
592:           i2    += 1;
593:         }
594:         break;
595:       case 2:
596:         for (i=0; i<m; i++) {
597:           v  = aa + 4*ai[i];
598:           vi = aj + ai[i];
599:           nz = ai[i+1] - ai[i];
600:           s[0] = b[i2]; s[1] = b[i2+1];
601:           for (j=0; j<nz; j++) {
602:             idx = 2*vi[j];
603:             it  = 4*j;
604:             xw[0] = x[idx]; xw[1] = x[1+idx];
605:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
606:           }
607:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
608:           x[i2]  += xw[0]; x[i2+1] += xw[1];
609:           idiag  += 4;
610:           i2     += 2;
611:         }
612:         break;
613:       case 3:
614:         for (i=0; i<m; i++) {
615:           v  = aa + 9*ai[i];
616:           vi = aj + ai[i];
617:           nz = ai[i+1] - ai[i];
618:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
619:           while (nz--) {
620:             idx = 3*(*vi++);
621:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
622:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
623:             v  += 9;
624:           }
625:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
626:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
627:           idiag  += 9;
628:           i2     += 3;
629:         }
630:         break;
631:       case 4:
632:         for (i=0; i<m; i++) {
633:           v  = aa + 16*ai[i];
634:           vi = aj + ai[i];
635:           nz = ai[i+1] - ai[i];
636:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
637:           while (nz--) {
638:             idx = 4*(*vi++);
639:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
640:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
641:             v  += 16;
642:           }
643:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
644:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
645:           idiag  += 16;
646:           i2     += 4;
647:         }
648:         break;
649:       case 5:
650:         for (i=0; i<m; i++) {
651:           v  = aa + 25*ai[i];
652:           vi = aj + ai[i];
653:           nz = ai[i+1] - ai[i];
654:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
655:           while (nz--) {
656:             idx = 5*(*vi++);
657:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
658:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
659:             v  += 25;
660:           }
661:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
662:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
663:           idiag  += 25;
664:           i2     += 5;
665:         }
666:         break;
667:       case 6:
668:         for (i=0; i<m; i++) {
669:           v  = aa + 36*ai[i];
670:           vi = aj + ai[i];
671:           nz = ai[i+1] - ai[i];
672:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5];
673:           while (nz--) {
674:             idx = 6*(*vi++);
675:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
676:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
677:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
678:             v  += 36;
679:           }
680:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
681:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
682:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
683:           idiag  += 36;
684:           i2     += 6;
685:         }
686:         break;
687:       case 7:
688:         for (i=0; i<m; i++) {
689:           v  = aa + 49*ai[i];
690:           vi = aj + ai[i];
691:           nz = ai[i+1] - ai[i];
692:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
693:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
694:           while (nz--) {
695:             idx = 7*(*vi++);
696:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
697:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
698:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
699:             v  += 49;
700:           }
701:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
702:           x[i2]   += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
703:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
704:           idiag  += 49;
705:           i2     += 7;
706:         }
707:         break;
708:       default:
709:         for (i=0; i<m; i++) {
710:           v  = aa + bs2*ai[i];
711:           vi = aj + ai[i];
712:           nz = ai[i+1] - ai[i];

714:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
715:           /* copy all rows of x that are needed into contiguous space */
716:           workt = work;
717:           for (j=0; j<nz; j++) {
718:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
719:             workt += bs;
720:           }
721:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
722:           PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);

724:           idiag += bs2;
725:           i2    += bs;
726:         }
727:         break;
728:       }
729:       PetscLogFlops(2.0*bs2*a->nz);
730:     }
731:     if (flag & SOR_BACKWARD_SWEEP || flag & SOR_LOCAL_BACKWARD_SWEEP) {
732:       idiag = a->idiag+bs2*(a->mbs-1);
733:       i2 = bs * (m-1);
734:       switch (bs) {
735:       case 1:
736:         for (i=m-1; i>=0; i--) {
737:           v  = aa + ai[i];
738:           vi = aj + ai[i];
739:           nz = ai[i+1] - ai[i];
740:           s[0] = b[i2];
741:           for (j=0; j<nz; j++) {
742:             xw[0] = x[vi[j]];
743:             PetscKernel_v_gets_v_minus_A_times_w_1(s,(v+j),xw);
744:           }
745:           PetscKernel_v_gets_A_times_w_1(xw,idiag,s);
746:           x[i2] += xw[0];
747:           idiag -= 1;
748:           i2    -= 1;
749:         }
750:         break;
751:       case 2:
752:         for (i=m-1; i>=0; i--) {
753:           v  = aa + 4*ai[i];
754:           vi = aj + ai[i];
755:           nz = ai[i+1] - ai[i];
756:           s[0] = b[i2]; s[1] = b[i2+1];
757:           for (j=0; j<nz; j++) {
758:             idx = 2*vi[j];
759:             it  = 4*j;
760:             xw[0] = x[idx]; xw[1] = x[1+idx];
761:             PetscKernel_v_gets_v_minus_A_times_w_2(s,(v+it),xw);
762:           }
763:           PetscKernel_v_gets_A_times_w_2(xw,idiag,s);
764:           x[i2]  += xw[0]; x[i2+1] += xw[1];
765:           idiag  -= 4;
766:           i2     -= 2;
767:         }
768:         break;
769:       case 3:
770:         for (i=m-1; i>=0; i--) {
771:           v  = aa + 9*ai[i];
772:           vi = aj + ai[i];
773:           nz = ai[i+1] - ai[i];
774:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2];
775:           while (nz--) {
776:             idx = 3*(*vi++);
777:             xw[0] = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx];
778:             PetscKernel_v_gets_v_minus_A_times_w_3(s,v,xw);
779:             v  += 9;
780:           }
781:           PetscKernel_v_gets_A_times_w_3(xw,idiag,s);
782:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
783:           idiag  -= 9;
784:           i2     -= 3;
785:         }
786:         break;
787:       case 4:
788:         for (i=m-1; i>=0; i--) {
789:           v  = aa + 16*ai[i];
790:           vi = aj + ai[i];
791:           nz = ai[i+1] - ai[i];
792:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3];
793:           while (nz--) {
794:             idx = 4*(*vi++);
795:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx];
796:             PetscKernel_v_gets_v_minus_A_times_w_4(s,v,xw);
797:             v  += 16;
798:           }
799:           PetscKernel_v_gets_A_times_w_4(xw,idiag,s);
800:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3];
801:           idiag  -= 16;
802:           i2     -= 4;
803:         }
804:         break;
805:       case 5:
806:         for (i=m-1; i>=0; i--) {
807:           v  = aa + 25*ai[i];
808:           vi = aj + ai[i];
809:           nz = ai[i+1] - ai[i];
810:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4];
811:           while (nz--) {
812:             idx = 5*(*vi++);
813:             xw[0]  = x[idx]; xw[1] = x[1+idx]; xw[2] = x[2+idx]; xw[3] = x[3+idx]; xw[4] = x[4+idx];
814:             PetscKernel_v_gets_v_minus_A_times_w_5(s,v,xw);
815:             v  += 25;
816:           }
817:           PetscKernel_v_gets_A_times_w_5(xw,idiag,s);
818:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2]; x[i2+3] += xw[3]; x[i2+4] += xw[4];
819:           idiag  -= 25;
820:           i2     -= 5;
821:         }
822:         break;
823:       case 6:
824:         for (i=m-1; i>=0; i--) {
825:           v  = aa + 36*ai[i];
826:           vi = aj + ai[i];
827:           nz = ai[i+1] - ai[i];
828:           s[0] = b[i2]; s[1] = b[i2+1]; s[2] = b[i2+2]; s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5];
829:           while (nz--) {
830:             idx = 6*(*vi++);
831:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
832:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx];
833:             PetscKernel_v_gets_v_minus_A_times_w_6(s,v,xw);
834:             v  += 36;
835:           }
836:           PetscKernel_v_gets_A_times_w_6(xw,idiag,s);
837:           x[i2] += xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
838:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5];
839:           idiag  -= 36;
840:           i2     -= 6;
841:         }
842:         break;
843:       case 7:
844:         for (i=m-1; i>=0; i--) {
845:           v  = aa + 49*ai[i];
846:           vi = aj + ai[i];
847:           nz = ai[i+1] - ai[i];
848:           s[0] = b[i2];   s[1] = b[i2+1]; s[2] = b[i2+2];
849:           s[3] = b[i2+3]; s[4] = b[i2+4]; s[5] = b[i2+5]; s[6] = b[i2+6];
850:           while (nz--) {
851:             idx = 7*(*vi++);
852:             xw[0] = x[idx];   xw[1] = x[1+idx]; xw[2] = x[2+idx];
853:             xw[3] = x[3+idx]; xw[4] = x[4+idx]; xw[5] = x[5+idx]; xw[6] = x[6+idx];
854:             PetscKernel_v_gets_v_minus_A_times_w_7(s,v,xw);
855:             v  += 49;
856:           }
857:           PetscKernel_v_gets_A_times_w_7(xw,idiag,s);
858:           x[i2] +=   xw[0]; x[i2+1] += xw[1]; x[i2+2] += xw[2];
859:           x[i2+3] += xw[3]; x[i2+4] += xw[4]; x[i2+5] += xw[5]; x[i2+6] += xw[6];
860:           idiag  -= 49;
861:           i2     -= 7;
862:         }
863:         break;
864:       default:
865:         for (i=m-1; i>=0; i--) {
866:           v  = aa + bs2*ai[i];
867:           vi = aj + ai[i];
868:           nz = ai[i+1] - ai[i];

870:           PetscMemcpy(w,b+i2,bs*sizeof(PetscScalar));
871:           /* copy all rows of x that are needed into contiguous space */
872:           workt = work;
873:           for (j=0; j<nz; j++) {
874:             PetscMemcpy(workt,x + bs*(*vi++),bs*sizeof(PetscScalar));
875:             workt += bs;
876:           }
877:           PetscKernel_w_gets_w_minus_Ar_times_v(bs,bs*nz,w,v,work);
878:           PetscKernel_w_gets_w_plus_Ar_times_v(bs,bs,w,idiag,x+i2);

880:           idiag -= bs2;
881:           i2    -= bs;
882:         }
883:         break;
884:       }
885:       PetscLogFlops(2.0*bs2*(a->nz));
886:     }
887:   }
888:   VecRestoreArray(xx,&x);
889:   VecRestoreArrayRead(bb,&b);
890:   return(0);
891: }


894: /*
895:     Special version for direct calls from Fortran (Used in PETSc-fun3d)
896: */
897: #if defined(PETSC_HAVE_FORTRAN_CAPS)
898: #define matsetvaluesblocked4_ MATSETVALUESBLOCKED4
899: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
900: #define matsetvaluesblocked4_ matsetvaluesblocked4
901: #endif

903: PETSC_EXTERN void matsetvaluesblocked4_(Mat *AA,PetscInt *mm,const PetscInt im[],PetscInt *nn,const PetscInt in[],const PetscScalar v[])
904: {
905:   Mat               A  = *AA;
906:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
907:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,N,m = *mm,n = *nn;
908:   PetscInt          *ai    =a->i,*ailen=a->ilen;
909:   PetscInt          *aj    =a->j,stepval,lastcol = -1;
910:   const PetscScalar *value = v;
911:   MatScalar         *ap,*aa = a->a,*bap;

914:   if (A->rmap->bs != 4) SETERRABORT(PetscObjectComm((PetscObject)A),PETSC_ERR_ARG_WRONG,"Can only be called with a block size of 4");
915:   stepval = (n-1)*4;
916:   for (k=0; k<m; k++) { /* loop over added rows */
917:     row  = im[k];
918:     rp   = aj + ai[row];
919:     ap   = aa + 16*ai[row];
920:     nrow = ailen[row];
921:     low  = 0;
922:     high = nrow;
923:     for (l=0; l<n; l++) { /* loop over added columns */
924:       col = in[l];
925:       if (col <= lastcol)  low = 0;
926:       else                high = nrow;
927:       lastcol = col;
928:       value   = v + k*(stepval+4 + l)*4;
929:       while (high-low > 7) {
930:         t = (low+high)/2;
931:         if (rp[t] > col) high = t;
932:         else             low  = t;
933:       }
934:       for (i=low; i<high; i++) {
935:         if (rp[i] > col) break;
936:         if (rp[i] == col) {
937:           bap = ap +  16*i;
938:           for (ii=0; ii<4; ii++,value+=stepval) {
939:             for (jj=ii; jj<16; jj+=4) {
940:               bap[jj] += *value++;
941:             }
942:           }
943:           goto noinsert2;
944:         }
945:       }
946:       N = nrow++ - 1;
947:       high++; /* added new column index thus must search to one higher than before */
948:       /* shift up all the later entries in this row */
949:       for (ii=N; ii>=i; ii--) {
950:         rp[ii+1] = rp[ii];
951:         PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
952:       }
953:       if (N >= i) {
954:         PetscMemzero(ap+16*i,16*sizeof(MatScalar));
955:       }
956:       rp[i] = col;
957:       bap   = ap +  16*i;
958:       for (ii=0; ii<4; ii++,value+=stepval) {
959:         for (jj=ii; jj<16; jj+=4) {
960:           bap[jj] = *value++;
961:         }
962:       }
963:       noinsert2:;
964:       low = i;
965:     }
966:     ailen[row] = nrow;
967:   }
968:   PetscFunctionReturnVoid();
969: }

971: #if defined(PETSC_HAVE_FORTRAN_CAPS)
972: #define matsetvalues4_ MATSETVALUES4
973: #elif !defined(PETSC_HAVE_FORTRAN_UNDERSCORE)
974: #define matsetvalues4_ matsetvalues4
975: #endif

977: PETSC_EXTERN void matsetvalues4_(Mat *AA,PetscInt *mm,PetscInt *im,PetscInt *nn,PetscInt *in,PetscScalar *v)
978: {
979:   Mat         A  = *AA;
980:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
981:   PetscInt    *rp,k,low,high,t,ii,row,nrow,i,col,l,N,n = *nn,m = *mm;
982:   PetscInt    *ai=a->i,*ailen=a->ilen;
983:   PetscInt    *aj=a->j,brow,bcol;
984:   PetscInt    ridx,cidx,lastcol = -1;
985:   MatScalar   *ap,value,*aa=a->a,*bap;

988:   for (k=0; k<m; k++) { /* loop over added rows */
989:     row  = im[k]; brow = row/4;
990:     rp   = aj + ai[brow];
991:     ap   = aa + 16*ai[brow];
992:     nrow = ailen[brow];
993:     low  = 0;
994:     high = nrow;
995:     for (l=0; l<n; l++) { /* loop over added columns */
996:       col   = in[l]; bcol = col/4;
997:       ridx  = row % 4; cidx = col % 4;
998:       value = v[l + k*n];
999:       if (col <= lastcol)  low = 0;
1000:       else                high = nrow;
1001:       lastcol = col;
1002:       while (high-low > 7) {
1003:         t = (low+high)/2;
1004:         if (rp[t] > bcol) high = t;
1005:         else              low  = t;
1006:       }
1007:       for (i=low; i<high; i++) {
1008:         if (rp[i] > bcol) break;
1009:         if (rp[i] == bcol) {
1010:           bap   = ap +  16*i + 4*cidx + ridx;
1011:           *bap += value;
1012:           goto noinsert1;
1013:         }
1014:       }
1015:       N = nrow++ - 1;
1016:       high++; /* added new column thus must search to one higher than before */
1017:       /* shift up all the later entries in this row */
1018:       for (ii=N; ii>=i; ii--) {
1019:         rp[ii+1] = rp[ii];
1020:         PetscMemcpy(ap+16*(ii+1),ap+16*(ii),16*sizeof(MatScalar));
1021:       }
1022:       if (N>=i) {
1023:         PetscMemzero(ap+16*i,16*sizeof(MatScalar));
1024:       }
1025:       rp[i]                    = bcol;
1026:       ap[16*i + 4*cidx + ridx] = value;
1027: noinsert1:;
1028:       low = i;
1029:     }
1030:     ailen[brow] = nrow;
1031:   }
1032:   PetscFunctionReturnVoid();
1033: }

1035: /*
1036:      Checks for missing diagonals
1037: */
1038: PetscErrorCode MatMissingDiagonal_SeqBAIJ(Mat A,PetscBool  *missing,PetscInt *d)
1039: {
1040:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
1042:   PetscInt       *diag,*ii = a->i,i;

1045:   MatMarkDiagonal_SeqBAIJ(A);
1046:   *missing = PETSC_FALSE;
1047:   if (A->rmap->n > 0 && !ii) {
1048:     *missing = PETSC_TRUE;
1049:     if (d) *d = 0;
1050:     PetscInfo(A,"Matrix has no entries therefore is missing diagonal\n");
1051:   } else {
1052:     diag = a->diag;
1053:     for (i=0; i<a->mbs; i++) {
1054:       if (diag[i] >= ii[i+1]) {
1055:         *missing = PETSC_TRUE;
1056:         if (d) *d = i;
1057:         PetscInfo1(A,"Matrix is missing block diagonal number %D\n",i);
1058:         break;
1059:       }
1060:     }
1061:   }
1062:   return(0);
1063: }

1065: PetscErrorCode MatMarkDiagonal_SeqBAIJ(Mat A)
1066: {
1067:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
1069:   PetscInt       i,j,m = a->mbs;

1072:   if (!a->diag) {
1073:     PetscMalloc1(m,&a->diag);
1074:     PetscLogObjectMemory((PetscObject)A,m*sizeof(PetscInt));
1075:     a->free_diag = PETSC_TRUE;
1076:   }
1077:   for (i=0; i<m; i++) {
1078:     a->diag[i] = a->i[i+1];
1079:     for (j=a->i[i]; j<a->i[i+1]; j++) {
1080:       if (a->j[j] == i) {
1081:         a->diag[i] = j;
1082:         break;
1083:       }
1084:     }
1085:   }
1086:   return(0);
1087: }


1090: static PetscErrorCode MatGetRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *inia[],const PetscInt *inja[],PetscBool  *done)
1091: {
1092:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
1094:   PetscInt       i,j,n = a->mbs,nz = a->i[n],*tia,*tja,bs = A->rmap->bs,k,l,cnt;
1095:   PetscInt       **ia = (PetscInt**)inia,**ja = (PetscInt**)inja;

1098:   *nn = n;
1099:   if (!ia) return(0);
1100:   if (symmetric) {
1101:     MatToSymmetricIJ_SeqAIJ(n,a->i,a->j,PETSC_TRUE,0,0,&tia,&tja);
1102:     nz   = tia[n];
1103:   } else {
1104:     tia = a->i; tja = a->j;
1105:   }

1107:   if (!blockcompressed && bs > 1) {
1108:     (*nn) *= bs;
1109:     /* malloc & create the natural set of indices */
1110:     PetscMalloc1((n+1)*bs,ia);
1111:     if (n) {
1112:       (*ia)[0] = oshift;
1113:       for (j=1; j<bs; j++) {
1114:         (*ia)[j] = (tia[1]-tia[0])*bs+(*ia)[j-1];
1115:       }
1116:     }

1118:     for (i=1; i<n; i++) {
1119:       (*ia)[i*bs] = (tia[i]-tia[i-1])*bs + (*ia)[i*bs-1];
1120:       for (j=1; j<bs; j++) {
1121:         (*ia)[i*bs+j] = (tia[i+1]-tia[i])*bs + (*ia)[i*bs+j-1];
1122:       }
1123:     }
1124:     if (n) {
1125:       (*ia)[n*bs] = (tia[n]-tia[n-1])*bs + (*ia)[n*bs-1];
1126:     }

1128:     if (inja) {
1129:       PetscMalloc1(nz*bs*bs,ja);
1130:       cnt = 0;
1131:       for (i=0; i<n; i++) {
1132:         for (j=0; j<bs; j++) {
1133:           for (k=tia[i]; k<tia[i+1]; k++) {
1134:             for (l=0; l<bs; l++) {
1135:               (*ja)[cnt++] = bs*tja[k] + l;
1136:             }
1137:           }
1138:         }
1139:       }
1140:     }

1142:     if (symmetric) { /* deallocate memory allocated in MatToSymmetricIJ_SeqAIJ() */
1143:       PetscFree(tia);
1144:       PetscFree(tja);
1145:     }
1146:   } else if (oshift == 1) {
1147:     if (symmetric) {
1148:       nz = tia[A->rmap->n/bs];
1149:       /*  add 1 to i and j indices */
1150:       for (i=0; i<A->rmap->n/bs+1; i++) tia[i] = tia[i] + 1;
1151:       *ia = tia;
1152:       if (ja) {
1153:         for (i=0; i<nz; i++) tja[i] = tja[i] + 1;
1154:         *ja = tja;
1155:       }
1156:     } else {
1157:       nz = a->i[A->rmap->n/bs];
1158:       /* malloc space and  add 1 to i and j indices */
1159:       PetscMalloc1(A->rmap->n/bs+1,ia);
1160:       for (i=0; i<A->rmap->n/bs+1; i++) (*ia)[i] = a->i[i] + 1;
1161:       if (ja) {
1162:         PetscMalloc1(nz,ja);
1163:         for (i=0; i<nz; i++) (*ja)[i] = a->j[i] + 1;
1164:       }
1165:     }
1166:   } else {
1167:     *ia = tia;
1168:     if (ja) *ja = tja;
1169:   }
1170:   return(0);
1171: }

1173: static PetscErrorCode MatRestoreRowIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool blockcompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
1174: {

1178:   if (!ia) return(0);
1179:   if ((!blockcompressed && A->rmap->bs > 1) || (symmetric || oshift == 1)) {
1180:     PetscFree(*ia);
1181:     if (ja) {PetscFree(*ja);}
1182:   }
1183:   return(0);
1184: }

1186: PetscErrorCode MatDestroy_SeqBAIJ(Mat A)
1187: {
1188:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

1192: #if defined(PETSC_USE_LOG)
1193:   PetscLogObjectState((PetscObject)A,"Rows=%D, Cols=%D, NZ=%D",A->rmap->N,A->cmap->n,a->nz);
1194: #endif
1195:   MatSeqXAIJFreeAIJ(A,&a->a,&a->j,&a->i);
1196:   ISDestroy(&a->row);
1197:   ISDestroy(&a->col);
1198:   if (a->free_diag) {PetscFree(a->diag);}
1199:   PetscFree(a->idiag);
1200:   if (a->free_imax_ilen) {PetscFree2(a->imax,a->ilen);}
1201:   PetscFree(a->solve_work);
1202:   PetscFree(a->mult_work);
1203:   PetscFree(a->sor_workt);
1204:   PetscFree(a->sor_work);
1205:   ISDestroy(&a->icol);
1206:   PetscFree(a->saved_values);
1207:   PetscFree2(a->compressedrow.i,a->compressedrow.rindex);

1209:   MatDestroy(&a->sbaijMat);
1210:   MatDestroy(&a->parent);
1211:   PetscFree(A->data);

1213:   PetscObjectChangeTypeName((PetscObject)A,0);
1214:   PetscObjectComposeFunction((PetscObject)A,"MatInvertBlockDiagonal_C",NULL);
1215:   PetscObjectComposeFunction((PetscObject)A,"MatStoreValues_C",NULL);
1216:   PetscObjectComposeFunction((PetscObject)A,"MatRetrieveValues_C",NULL);
1217:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetColumnIndices_C",NULL);
1218:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqaij_C",NULL);
1219:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqsbaij_C",NULL);
1220:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocation_C",NULL);
1221:   PetscObjectComposeFunction((PetscObject)A,"MatSeqBAIJSetPreallocationCSR_C",NULL);
1222:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_seqbstrm_C",NULL);
1223:   PetscObjectComposeFunction((PetscObject)A,"MatIsTranspose_C",NULL);
1224: #if defined(PETSC_HAVE_HYPRE)
1225:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_hypre_C",NULL);
1226: #endif
1227:   PetscObjectComposeFunction((PetscObject)A,"MatConvert_seqbaij_is_C",NULL);
1228:   PetscObjectComposeFunction((PetscObject)A,"MatPtAP_is_seqaij_C",NULL);
1229:   return(0);
1230: }

1232: PetscErrorCode MatSetOption_SeqBAIJ(Mat A,MatOption op,PetscBool flg)
1233: {
1234:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

1238:   switch (op) {
1239:   case MAT_ROW_ORIENTED:
1240:     a->roworiented = flg;
1241:     break;
1242:   case MAT_KEEP_NONZERO_PATTERN:
1243:     a->keepnonzeropattern = flg;
1244:     break;
1245:   case MAT_NEW_NONZERO_LOCATIONS:
1246:     a->nonew = (flg ? 0 : 1);
1247:     break;
1248:   case MAT_NEW_NONZERO_LOCATION_ERR:
1249:     a->nonew = (flg ? -1 : 0);
1250:     break;
1251:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
1252:     a->nonew = (flg ? -2 : 0);
1253:     break;
1254:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
1255:     a->nounused = (flg ? -1 : 0);
1256:     break;
1257:   case MAT_NEW_DIAGONALS:
1258:   case MAT_IGNORE_OFF_PROC_ENTRIES:
1259:   case MAT_USE_HASH_TABLE:
1260:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
1261:     break;
1262:   case MAT_SPD:
1263:   case MAT_SYMMETRIC:
1264:   case MAT_STRUCTURALLY_SYMMETRIC:
1265:   case MAT_HERMITIAN:
1266:   case MAT_SYMMETRY_ETERNAL:
1267:   case MAT_SUBMAT_SINGLEIS:
1268:   case MAT_STRUCTURE_ONLY:
1269:     /* These options are handled directly by MatSetOption() */
1270:     break;
1271:   default:
1272:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
1273:   }
1274:   return(0);
1275: }

1277: /* used for both SeqBAIJ and SeqSBAIJ matrices */
1278: PetscErrorCode MatGetRow_SeqBAIJ_private(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v,PetscInt *ai,PetscInt *aj,PetscScalar *aa)
1279: {
1281:   PetscInt       itmp,i,j,k,M,bn,bp,*idx_i,bs,bs2;
1282:   MatScalar      *aa_i;
1283:   PetscScalar    *v_i;

1286:   bs  = A->rmap->bs;
1287:   bs2 = bs*bs;
1288:   if (row < 0 || row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D out of range", row);

1290:   bn  = row/bs;   /* Block number */
1291:   bp  = row % bs; /* Block Position */
1292:   M   = ai[bn+1] - ai[bn];
1293:   *nz = bs*M;

1295:   if (v) {
1296:     *v = 0;
1297:     if (*nz) {
1298:       PetscMalloc1(*nz,v);
1299:       for (i=0; i<M; i++) { /* for each block in the block row */
1300:         v_i  = *v + i*bs;
1301:         aa_i = aa + bs2*(ai[bn] + i);
1302:         for (j=bp,k=0; j<bs2; j+=bs,k++) v_i[k] = aa_i[j];
1303:       }
1304:     }
1305:   }

1307:   if (idx) {
1308:     *idx = 0;
1309:     if (*nz) {
1310:       PetscMalloc1(*nz,idx);
1311:       for (i=0; i<M; i++) { /* for each block in the block row */
1312:         idx_i = *idx + i*bs;
1313:         itmp  = bs*aj[ai[bn] + i];
1314:         for (j=0; j<bs; j++) idx_i[j] = itmp++;
1315:       }
1316:     }
1317:   }
1318:   return(0);
1319: }

1321: PetscErrorCode MatGetRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1322: {
1323:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;

1327:   MatGetRow_SeqBAIJ_private(A,row,nz,idx,v,a->i,a->j,a->a);
1328:   return(0);
1329: }

1331: PetscErrorCode MatRestoreRow_SeqBAIJ(Mat A,PetscInt row,PetscInt *nz,PetscInt **idx,PetscScalar **v)
1332: {

1336:   if (idx) {PetscFree(*idx);}
1337:   if (v)   {PetscFree(*v);}
1338:   return(0);
1339: }

1341: PetscErrorCode MatTranspose_SeqBAIJ(Mat A,MatReuse reuse,Mat *B)
1342: {
1343:   Mat_SeqBAIJ    *a=(Mat_SeqBAIJ*)A->data;
1344:   Mat            C;
1346:   PetscInt       i,j,k,*aj=a->j,*ai=a->i,bs=A->rmap->bs,mbs=a->mbs,nbs=a->nbs,len,*col;
1347:   PetscInt       *rows,*cols,bs2=a->bs2;
1348:   MatScalar      *array;

1351:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_INPLACE_MATRIX) {
1352:     PetscCalloc1(1+nbs,&col);

1354:     for (i=0; i<ai[mbs]; i++) col[aj[i]] += 1;
1355:     MatCreate(PetscObjectComm((PetscObject)A),&C);
1356:     MatSetSizes(C,A->cmap->n,A->rmap->N,A->cmap->n,A->rmap->N);
1357:     MatSetType(C,((PetscObject)A)->type_name);
1358:     MatSeqBAIJSetPreallocation(C,bs,0,col);
1359:     PetscFree(col);
1360:   } else {
1361:     C = *B;
1362:   }

1364:   array = a->a;
1365:   PetscMalloc2(bs,&rows,bs,&cols);
1366:   for (i=0; i<mbs; i++) {
1367:     cols[0] = i*bs;
1368:     for (k=1; k<bs; k++) cols[k] = cols[k-1] + 1;
1369:     len = ai[i+1] - ai[i];
1370:     for (j=0; j<len; j++) {
1371:       rows[0] = (*aj++)*bs;
1372:       for (k=1; k<bs; k++) rows[k] = rows[k-1] + 1;
1373:       MatSetValues_SeqBAIJ(C,bs,rows,bs,cols,array,INSERT_VALUES);
1374:       array += bs2;
1375:     }
1376:   }
1377:   PetscFree2(rows,cols);

1379:   MatAssemblyBegin(C,MAT_FINAL_ASSEMBLY);
1380:   MatAssemblyEnd(C,MAT_FINAL_ASSEMBLY);

1382:   if (reuse == MAT_INITIAL_MATRIX || reuse == MAT_REUSE_MATRIX) {
1383:     *B = C;
1384:   } else {
1385:     MatHeaderMerge(A,&C);
1386:   }
1387:   return(0);
1388: }

1390: PetscErrorCode MatIsTranspose_SeqBAIJ(Mat A,Mat B,PetscReal tol,PetscBool  *f)
1391: {
1393:   Mat            Btrans;

1396:   *f   = PETSC_FALSE;
1397:   MatTranspose_SeqBAIJ(A,MAT_INITIAL_MATRIX,&Btrans);
1398:   MatEqual_SeqBAIJ(B,Btrans,f);
1399:   MatDestroy(&Btrans);
1400:   return(0);
1401: }

1403: static PetscErrorCode MatView_SeqBAIJ_Binary(Mat A,PetscViewer viewer)
1404: {
1405:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
1407:   PetscInt       i,*col_lens,bs = A->rmap->bs,count,*jj,j,k,l,bs2=a->bs2;
1408:   int            fd;
1409:   PetscScalar    *aa;
1410:   FILE           *file;

1413:   PetscViewerBinaryGetDescriptor(viewer,&fd);
1414:   PetscMalloc1(4+A->rmap->N,&col_lens);
1415:   col_lens[0] = MAT_FILE_CLASSID;

1417:   col_lens[1] = A->rmap->N;
1418:   col_lens[2] = A->cmap->n;
1419:   col_lens[3] = a->nz*bs2;

1421:   /* store lengths of each row and write (including header) to file */
1422:   count = 0;
1423:   for (i=0; i<a->mbs; i++) {
1424:     for (j=0; j<bs; j++) {
1425:       col_lens[4+count++] = bs*(a->i[i+1] - a->i[i]);
1426:     }
1427:   }
1428:   PetscBinaryWrite(fd,col_lens,4+A->rmap->N,PETSC_INT,PETSC_TRUE);
1429:   PetscFree(col_lens);

1431:   /* store column indices (zero start index) */
1432:   PetscMalloc1((a->nz+1)*bs2,&jj);
1433:   count = 0;
1434:   for (i=0; i<a->mbs; i++) {
1435:     for (j=0; j<bs; j++) {
1436:       for (k=a->i[i]; k<a->i[i+1]; k++) {
1437:         for (l=0; l<bs; l++) {
1438:           jj[count++] = bs*a->j[k] + l;
1439:         }
1440:       }
1441:     }
1442:   }
1443:   PetscBinaryWrite(fd,jj,bs2*a->nz,PETSC_INT,PETSC_FALSE);
1444:   PetscFree(jj);

1446:   /* store nonzero values */
1447:   PetscMalloc1((a->nz+1)*bs2,&aa);
1448:   count = 0;
1449:   for (i=0; i<a->mbs; i++) {
1450:     for (j=0; j<bs; j++) {
1451:       for (k=a->i[i]; k<a->i[i+1]; k++) {
1452:         for (l=0; l<bs; l++) {
1453:           aa[count++] = a->a[bs2*k + l*bs + j];
1454:         }
1455:       }
1456:     }
1457:   }
1458:   PetscBinaryWrite(fd,aa,bs2*a->nz,PETSC_SCALAR,PETSC_FALSE);
1459:   PetscFree(aa);

1461:   PetscViewerBinaryGetInfoPointer(viewer,&file);
1462:   if (file) {
1463:     fprintf(file,"-matload_block_size %d\n",(int)A->rmap->bs);
1464:   }
1465:   return(0);
1466: }

1468: static PetscErrorCode MatView_SeqBAIJ_ASCII_structonly(Mat A,PetscViewer viewer)
1469: {
1471:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
1472:   PetscInt       i,bs = A->rmap->bs,k;

1475:   PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1476:   for (i=0; i<a->mbs; i++) {
1477:     PetscViewerASCIIPrintf(viewer,"row %D-%D:",i*bs,i*bs+bs-1);
1478:     for (k=a->i[i]; k<a->i[i+1]; k++) {
1479:       PetscViewerASCIIPrintf(viewer," (%D-%D) ",bs*a->j[k],bs*a->j[k]+bs-1);
1480:     }
1481:     PetscViewerASCIIPrintf(viewer,"\n");
1482:   }
1483:   PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1484:   return(0);
1485: }

1487: static PetscErrorCode MatView_SeqBAIJ_ASCII(Mat A,PetscViewer viewer)
1488: {
1489:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
1490:   PetscErrorCode    ierr;
1491:   PetscInt          i,j,bs = A->rmap->bs,k,l,bs2=a->bs2;
1492:   PetscViewerFormat format;

1495:   if (A->structure_only) {
1496:     MatView_SeqBAIJ_ASCII_structonly(A,viewer);
1497:     return(0);
1498:   }

1500:   PetscViewerGetFormat(viewer,&format);
1501:   if (format == PETSC_VIEWER_ASCII_INFO || format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
1502:     PetscViewerASCIIPrintf(viewer,"  block size is %D\n",bs);
1503:   } else if (format == PETSC_VIEWER_ASCII_MATLAB) {
1504:     const char *matname;
1505:     Mat        aij;
1506:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&aij);
1507:     PetscObjectGetName((PetscObject)A,&matname);
1508:     PetscObjectSetName((PetscObject)aij,matname);
1509:     MatView(aij,viewer);
1510:     MatDestroy(&aij);
1511:   } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
1512:       return(0);
1513:   } else if (format == PETSC_VIEWER_ASCII_COMMON) {
1514:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1515:     for (i=0; i<a->mbs; i++) {
1516:       for (j=0; j<bs; j++) {
1517:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
1518:         for (k=a->i[i]; k<a->i[i+1]; k++) {
1519:           for (l=0; l<bs; l++) {
1520: #if defined(PETSC_USE_COMPLEX)
1521:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1522:               PetscViewerASCIIPrintf(viewer," (%D, %g + %gi) ",bs*a->j[k]+l,
1523:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1524:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0 && PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1525:               PetscViewerASCIIPrintf(viewer," (%D, %g - %gi) ",bs*a->j[k]+l,
1526:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1527:             } else if (PetscRealPart(a->a[bs2*k + l*bs + j]) != 0.0) {
1528:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
1529:             }
1530: #else
1531:             if (a->a[bs2*k + l*bs + j] != 0.0) {
1532:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
1533:             }
1534: #endif
1535:           }
1536:         }
1537:         PetscViewerASCIIPrintf(viewer,"\n");
1538:       }
1539:     }
1540:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1541:   } else {
1542:     PetscViewerASCIIUseTabs(viewer,PETSC_FALSE);
1543:     for (i=0; i<a->mbs; i++) {
1544:       for (j=0; j<bs; j++) {
1545:         PetscViewerASCIIPrintf(viewer,"row %D:",i*bs+j);
1546:         for (k=a->i[i]; k<a->i[i+1]; k++) {
1547:           for (l=0; l<bs; l++) {
1548: #if defined(PETSC_USE_COMPLEX)
1549:             if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) > 0.0) {
1550:               PetscViewerASCIIPrintf(viewer," (%D, %g + %g i) ",bs*a->j[k]+l,
1551:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1552:             } else if (PetscImaginaryPart(a->a[bs2*k + l*bs + j]) < 0.0) {
1553:               PetscViewerASCIIPrintf(viewer," (%D, %g - %g i) ",bs*a->j[k]+l,
1554:                                             (double)PetscRealPart(a->a[bs2*k + l*bs + j]),-(double)PetscImaginaryPart(a->a[bs2*k + l*bs + j]));
1555:             } else {
1556:               PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)PetscRealPart(a->a[bs2*k + l*bs + j]));
1557:             }
1558: #else
1559:             PetscViewerASCIIPrintf(viewer," (%D, %g) ",bs*a->j[k]+l,(double)a->a[bs2*k + l*bs + j]);
1560: #endif
1561:           }
1562:         }
1563:         PetscViewerASCIIPrintf(viewer,"\n");
1564:       }
1565:     }
1566:     PetscViewerASCIIUseTabs(viewer,PETSC_TRUE);
1567:   }
1568:   PetscViewerFlush(viewer);
1569:   return(0);
1570: }

1572:  #include <petscdraw.h>
1573: static PetscErrorCode MatView_SeqBAIJ_Draw_Zoom(PetscDraw draw,void *Aa)
1574: {
1575:   Mat               A = (Mat) Aa;
1576:   Mat_SeqBAIJ       *a=(Mat_SeqBAIJ*)A->data;
1577:   PetscErrorCode    ierr;
1578:   PetscInt          row,i,j,k,l,mbs=a->mbs,color,bs=A->rmap->bs,bs2=a->bs2;
1579:   PetscReal         xl,yl,xr,yr,x_l,x_r,y_l,y_r;
1580:   MatScalar         *aa;
1581:   PetscViewer       viewer;
1582:   PetscViewerFormat format;

1585:   PetscObjectQuery((PetscObject)A,"Zoomviewer",(PetscObject*)&viewer);
1586:   PetscViewerGetFormat(viewer,&format);
1587:   PetscDrawGetCoordinates(draw,&xl,&yl,&xr,&yr);

1589:   /* loop over matrix elements drawing boxes */

1591:   if (format != PETSC_VIEWER_DRAW_CONTOUR) {
1592:     PetscDrawCollectiveBegin(draw);
1593:     /* Blue for negative, Cyan for zero and  Red for positive */
1594:     color = PETSC_DRAW_BLUE;
1595:     for (i=0,row=0; i<mbs; i++,row+=bs) {
1596:       for (j=a->i[i]; j<a->i[i+1]; j++) {
1597:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1598:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
1599:         aa  = a->a + j*bs2;
1600:         for (k=0; k<bs; k++) {
1601:           for (l=0; l<bs; l++) {
1602:             if (PetscRealPart(*aa++) >=  0.) continue;
1603:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1604:           }
1605:         }
1606:       }
1607:     }
1608:     color = PETSC_DRAW_CYAN;
1609:     for (i=0,row=0; i<mbs; i++,row+=bs) {
1610:       for (j=a->i[i]; j<a->i[i+1]; j++) {
1611:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1612:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
1613:         aa  = a->a + j*bs2;
1614:         for (k=0; k<bs; k++) {
1615:           for (l=0; l<bs; l++) {
1616:             if (PetscRealPart(*aa++) != 0.) continue;
1617:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1618:           }
1619:         }
1620:       }
1621:     }
1622:     color = PETSC_DRAW_RED;
1623:     for (i=0,row=0; i<mbs; i++,row+=bs) {
1624:       for (j=a->i[i]; j<a->i[i+1]; j++) {
1625:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1626:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
1627:         aa  = a->a + j*bs2;
1628:         for (k=0; k<bs; k++) {
1629:           for (l=0; l<bs; l++) {
1630:             if (PetscRealPart(*aa++) <= 0.) continue;
1631:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1632:           }
1633:         }
1634:       }
1635:     }
1636:     PetscDrawCollectiveEnd(draw);
1637:   } else {
1638:     /* use contour shading to indicate magnitude of values */
1639:     /* first determine max of all nonzero values */
1640:     PetscReal minv = 0.0, maxv = 0.0;
1641:     PetscDraw popup;

1643:     for (i=0; i<a->nz*a->bs2; i++) {
1644:       if (PetscAbsScalar(a->a[i]) > maxv) maxv = PetscAbsScalar(a->a[i]);
1645:     }
1646:     if (minv >= maxv) maxv = minv + PETSC_SMALL;
1647:     PetscDrawGetPopup(draw,&popup);
1648:     PetscDrawScalePopup(popup,0.0,maxv);

1650:     PetscDrawCollectiveBegin(draw);
1651:     for (i=0,row=0; i<mbs; i++,row+=bs) {
1652:       for (j=a->i[i]; j<a->i[i+1]; j++) {
1653:         y_l = A->rmap->N - row - 1.0; y_r = y_l + 1.0;
1654:         x_l = a->j[j]*bs; x_r = x_l + 1.0;
1655:         aa  = a->a + j*bs2;
1656:         for (k=0; k<bs; k++) {
1657:           for (l=0; l<bs; l++) {
1658:             MatScalar v = *aa++;
1659:             color = PetscDrawRealToColor(PetscAbsScalar(v),minv,maxv);
1660:             PetscDrawRectangle(draw,x_l+k,y_l-l,x_r+k,y_r-l,color,color,color,color);
1661:           }
1662:         }
1663:       }
1664:     }
1665:     PetscDrawCollectiveEnd(draw);
1666:   }
1667:   return(0);
1668: }

1670: static PetscErrorCode MatView_SeqBAIJ_Draw(Mat A,PetscViewer viewer)
1671: {
1673:   PetscReal      xl,yl,xr,yr,w,h;
1674:   PetscDraw      draw;
1675:   PetscBool      isnull;

1678:   PetscViewerDrawGetDraw(viewer,0,&draw);
1679:   PetscDrawIsNull(draw,&isnull);
1680:   if (isnull) return(0);

1682:   xr   = A->cmap->n; yr = A->rmap->N; h = yr/10.0; w = xr/10.0;
1683:   xr  += w;          yr += h;        xl = -w;     yl = -h;
1684:   PetscDrawSetCoordinates(draw,xl,yl,xr,yr);
1685:   PetscObjectCompose((PetscObject)A,"Zoomviewer",(PetscObject)viewer);
1686:   PetscDrawZoom(draw,MatView_SeqBAIJ_Draw_Zoom,A);
1687:   PetscObjectCompose((PetscObject)A,"Zoomviewer",NULL);
1688:   PetscDrawSave(draw);
1689:   return(0);
1690: }

1692: PetscErrorCode MatView_SeqBAIJ(Mat A,PetscViewer viewer)
1693: {
1695:   PetscBool      iascii,isbinary,isdraw;

1698:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
1699:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
1700:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
1701:   if (iascii) {
1702:     MatView_SeqBAIJ_ASCII(A,viewer);
1703:   } else if (isbinary) {
1704:     MatView_SeqBAIJ_Binary(A,viewer);
1705:   } else if (isdraw) {
1706:     MatView_SeqBAIJ_Draw(A,viewer);
1707:   } else {
1708:     Mat B;
1709:     MatConvert(A,MATSEQAIJ,MAT_INITIAL_MATRIX,&B);
1710:     MatView(B,viewer);
1711:     MatDestroy(&B);
1712:   }
1713:   return(0);
1714: }


1717: PetscErrorCode MatGetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],PetscScalar v[])
1718: {
1719:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
1720:   PetscInt    *rp,k,low,high,t,row,nrow,i,col,l,*aj = a->j;
1721:   PetscInt    *ai = a->i,*ailen = a->ilen;
1722:   PetscInt    brow,bcol,ridx,cidx,bs=A->rmap->bs,bs2=a->bs2;
1723:   MatScalar   *ap,*aa = a->a;

1726:   for (k=0; k<m; k++) { /* loop over rows */
1727:     row = im[k]; brow = row/bs;
1728:     if (row < 0) {v += n; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row"); */
1729:     if (row >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row %D too large", row);
1730:     rp   = aj + ai[brow]; ap = aa + bs2*ai[brow];
1731:     nrow = ailen[brow];
1732:     for (l=0; l<n; l++) { /* loop over columns */
1733:       if (in[l] < 0) {v++; continue;} /* SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column"); */
1734:       if (in[l] >= A->cmap->n) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column %D too large", in[l]);
1735:       col  = in[l];
1736:       bcol = col/bs;
1737:       cidx = col%bs;
1738:       ridx = row%bs;
1739:       high = nrow;
1740:       low  = 0; /* assume unsorted */
1741:       while (high-low > 5) {
1742:         t = (low+high)/2;
1743:         if (rp[t] > bcol) high = t;
1744:         else             low  = t;
1745:       }
1746:       for (i=low; i<high; i++) {
1747:         if (rp[i] > bcol) break;
1748:         if (rp[i] == bcol) {
1749:           *v++ = ap[bs2*i+bs*cidx+ridx];
1750:           goto finished;
1751:         }
1752:       }
1753:       *v++ = 0.0;
1754: finished:;
1755:     }
1756:   }
1757:   return(0);
1758: }

1760: PetscErrorCode MatSetValuesBlocked_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
1761: {
1762:   Mat_SeqBAIJ       *a = (Mat_SeqBAIJ*)A->data;
1763:   PetscInt          *rp,k,low,high,t,ii,jj,row,nrow,i,col,l,rmax,N,lastcol = -1;
1764:   PetscInt          *imax=a->imax,*ai=a->i,*ailen=a->ilen;
1765:   PetscErrorCode    ierr;
1766:   PetscInt          *aj        =a->j,nonew=a->nonew,bs2=a->bs2,bs=A->rmap->bs,stepval;
1767:   PetscBool         roworiented=a->roworiented;
1768:   const PetscScalar *value     = v;
1769:   MatScalar         *ap=NULL,*aa = a->a,*bap;

1772:   if (roworiented) {
1773:     stepval = (n-1)*bs;
1774:   } else {
1775:     stepval = (m-1)*bs;
1776:   }
1777:   for (k=0; k<m; k++) { /* loop over added rows */
1778:     row = im[k];
1779:     if (row < 0) continue;
1780: #if defined(PETSC_USE_DEBUG)
1781:     if (row >= a->mbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block row index too large %D max %D",row,a->mbs-1);
1782: #endif
1783:     rp   = aj + ai[row];
1784:     if (!A->structure_only) ap = aa + bs2*ai[row];
1785:     rmax = imax[row];
1786:     nrow = ailen[row];
1787:     low  = 0;
1788:     high = nrow;
1789:     for (l=0; l<n; l++) { /* loop over added columns */
1790:       if (in[l] < 0) continue;
1791: #if defined(PETSC_USE_DEBUG)
1792:       if (in[l] >= a->nbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Block column index too large %D max %D",in[l],a->nbs-1);
1793: #endif
1794:       col = in[l];
1795:       if (!A->structure_only) {
1796:         if (roworiented) {
1797:           value = v + (k*(stepval+bs) + l)*bs;
1798:         } else {
1799:           value = v + (l*(stepval+bs) + k)*bs;
1800:         }
1801:       }
1802:       if (col <= lastcol) low = 0;
1803:       else high = nrow;
1804:       lastcol = col;
1805:       while (high-low > 7) {
1806:         t = (low+high)/2;
1807:         if (rp[t] > col) high = t;
1808:         else             low  = t;
1809:       }
1810:       for (i=low; i<high; i++) {
1811:         if (rp[i] > col) break;
1812:         if (rp[i] == col) {
1813:           if (A->structure_only) goto noinsert2;
1814:           bap = ap +  bs2*i;
1815:           if (roworiented) {
1816:             if (is == ADD_VALUES) {
1817:               for (ii=0; ii<bs; ii++,value+=stepval) {
1818:                 for (jj=ii; jj<bs2; jj+=bs) {
1819:                   bap[jj] += *value++;
1820:                 }
1821:               }
1822:             } else {
1823:               for (ii=0; ii<bs; ii++,value+=stepval) {
1824:                 for (jj=ii; jj<bs2; jj+=bs) {
1825:                   bap[jj] = *value++;
1826:                 }
1827:               }
1828:             }
1829:           } else {
1830:             if (is == ADD_VALUES) {
1831:               for (ii=0; ii<bs; ii++,value+=bs+stepval) {
1832:                 for (jj=0; jj<bs; jj++) {
1833:                   bap[jj] += value[jj];
1834:                 }
1835:                 bap += bs;
1836:               }
1837:             } else {
1838:               for (ii=0; ii<bs; ii++,value+=bs+stepval) {
1839:                 for (jj=0; jj<bs; jj++) {
1840:                   bap[jj]  = value[jj];
1841:                 }
1842:                 bap += bs;
1843:               }
1844:             }
1845:           }
1846:           goto noinsert2;
1847:         }
1848:       }
1849:       if (nonew == 1) goto noinsert2;
1850:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new blocked index new nonzero block (%D, %D) in the matrix", row, col);
1851:       if (A->structure_only) {
1852:         MatSeqXAIJReallocateAIJ_structure_only(A,a->mbs,bs2,nrow,row,col,rmax,ai,aj,rp,imax,nonew,MatScalar);
1853:       } else {
1854:         MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,row,col,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
1855:       }
1856:       N = nrow++ - 1; high++;
1857:       /* shift up all the later entries in this row */
1858:       for (ii=N; ii>=i; ii--) {
1859:         rp[ii+1] = rp[ii];
1860:         if (!A->structure_only) {
1861:           PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
1862:         }
1863:       }
1864:       if (N >= i && !A->structure_only) {
1865:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
1866:       }

1868:       rp[i] = col;
1869:       if (!A->structure_only) {
1870:         bap   = ap +  bs2*i;
1871:         if (roworiented) {
1872:           for (ii=0; ii<bs; ii++,value+=stepval) {
1873:             for (jj=ii; jj<bs2; jj+=bs) {
1874:               bap[jj] = *value++;
1875:             }
1876:           }
1877:         } else {
1878:           for (ii=0; ii<bs; ii++,value+=stepval) {
1879:             for (jj=0; jj<bs; jj++) {
1880:               *bap++ = *value++;
1881:             }
1882:           }
1883:         }
1884:       }
1885: noinsert2:;
1886:       low = i;
1887:     }
1888:     ailen[row] = nrow;
1889:   }
1890:   return(0);
1891: }

1893: PetscErrorCode MatAssemblyEnd_SeqBAIJ(Mat A,MatAssemblyType mode)
1894: {
1895:   Mat_SeqBAIJ    *a     = (Mat_SeqBAIJ*)A->data;
1896:   PetscInt       fshift = 0,i,j,*ai = a->i,*aj = a->j,*imax = a->imax;
1897:   PetscInt       m      = A->rmap->N,*ip,N,*ailen = a->ilen;
1899:   PetscInt       mbs  = a->mbs,bs2 = a->bs2,rmax = 0;
1900:   MatScalar      *aa  = a->a,*ap;
1901:   PetscReal      ratio=0.6;

1904:   if (mode == MAT_FLUSH_ASSEMBLY) return(0);

1906:   if (m) rmax = ailen[0];
1907:   for (i=1; i<mbs; i++) {
1908:     /* move each row back by the amount of empty slots (fshift) before it*/
1909:     fshift += imax[i-1] - ailen[i-1];
1910:     rmax    = PetscMax(rmax,ailen[i]);
1911:     if (fshift) {
1912:       ip = aj + ai[i]; ap = aa + bs2*ai[i];
1913:       N  = ailen[i];
1914:       for (j=0; j<N; j++) {
1915:         ip[j-fshift] = ip[j];
1916:         if (!A->structure_only) {
1917:           PetscMemcpy(ap+(j-fshift)*bs2,ap+j*bs2,bs2*sizeof(MatScalar));
1918:         }
1919:       }
1920:     }
1921:     ai[i] = ai[i-1] + ailen[i-1];
1922:   }
1923:   if (mbs) {
1924:     fshift += imax[mbs-1] - ailen[mbs-1];
1925:     ai[mbs] = ai[mbs-1] + ailen[mbs-1];
1926:   }

1928:   /* reset ilen and imax for each row */
1929:   a->nonzerorowcnt = 0;
1930:   if (A->structure_only) {
1931:     PetscFree2(a->imax,a->ilen);
1932:   } else { /* !A->structure_only */
1933:     for (i=0; i<mbs; i++) {
1934:       ailen[i] = imax[i] = ai[i+1] - ai[i];
1935:       a->nonzerorowcnt += ((ai[i+1] - ai[i]) > 0);
1936:     }
1937:   }
1938:   a->nz = ai[mbs];

1940:   /* diagonals may have moved, so kill the diagonal pointers */
1941:   a->idiagvalid = PETSC_FALSE;
1942:   if (fshift && a->diag) {
1943:     PetscFree(a->diag);
1944:     PetscLogObjectMemory((PetscObject)A,-(mbs+1)*sizeof(PetscInt));
1945:     a->diag = 0;
1946:   }
1947:   if (fshift && a->nounused == -1) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_PLIB, "Unused space detected in matrix: %D X %D block size %D, %D unneeded", m, A->cmap->n, A->rmap->bs, fshift*bs2);
1948:   PetscInfo5(A,"Matrix size: %D X %D, block size %D; storage space: %D unneeded, %D used\n",m,A->cmap->n,A->rmap->bs,fshift*bs2,a->nz*bs2);
1949:   PetscInfo1(A,"Number of mallocs during MatSetValues is %D\n",a->reallocs);
1950:   PetscInfo1(A,"Most nonzeros blocks in any row is %D\n",rmax);

1952:   A->info.mallocs    += a->reallocs;
1953:   a->reallocs         = 0;
1954:   A->info.nz_unneeded = (PetscReal)fshift*bs2;
1955:   a->rmax             = rmax;

1957:   if (!A->structure_only) {
1958:     MatCheckCompressedRow(A,a->nonzerorowcnt,&a->compressedrow,a->i,mbs,ratio);
1959:   }
1960:   return(0);
1961: }

1963: /*
1964:    This function returns an array of flags which indicate the locations of contiguous
1965:    blocks that should be zeroed. for eg: if bs = 3  and is = [0,1,2,3,5,6,7,8,9]
1966:    then the resulting sizes = [3,1,1,3,1] correspondig to sets [(0,1,2),(3),(5),(6,7,8),(9)]
1967:    Assume: sizes should be long enough to hold all the values.
1968: */
1969: static PetscErrorCode MatZeroRows_SeqBAIJ_Check_Blocks(PetscInt idx[],PetscInt n,PetscInt bs,PetscInt sizes[], PetscInt *bs_max)
1970: {
1971:   PetscInt  i,j,k,row;
1972:   PetscBool flg;

1975:   for (i=0,j=0; i<n; j++) {
1976:     row = idx[i];
1977:     if (row%bs!=0) { /* Not the begining of a block */
1978:       sizes[j] = 1;
1979:       i++;
1980:     } else if (i+bs > n) { /* complete block doesn't exist (at idx end) */
1981:       sizes[j] = 1;         /* Also makes sure atleast 'bs' values exist for next else */
1982:       i++;
1983:     } else { /* Begining of the block, so check if the complete block exists */
1984:       flg = PETSC_TRUE;
1985:       for (k=1; k<bs; k++) {
1986:         if (row+k != idx[i+k]) { /* break in the block */
1987:           flg = PETSC_FALSE;
1988:           break;
1989:         }
1990:       }
1991:       if (flg) { /* No break in the bs */
1992:         sizes[j] = bs;
1993:         i       += bs;
1994:       } else {
1995:         sizes[j] = 1;
1996:         i++;
1997:       }
1998:     }
1999:   }
2000:   *bs_max = j;
2001:   return(0);
2002: }

2004: PetscErrorCode MatZeroRows_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
2005: {
2006:   Mat_SeqBAIJ       *baij=(Mat_SeqBAIJ*)A->data;
2007:   PetscErrorCode    ierr;
2008:   PetscInt          i,j,k,count,*rows;
2009:   PetscInt          bs=A->rmap->bs,bs2=baij->bs2,*sizes,row,bs_max;
2010:   PetscScalar       zero = 0.0;
2011:   MatScalar         *aa;
2012:   const PetscScalar *xx;
2013:   PetscScalar       *bb;

2016:   /* fix right hand side if needed */
2017:   if (x && b) {
2018:     VecGetArrayRead(x,&xx);
2019:     VecGetArray(b,&bb);
2020:     for (i=0; i<is_n; i++) {
2021:       bb[is_idx[i]] = diag*xx[is_idx[i]];
2022:     }
2023:     VecRestoreArrayRead(x,&xx);
2024:     VecRestoreArray(b,&bb);
2025:   }

2027:   /* Make a copy of the IS and  sort it */
2028:   /* allocate memory for rows,sizes */
2029:   PetscMalloc2(is_n,&rows,2*is_n,&sizes);

2031:   /* copy IS values to rows, and sort them */
2032:   for (i=0; i<is_n; i++) rows[i] = is_idx[i];
2033:   PetscSortInt(is_n,rows);

2035:   if (baij->keepnonzeropattern) {
2036:     for (i=0; i<is_n; i++) sizes[i] = 1;
2037:     bs_max          = is_n;
2038:   } else {
2039:     MatZeroRows_SeqBAIJ_Check_Blocks(rows,is_n,bs,sizes,&bs_max);
2040:     A->nonzerostate++;
2041:   }

2043:   for (i=0,j=0; i<bs_max; j+=sizes[i],i++) {
2044:     row = rows[j];
2045:     if (row < 0 || row > A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",row);
2046:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
2047:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
2048:     if (sizes[i] == bs && !baij->keepnonzeropattern) {
2049:       if (diag != (PetscScalar)0.0) {
2050:         if (baij->ilen[row/bs] > 0) {
2051:           baij->ilen[row/bs]       = 1;
2052:           baij->j[baij->i[row/bs]] = row/bs;

2054:           PetscMemzero(aa,count*bs*sizeof(MatScalar));
2055:         }
2056:         /* Now insert all the diagonal values for this bs */
2057:         for (k=0; k<bs; k++) {
2058:           (*A->ops->setvalues)(A,1,rows+j+k,1,rows+j+k,&diag,INSERT_VALUES);
2059:         }
2060:       } else { /* (diag == 0.0) */
2061:         baij->ilen[row/bs] = 0;
2062:       } /* end (diag == 0.0) */
2063:     } else { /* (sizes[i] != bs) */
2064: #if defined(PETSC_USE_DEBUG)
2065:       if (sizes[i] != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Internal Error. Value should be 1");
2066: #endif
2067:       for (k=0; k<count; k++) {
2068:         aa[0] =  zero;
2069:         aa   += bs;
2070:       }
2071:       if (diag != (PetscScalar)0.0) {
2072:         (*A->ops->setvalues)(A,1,rows+j,1,rows+j,&diag,INSERT_VALUES);
2073:       }
2074:     }
2075:   }

2077:   PetscFree2(rows,sizes);
2078:   MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
2079:   return(0);
2080: }

2082: PetscErrorCode MatZeroRowsColumns_SeqBAIJ(Mat A,PetscInt is_n,const PetscInt is_idx[],PetscScalar diag,Vec x, Vec b)
2083: {
2084:   Mat_SeqBAIJ       *baij=(Mat_SeqBAIJ*)A->data;
2085:   PetscErrorCode    ierr;
2086:   PetscInt          i,j,k,count;
2087:   PetscInt          bs   =A->rmap->bs,bs2=baij->bs2,row,col;
2088:   PetscScalar       zero = 0.0;
2089:   MatScalar         *aa;
2090:   const PetscScalar *xx;
2091:   PetscScalar       *bb;
2092:   PetscBool         *zeroed,vecs = PETSC_FALSE;

2095:   /* fix right hand side if needed */
2096:   if (x && b) {
2097:     VecGetArrayRead(x,&xx);
2098:     VecGetArray(b,&bb);
2099:     vecs = PETSC_TRUE;
2100:   }

2102:   /* zero the columns */
2103:   PetscCalloc1(A->rmap->n,&zeroed);
2104:   for (i=0; i<is_n; i++) {
2105:     if (is_idx[i] < 0 || is_idx[i] >= A->rmap->N) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"row %D out of range",is_idx[i]);
2106:     zeroed[is_idx[i]] = PETSC_TRUE;
2107:   }
2108:   for (i=0; i<A->rmap->N; i++) {
2109:     if (!zeroed[i]) {
2110:       row = i/bs;
2111:       for (j=baij->i[row]; j<baij->i[row+1]; j++) {
2112:         for (k=0; k<bs; k++) {
2113:           col = bs*baij->j[j] + k;
2114:           if (zeroed[col]) {
2115:             aa = ((MatScalar*)(baij->a)) + j*bs2 + (i%bs) + bs*k;
2116:             if (vecs) bb[i] -= aa[0]*xx[col];
2117:             aa[0] = 0.0;
2118:           }
2119:         }
2120:       }
2121:     } else if (vecs) bb[i] = diag*xx[i];
2122:   }
2123:   PetscFree(zeroed);
2124:   if (vecs) {
2125:     VecRestoreArrayRead(x,&xx);
2126:     VecRestoreArray(b,&bb);
2127:   }

2129:   /* zero the rows */
2130:   for (i=0; i<is_n; i++) {
2131:     row   = is_idx[i];
2132:     count = (baij->i[row/bs +1] - baij->i[row/bs])*bs;
2133:     aa    = ((MatScalar*)(baij->a)) + baij->i[row/bs]*bs2 + (row%bs);
2134:     for (k=0; k<count; k++) {
2135:       aa[0] =  zero;
2136:       aa   += bs;
2137:     }
2138:     if (diag != (PetscScalar)0.0) {
2139:       (*A->ops->setvalues)(A,1,&row,1,&row,&diag,INSERT_VALUES);
2140:     }
2141:   }
2142:   MatAssemblyEnd_SeqBAIJ(A,MAT_FINAL_ASSEMBLY);
2143:   return(0);
2144: }

2146: PetscErrorCode MatSetValues_SeqBAIJ(Mat A,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode is)
2147: {
2148:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
2149:   PetscInt       *rp,k,low,high,t,ii,row,nrow,i,col,l,rmax,N,lastcol = -1;
2150:   PetscInt       *imax=a->imax,*ai=a->i,*ailen=a->ilen;
2151:   PetscInt       *aj  =a->j,nonew=a->nonew,bs=A->rmap->bs,brow,bcol;
2153:   PetscInt       ridx,cidx,bs2=a->bs2;
2154:   PetscBool      roworiented=a->roworiented;
2155:   MatScalar      *ap=NULL,value=0.0,*aa=a->a,*bap;

2158:   for (k=0; k<m; k++) { /* loop over added rows */
2159:     row  = im[k];
2160:     brow = row/bs;
2161:     if (row < 0) continue;
2162: #if defined(PETSC_USE_DEBUG)
2163:     if (row >= A->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",row,A->rmap->N-1);
2164: #endif
2165:     rp   = aj + ai[brow];
2166:     if (!A->structure_only) ap = aa + bs2*ai[brow];
2167:     rmax = imax[brow];
2168:     nrow = ailen[brow];
2169:     low  = 0;
2170:     high = nrow;
2171:     for (l=0; l<n; l++) { /* loop over added columns */
2172:       if (in[l] < 0) continue;
2173: #if defined(PETSC_USE_DEBUG)
2174:       if (in[l] >= A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[l],A->cmap->n-1);
2175: #endif
2176:       col  = in[l]; bcol = col/bs;
2177:       ridx = row % bs; cidx = col % bs;
2178:       if (!A->structure_only) {
2179:         if (roworiented) {
2180:           value = v[l + k*n];
2181:         } else {
2182:           value = v[k + l*m];
2183:         }
2184:       }
2185:       if (col <= lastcol) low = 0; else high = nrow;
2186:       lastcol = col;
2187:       while (high-low > 7) {
2188:         t = (low+high)/2;
2189:         if (rp[t] > bcol) high = t;
2190:         else              low  = t;
2191:       }
2192:       for (i=low; i<high; i++) {
2193:         if (rp[i] > bcol) break;
2194:         if (rp[i] == bcol) {
2195:           bap = ap +  bs2*i + bs*cidx + ridx;
2196:           if (!A->structure_only) {
2197:             if (is == ADD_VALUES) *bap += value;
2198:             else                  *bap  = value;
2199:           }
2200:           goto noinsert1;
2201:         }
2202:       }
2203:       if (nonew == 1) goto noinsert1;
2204:       if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero (%D, %D) in the matrix", row, col);
2205:       if (A->structure_only) {
2206:         MatSeqXAIJReallocateAIJ_structure_only(A,a->mbs,bs2,nrow,brow,bcol,rmax,ai,aj,rp,imax,nonew,MatScalar);
2207:       } else {
2208:         MatSeqXAIJReallocateAIJ(A,a->mbs,bs2,nrow,brow,bcol,rmax,aa,ai,aj,rp,ap,imax,nonew,MatScalar);
2209:       }
2210:       N = nrow++ - 1; high++;
2211:       /* shift up all the later entries in this row */
2212:       for (ii=N; ii>=i; ii--) {
2213:         rp[ii+1] = rp[ii];
2214:         if (!A->structure_only) {
2215:           PetscMemcpy(ap+bs2*(ii+1),ap+bs2*(ii),bs2*sizeof(MatScalar));
2216:         }
2217:       }
2218:       if (N>=i && !A->structure_only) {
2219:         PetscMemzero(ap+bs2*i,bs2*sizeof(MatScalar));
2220:       }
2221:       rp[i]                      = bcol;
2222:       if (!A->structure_only) ap[bs2*i + bs*cidx + ridx] = value;
2223:       a->nz++;
2224:       A->nonzerostate++;
2225: noinsert1:;
2226:       low = i;
2227:     }
2228:     ailen[brow] = nrow;
2229:   }
2230:   return(0);
2231: }

2233: PetscErrorCode MatILUFactor_SeqBAIJ(Mat inA,IS row,IS col,const MatFactorInfo *info)
2234: {
2235:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)inA->data;
2236:   Mat            outA;
2238:   PetscBool      row_identity,col_identity;

2241:   if (info->levels != 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only levels = 0 supported for in-place ILU");
2242:   ISIdentity(row,&row_identity);
2243:   ISIdentity(col,&col_identity);
2244:   if (!row_identity || !col_identity) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Row and column permutations must be identity for in-place ILU");

2246:   outA            = inA;
2247:   inA->factortype = MAT_FACTOR_LU;
2248:   PetscFree(inA->solvertype);
2249:   PetscStrallocpy(MATSOLVERPETSC,&inA->solvertype);

2251:   MatMarkDiagonal_SeqBAIJ(inA);

2253:   PetscObjectReference((PetscObject)row);
2254:   ISDestroy(&a->row);
2255:   a->row = row;
2256:   PetscObjectReference((PetscObject)col);
2257:   ISDestroy(&a->col);
2258:   a->col = col;

2260:   /* Create the invert permutation so that it can be used in MatLUFactorNumeric() */
2261:   ISDestroy(&a->icol);
2262:   ISInvertPermutation(col,PETSC_DECIDE,&a->icol);
2263:   PetscLogObjectParent((PetscObject)inA,(PetscObject)a->icol);

2265:   MatSeqBAIJSetNumericFactorization_inplace(inA,(PetscBool)(row_identity && col_identity));
2266:   if (!a->solve_work) {
2267:     PetscMalloc1(inA->rmap->N+inA->rmap->bs,&a->solve_work);
2268:     PetscLogObjectMemory((PetscObject)inA,(inA->rmap->N+inA->rmap->bs)*sizeof(PetscScalar));
2269:   }
2270:   MatLUFactorNumeric(outA,inA,info);
2271:   return(0);
2272: }

2274: PetscErrorCode  MatSeqBAIJSetColumnIndices_SeqBAIJ(Mat mat,PetscInt *indices)
2275: {
2276:   Mat_SeqBAIJ *baij = (Mat_SeqBAIJ*)mat->data;
2277:   PetscInt    i,nz,mbs;

2280:   nz  = baij->maxnz;
2281:   mbs = baij->mbs;
2282:   for (i=0; i<nz; i++) {
2283:     baij->j[i] = indices[i];
2284:   }
2285:   baij->nz = nz;
2286:   for (i=0; i<mbs; i++) {
2287:     baij->ilen[i] = baij->imax[i];
2288:   }
2289:   return(0);
2290: }

2292: /*@
2293:     MatSeqBAIJSetColumnIndices - Set the column indices for all the rows
2294:        in the matrix.

2296:   Input Parameters:
2297: +  mat - the SeqBAIJ matrix
2298: -  indices - the column indices

2300:   Level: advanced

2302:   Notes:
2303:     This can be called if you have precomputed the nonzero structure of the
2304:   matrix and want to provide it to the matrix object to improve the performance
2305:   of the MatSetValues() operation.

2307:     You MUST have set the correct numbers of nonzeros per row in the call to
2308:   MatCreateSeqBAIJ(), and the columns indices MUST be sorted.

2310:     MUST be called before any calls to MatSetValues();

2312: @*/
2313: PetscErrorCode  MatSeqBAIJSetColumnIndices(Mat mat,PetscInt *indices)
2314: {

2320:   PetscUseMethod(mat,"MatSeqBAIJSetColumnIndices_C",(Mat,PetscInt*),(mat,indices));
2321:   return(0);
2322: }

2324: PetscErrorCode MatGetRowMaxAbs_SeqBAIJ(Mat A,Vec v,PetscInt idx[])
2325: {
2326:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
2328:   PetscInt       i,j,n,row,bs,*ai,*aj,mbs;
2329:   PetscReal      atmp;
2330:   PetscScalar    *x,zero = 0.0;
2331:   MatScalar      *aa;
2332:   PetscInt       ncols,brow,krow,kcol;

2335:   if (A->factortype) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"Not for factored matrix");
2336:   bs  = A->rmap->bs;
2337:   aa  = a->a;
2338:   ai  = a->i;
2339:   aj  = a->j;
2340:   mbs = a->mbs;

2342:   VecSet(v,zero);
2343:   VecGetArray(v,&x);
2344:   VecGetLocalSize(v,&n);
2345:   if (n != A->rmap->N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Nonconforming matrix and vector");
2346:   for (i=0; i<mbs; i++) {
2347:     ncols = ai[1] - ai[0]; ai++;
2348:     brow  = bs*i;
2349:     for (j=0; j<ncols; j++) {
2350:       for (kcol=0; kcol<bs; kcol++) {
2351:         for (krow=0; krow<bs; krow++) {
2352:           atmp = PetscAbsScalar(*aa);aa++;
2353:           row  = brow + krow;   /* row index */
2354:           if (PetscAbsScalar(x[row]) < atmp) {x[row] = atmp; if (idx) idx[row] = bs*(*aj) + kcol;}
2355:         }
2356:       }
2357:       aj++;
2358:     }
2359:   }
2360:   VecRestoreArray(v,&x);
2361:   return(0);
2362: }

2364: PetscErrorCode MatCopy_SeqBAIJ(Mat A,Mat B,MatStructure str)
2365: {

2369:   /* If the two matrices have the same copy implementation, use fast copy. */
2370:   if (str == SAME_NONZERO_PATTERN && (A->ops->copy == B->ops->copy)) {
2371:     Mat_SeqBAIJ *a  = (Mat_SeqBAIJ*)A->data;
2372:     Mat_SeqBAIJ *b  = (Mat_SeqBAIJ*)B->data;
2373:     PetscInt    ambs=a->mbs,bmbs=b->mbs,abs=A->rmap->bs,bbs=B->rmap->bs,bs2=abs*abs;

2375:     if (a->i[ambs] != b->i[bmbs]) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Number of nonzero blocks in matrices A %D and B %D are different",a->i[ambs],b->i[bmbs]);
2376:     if (abs != bbs) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_INCOMP,"Block size A %D and B %D are different",abs,bbs);
2377:     PetscMemcpy(b->a,a->a,(bs2*a->i[ambs])*sizeof(PetscScalar));
2378:     PetscObjectStateIncrease((PetscObject)B);
2379:   } else {
2380:     MatCopy_Basic(A,B,str);
2381:   }
2382:   return(0);
2383: }

2385: PetscErrorCode MatSetUp_SeqBAIJ(Mat A)
2386: {

2390:   MatSeqBAIJSetPreallocation(A,A->rmap->bs,PETSC_DEFAULT,0);
2391:   return(0);
2392: }

2394: PetscErrorCode MatSeqBAIJGetArray_SeqBAIJ(Mat A,PetscScalar *array[])
2395: {
2396:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;

2399:   *array = a->a;
2400:   return(0);
2401: }

2403: PetscErrorCode MatSeqBAIJRestoreArray_SeqBAIJ(Mat A,PetscScalar *array[])
2404: {
2406:   return(0);
2407: }

2409: PetscErrorCode MatAXPYGetPreallocation_SeqBAIJ(Mat Y,Mat X,PetscInt *nnz)
2410: {
2411:   PetscInt       bs = Y->rmap->bs,mbs = Y->rmap->N/bs;
2412:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data;
2413:   Mat_SeqBAIJ    *y = (Mat_SeqBAIJ*)Y->data;

2417:   /* Set the number of nonzeros in the new matrix */
2418:   MatAXPYGetPreallocation_SeqX_private(mbs,x->i,x->j,y->i,y->j,nnz);
2419:   return(0);
2420: }

2422: PetscErrorCode MatAXPY_SeqBAIJ(Mat Y,PetscScalar a,Mat X,MatStructure str)
2423: {
2424:   Mat_SeqBAIJ    *x = (Mat_SeqBAIJ*)X->data,*y = (Mat_SeqBAIJ*)Y->data;
2426:   PetscInt       bs=Y->rmap->bs,bs2=bs*bs;
2427:   PetscBLASInt   one=1;

2430:   if (str == SAME_NONZERO_PATTERN) {
2431:     PetscScalar  alpha = a;
2432:     PetscBLASInt bnz;
2433:     PetscBLASIntCast(x->nz*bs2,&bnz);
2434:     PetscStackCallBLAS("BLASaxpy",BLASaxpy_(&bnz,&alpha,x->a,&one,y->a,&one));
2435:     PetscObjectStateIncrease((PetscObject)Y);
2436:   } else if (str == SUBSET_NONZERO_PATTERN) { /* nonzeros of X is a subset of Y's */
2437:     MatAXPY_Basic(Y,a,X,str);
2438:   } else {
2439:     Mat      B;
2440:     PetscInt *nnz;
2441:     if (bs != X->rmap->bs) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Matrices must have same block size");
2442:     PetscMalloc1(Y->rmap->N,&nnz);
2443:     MatCreate(PetscObjectComm((PetscObject)Y),&B);
2444:     PetscObjectSetName((PetscObject)B,((PetscObject)Y)->name);
2445:     MatSetSizes(B,Y->rmap->n,Y->cmap->n,Y->rmap->N,Y->cmap->N);
2446:     MatSetBlockSizesFromMats(B,Y,Y);
2447:     MatSetType(B,(MatType) ((PetscObject)Y)->type_name);
2448:     MatAXPYGetPreallocation_SeqBAIJ(Y,X,nnz);
2449:     MatSeqBAIJSetPreallocation(B,bs,0,nnz);
2450:     MatAXPY_BasicWithPreallocation(B,Y,a,X,str);
2451:     MatHeaderReplace(Y,&B);
2452:     PetscFree(nnz);
2453:   }
2454:   return(0);
2455: }

2457: PetscErrorCode MatRealPart_SeqBAIJ(Mat A)
2458: {
2459:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2460:   PetscInt    i,nz = a->bs2*a->i[a->mbs];
2461:   MatScalar   *aa = a->a;

2464:   for (i=0; i<nz; i++) aa[i] = PetscRealPart(aa[i]);
2465:   return(0);
2466: }

2468: PetscErrorCode MatImaginaryPart_SeqBAIJ(Mat A)
2469: {
2470:   Mat_SeqBAIJ *a = (Mat_SeqBAIJ*)A->data;
2471:   PetscInt    i,nz = a->bs2*a->i[a->mbs];
2472:   MatScalar   *aa = a->a;

2475:   for (i=0; i<nz; i++) aa[i] = PetscImaginaryPart(aa[i]);
2476:   return(0);
2477: }

2479: /*
2480:     Code almost idential to MatGetColumnIJ_SeqAIJ() should share common code
2481: */
2482: PetscErrorCode MatGetColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
2483: {
2484:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
2486:   PetscInt       bs = A->rmap->bs,i,*collengths,*cia,*cja,n = A->cmap->n/bs,m = A->rmap->n/bs;
2487:   PetscInt       nz = a->i[m],row,*jj,mr,col;

2490:   *nn = n;
2491:   if (!ia) return(0);
2492:   if (symmetric) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not for BAIJ matrices");
2493:   else {
2494:     PetscCalloc1(n+1,&collengths);
2495:     PetscMalloc1(n+1,&cia);
2496:     PetscMalloc1(nz+1,&cja);
2497:     jj   = a->j;
2498:     for (i=0; i<nz; i++) {
2499:       collengths[jj[i]]++;
2500:     }
2501:     cia[0] = oshift;
2502:     for (i=0; i<n; i++) {
2503:       cia[i+1] = cia[i] + collengths[i];
2504:     }
2505:     PetscMemzero(collengths,n*sizeof(PetscInt));
2506:     jj   = a->j;
2507:     for (row=0; row<m; row++) {
2508:       mr = a->i[row+1] - a->i[row];
2509:       for (i=0; i<mr; i++) {
2510:         col = *jj++;

2512:         cja[cia[col] + collengths[col]++ - oshift] = row + oshift;
2513:       }
2514:     }
2515:     PetscFree(collengths);
2516:     *ia  = cia; *ja = cja;
2517:   }
2518:   return(0);
2519: }

2521: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscBool  *done)
2522: {

2526:   if (!ia) return(0);
2527:   PetscFree(*ia);
2528:   PetscFree(*ja);
2529:   return(0);
2530: }

2532: /*
2533:  MatGetColumnIJ_SeqBAIJ_Color() and MatRestoreColumnIJ_SeqBAIJ_Color() are customized from
2534:  MatGetColumnIJ_SeqBAIJ() and MatRestoreColumnIJ_SeqBAIJ() by adding an output
2535:  spidx[], index of a->a, to be used in MatTransposeColoringCreate() and MatFDColoringCreate()
2536:  */
2537: PetscErrorCode MatGetColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *nn,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool  *done)
2538: {
2539:   Mat_SeqBAIJ    *a = (Mat_SeqBAIJ*)A->data;
2541:   PetscInt       i,*collengths,*cia,*cja,n=a->nbs,m=a->mbs;
2542:   PetscInt       nz = a->i[m],row,*jj,mr,col;
2543:   PetscInt       *cspidx;

2546:   *nn = n;
2547:   if (!ia) return(0);

2549:   PetscCalloc1(n+1,&collengths);
2550:   PetscMalloc1(n+1,&cia);
2551:   PetscMalloc1(nz+1,&cja);
2552:   PetscMalloc1(nz+1,&cspidx);
2553:   jj   = a->j;
2554:   for (i=0; i<nz; i++) {
2555:     collengths[jj[i]]++;
2556:   }
2557:   cia[0] = oshift;
2558:   for (i=0; i<n; i++) {
2559:     cia[i+1] = cia[i] + collengths[i];
2560:   }
2561:   PetscMemzero(collengths,n*sizeof(PetscInt));
2562:   jj   = a->j;
2563:   for (row=0; row<m; row++) {
2564:     mr = a->i[row+1] - a->i[row];
2565:     for (i=0; i<mr; i++) {
2566:       col = *jj++;
2567:       cspidx[cia[col] + collengths[col] - oshift] = a->i[row] + i; /* index of a->j */
2568:       cja[cia[col] + collengths[col]++ - oshift]  = row + oshift;
2569:     }
2570:   }
2571:   PetscFree(collengths);
2572:   *ia    = cia; *ja = cja;
2573:   *spidx = cspidx;
2574:   return(0);
2575: }

2577: PetscErrorCode MatRestoreColumnIJ_SeqBAIJ_Color(Mat A,PetscInt oshift,PetscBool symmetric,PetscBool inodecompressed,PetscInt *n,const PetscInt *ia[],const PetscInt *ja[],PetscInt *spidx[],PetscBool  *done)
2578: {

2582:   MatRestoreColumnIJ_SeqBAIJ(A,oshift,symmetric,inodecompressed,n,ia,ja,done);
2583:   PetscFree(*spidx);
2584:   return(0);
2585: }

2587: PetscErrorCode MatShift_SeqBAIJ(Mat Y,PetscScalar a)
2588: {
2590:   Mat_SeqBAIJ     *aij = (Mat_SeqBAIJ*)Y->data;

2593:   if (!Y->preallocated || !aij->nz) {
2594:     MatSeqBAIJSetPreallocation(Y,Y->rmap->bs,1,NULL);
2595:   }
2596:   MatShift_Basic(Y,a);
2597:   return(0);
2598: }

2600: /* -------------------------------------------------------------------*/
2601: static struct _MatOps MatOps_Values = {MatSetValues_SeqBAIJ,
2602:                                        MatGetRow_SeqBAIJ,
2603:                                        MatRestoreRow_SeqBAIJ,
2604:                                        MatMult_SeqBAIJ_N,
2605:                                /* 4*/  MatMultAdd_SeqBAIJ_N,
2606:                                        MatMultTranspose_SeqBAIJ,
2607:                                        MatMultTransposeAdd_SeqBAIJ,
2608:                                        0,
2609:                                        0,
2610:                                        0,
2611:                                /* 10*/ 0,
2612:                                        MatLUFactor_SeqBAIJ,
2613:                                        0,
2614:                                        0,
2615:                                        MatTranspose_SeqBAIJ,
2616:                                /* 15*/ MatGetInfo_SeqBAIJ,
2617:                                        MatEqual_SeqBAIJ,
2618:                                        MatGetDiagonal_SeqBAIJ,
2619:                                        MatDiagonalScale_SeqBAIJ,
2620:                                        MatNorm_SeqBAIJ,
2621:                                /* 20*/ 0,
2622:                                        MatAssemblyEnd_SeqBAIJ,
2623:                                        MatSetOption_SeqBAIJ,
2624:                                        MatZeroEntries_SeqBAIJ,
2625:                                /* 24*/ MatZeroRows_SeqBAIJ,
2626:                                        0,
2627:                                        0,
2628:                                        0,
2629:                                        0,
2630:                                /* 29*/ MatSetUp_SeqBAIJ,
2631:                                        0,
2632:                                        0,
2633:                                        0,
2634:                                        0,
2635:                                /* 34*/ MatDuplicate_SeqBAIJ,
2636:                                        0,
2637:                                        0,
2638:                                        MatILUFactor_SeqBAIJ,
2639:                                        0,
2640:                                /* 39*/ MatAXPY_SeqBAIJ,
2641:                                        MatCreateSubMatrices_SeqBAIJ,
2642:                                        MatIncreaseOverlap_SeqBAIJ,
2643:                                        MatGetValues_SeqBAIJ,
2644:                                        MatCopy_SeqBAIJ,
2645:                                /* 44*/ 0,
2646:                                        MatScale_SeqBAIJ,
2647:                                        MatShift_SeqBAIJ,
2648:                                        0,
2649:                                        MatZeroRowsColumns_SeqBAIJ,
2650:                                /* 49*/ 0,
2651:                                        MatGetRowIJ_SeqBAIJ,
2652:                                        MatRestoreRowIJ_SeqBAIJ,
2653:                                        MatGetColumnIJ_SeqBAIJ,
2654:                                        MatRestoreColumnIJ_SeqBAIJ,
2655:                                /* 54*/ MatFDColoringCreate_SeqXAIJ,
2656:                                        0,
2657:                                        0,
2658:                                        0,
2659:                                        MatSetValuesBlocked_SeqBAIJ,
2660:                                /* 59*/ MatCreateSubMatrix_SeqBAIJ,
2661:                                        MatDestroy_SeqBAIJ,
2662:                                        MatView_SeqBAIJ,
2663:                                        0,
2664:                                        0,
2665:                                /* 64*/ 0,
2666:                                        0,
2667:                                        0,
2668:                                        0,
2669:                                        0,
2670:                                /* 69*/ MatGetRowMaxAbs_SeqBAIJ,
2671:                                        0,
2672:                                        MatConvert_Basic,
2673:                                        0,
2674:                                        0,
2675:                                /* 74*/ 0,
2676:                                        MatFDColoringApply_BAIJ,
2677:                                        0,
2678:                                        0,
2679:                                        0,
2680:                                /* 79*/ 0,
2681:                                        0,
2682:                                        0,
2683:                                        0,
2684:                                        MatLoad_SeqBAIJ,
2685:                                /* 84*/ 0,
2686:                                        0,
2687:                                        0,
2688:                                        0,
2689:                                        0,
2690:                                /* 89*/ 0,
2691:                                        0,
2692:                                        0,
2693:                                        0,
2694:                                        0,
2695:                                /* 94*/ 0,
2696:                                        0,
2697:                                        0,
2698:                                        0,
2699:                                        0,
2700:                                /* 99*/ 0,
2701:                                        0,
2702:                                        0,
2703:                                        0,
2704:                                        0,
2705:                                /*104*/ 0,
2706:                                        MatRealPart_SeqBAIJ,
2707:                                        MatImaginaryPart_SeqBAIJ,
2708:                                        0,
2709:                                        0,
2710:                                /*109*/ 0,
2711:                                        0,
2712:                                        0,
2713:                                        0,
2714:                                        MatMissingDiagonal_SeqBAIJ,
2715:                                /*114*/ 0,
2716:                                        0,
2717:                                        0,
2718:                                        0,
2719:                                        0,
2720:                                /*119*/ 0,
2721:                                        0,
2722:                                        MatMultHermitianTranspose_SeqBAIJ,
2723:                                        MatMultHermitianTransposeAdd_SeqBAIJ,
2724:                                        0,
2725:                                /*124*/ 0,
2726:                                        0,
2727:                                        MatInvertBlockDiagonal_SeqBAIJ,
2728:                                        0,
2729:                                        0,
2730:                                /*129*/ 0,
2731:                                        0,
2732:                                        0,
2733:                                        0,
2734:                                        0,
2735:                                /*134*/ 0,
2736:                                        0,
2737:                                        0,
2738:                                        0,
2739:                                        0,
2740:                                /*139*/ MatSetBlockSizes_Default,
2741:                                        0,
2742:                                        0,
2743:                                        MatFDColoringSetUp_SeqXAIJ,
2744:                                        0,
2745:                                 /*144*/MatCreateMPIMatConcatenateSeqMat_SeqBAIJ,
2746:                                        MatDestroySubMatrices_SeqBAIJ
2747: };

2749: PetscErrorCode  MatStoreValues_SeqBAIJ(Mat mat)
2750: {
2751:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)mat->data;
2752:   PetscInt       nz   = aij->i[aij->mbs]*aij->bs2;

2756:   if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");

2758:   /* allocate space for values if not already there */
2759:   if (!aij->saved_values) {
2760:     PetscMalloc1(nz+1,&aij->saved_values);
2761:     PetscLogObjectMemory((PetscObject)mat,(nz+1)*sizeof(PetscScalar));
2762:   }

2764:   /* copy values over */
2765:   PetscMemcpy(aij->saved_values,aij->a,nz*sizeof(PetscScalar));
2766:   return(0);
2767: }

2769: PetscErrorCode  MatRetrieveValues_SeqBAIJ(Mat mat)
2770: {
2771:   Mat_SeqBAIJ    *aij = (Mat_SeqBAIJ*)mat->data;
2773:   PetscInt       nz = aij->i[aij->mbs]*aij->bs2;

2776:   if (aij->nonew != 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatSetOption(A,MAT_NEW_NONZERO_LOCATIONS,PETSC_FALSE);first");
2777:   if (!aij->saved_values) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Must call MatStoreValues(A);first");

2779:   /* copy values over */
2780:   PetscMemcpy(aij->a,aij->saved_values,nz*sizeof(PetscScalar));
2781:   return(0);
2782: }

2784: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqAIJ(Mat, MatType,MatReuse,Mat*);
2785: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqSBAIJ(Mat, MatType,MatReuse,Mat*);

2787: PetscErrorCode  MatSeqBAIJSetPreallocation_SeqBAIJ(Mat B,PetscInt bs,PetscInt nz,PetscInt *nnz)
2788: {
2789:   Mat_SeqBAIJ    *b;
2791:   PetscInt       i,mbs,nbs,bs2;
2792:   PetscBool      flg = PETSC_FALSE,skipallocation = PETSC_FALSE,realalloc = PETSC_FALSE;

2795:   if (nz >= 0 || nnz) realalloc = PETSC_TRUE;
2796:   if (nz == MAT_SKIP_ALLOCATION) {
2797:     skipallocation = PETSC_TRUE;
2798:     nz             = 0;
2799:   }

2801:   MatSetBlockSize(B,PetscAbs(bs));
2802:   PetscLayoutSetUp(B->rmap);
2803:   PetscLayoutSetUp(B->cmap);
2804:   PetscLayoutGetBlockSize(B->rmap,&bs);

2806:   B->preallocated = PETSC_TRUE;

2808:   mbs = B->rmap->n/bs;
2809:   nbs = B->cmap->n/bs;
2810:   bs2 = bs*bs;

2812:   if (mbs*bs!=B->rmap->n || nbs*bs!=B->cmap->n) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Number rows %D, cols %D must be divisible by blocksize %D",B->rmap->N,B->cmap->n,bs);

2814:   if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
2815:   if (nz < 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nz cannot be less than 0: value %D",nz);
2816:   if (nnz) {
2817:     for (i=0; i<mbs; i++) {
2818:       if (nnz[i] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be less than 0: local row %D value %D",i,nnz[i]);
2819:       if (nnz[i] > nbs) SETERRQ3(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"nnz cannot be greater than block row length: local row %D value %D rowlength %D",i,nnz[i],nbs);
2820:     }
2821:   }

2823:   b    = (Mat_SeqBAIJ*)B->data;
2824:   PetscOptionsBegin(PetscObjectComm((PetscObject)B),NULL,"Optimize options for SEQBAIJ matrix 2 ","Mat");
2825:   PetscOptionsBool("-mat_no_unroll","Do not optimize for block size (slow)",NULL,flg,&flg,NULL);
2826:   PetscOptionsEnd();

2828:   if (!flg) {
2829:     switch (bs) {
2830:     case 1:
2831:       B->ops->mult    = MatMult_SeqBAIJ_1;
2832:       B->ops->multadd = MatMultAdd_SeqBAIJ_1;
2833:       break;
2834:     case 2:
2835:       B->ops->mult    = MatMult_SeqBAIJ_2;
2836:       B->ops->multadd = MatMultAdd_SeqBAIJ_2;
2837:       break;
2838:     case 3:
2839:       B->ops->mult    = MatMult_SeqBAIJ_3;
2840:       B->ops->multadd = MatMultAdd_SeqBAIJ_3;
2841:       break;
2842:     case 4:
2843:       B->ops->mult    = MatMult_SeqBAIJ_4;
2844:       B->ops->multadd = MatMultAdd_SeqBAIJ_4;
2845:       break;
2846:     case 5:
2847:       B->ops->mult    = MatMult_SeqBAIJ_5;
2848:       B->ops->multadd = MatMultAdd_SeqBAIJ_5;
2849:       break;
2850:     case 6:
2851:       B->ops->mult    = MatMult_SeqBAIJ_6;
2852:       B->ops->multadd = MatMultAdd_SeqBAIJ_6;
2853:       break;
2854:     case 7:
2855:       B->ops->mult    = MatMult_SeqBAIJ_7;
2856:       B->ops->multadd = MatMultAdd_SeqBAIJ_7;
2857:       break;
2858:     case 9:
2859: #if defined(PETSC_HAVE_IMMINTRIN_H) && defined(__AVX2__) && defined(__FMA__) && defined(PETSC_USE_REAL_DOUBLE) && !defined(PETSC_USE_COMPLEX) && !defined(PETSC_USE_64BIT_INDICES)
2860:       B->ops->mult    = MatMult_SeqBAIJ_9_AVX2;
2861:       B->ops->multadd = MatMultAdd_SeqBAIJ_9_AVX2;
2862: #else
2863:       B->ops->mult    = MatMult_SeqBAIJ_N;
2864:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
2865: #endif
2866:       break;
2867:     case 11:
2868:       B->ops->mult    = MatMult_SeqBAIJ_11;
2869:       B->ops->multadd = MatMultAdd_SeqBAIJ_11;
2870:       break;
2871:     case 15:
2872:       B->ops->mult    = MatMult_SeqBAIJ_15_ver1;
2873:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
2874:       break;
2875:     default:
2876:       B->ops->mult    = MatMult_SeqBAIJ_N;
2877:       B->ops->multadd = MatMultAdd_SeqBAIJ_N;
2878:       break;
2879:     }
2880:   }
2881:   B->ops->sor = MatSOR_SeqBAIJ;
2882:   b->mbs = mbs;
2883:   b->nbs = nbs;
2884:   if (!skipallocation) {
2885:     if (!b->imax) {
2886:       PetscMalloc2(mbs,&b->imax,mbs,&b->ilen);
2887:       PetscLogObjectMemory((PetscObject)B,2*mbs*sizeof(PetscInt));

2889:       b->free_imax_ilen = PETSC_TRUE;
2890:     }
2891:     /* b->ilen will count nonzeros in each block row so far. */
2892:     for (i=0; i<mbs; i++) b->ilen[i] = 0;
2893:     if (!nnz) {
2894:       if (nz == PETSC_DEFAULT || nz == PETSC_DECIDE) nz = 5;
2895:       else if (nz < 0) nz = 1;
2896:       for (i=0; i<mbs; i++) b->imax[i] = nz;
2897:       nz = nz*mbs;
2898:     } else {
2899:       nz = 0;
2900:       for (i=0; i<mbs; i++) {b->imax[i] = nnz[i]; nz += nnz[i];}
2901:     }

2903:     /* allocate the matrix space */
2904:     MatSeqXAIJFreeAIJ(B,&b->a,&b->j,&b->i);
2905:     if (B->structure_only) {
2906:       PetscMalloc1(nz,&b->j);
2907:       PetscMalloc1(B->rmap->N+1,&b->i);
2908:       PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*sizeof(PetscInt));
2909:     } else {
2910:       PetscMalloc3(bs2*nz,&b->a,nz,&b->j,B->rmap->N+1,&b->i);
2911:       PetscLogObjectMemory((PetscObject)B,(B->rmap->N+1)*sizeof(PetscInt)+nz*(bs2*sizeof(PetscScalar)+sizeof(PetscInt)));
2912:       PetscMemzero(b->a,nz*bs2*sizeof(MatScalar));
2913:     }
2914:     PetscMemzero(b->j,nz*sizeof(PetscInt));

2916:     if (B->structure_only) {
2917:       b->singlemalloc = PETSC_FALSE;
2918:       b->free_a       = PETSC_FALSE;
2919:     } else {
2920:       b->singlemalloc = PETSC_TRUE;
2921:       b->free_a       = PETSC_TRUE;
2922:     }
2923:     b->free_ij = PETSC_TRUE;

2925:     b->i[0] = 0;
2926:     for (i=1; i<mbs+1; i++) {
2927:       b->i[i] = b->i[i-1] + b->imax[i-1];
2928:     }

2930:   } else {
2931:     b->free_a  = PETSC_FALSE;
2932:     b->free_ij = PETSC_FALSE;
2933:   }

2935:   b->bs2              = bs2;
2936:   b->mbs              = mbs;
2937:   b->nz               = 0;
2938:   b->maxnz            = nz;
2939:   B->info.nz_unneeded = (PetscReal)b->maxnz*bs2;
2940:   B->was_assembled    = PETSC_FALSE;
2941:   B->assembled        = PETSC_FALSE;
2942:   if (realalloc) {MatSetOption(B,MAT_NEW_NONZERO_ALLOCATION_ERR,PETSC_TRUE);}
2943:   return(0);
2944: }

2946: PetscErrorCode MatSeqBAIJSetPreallocationCSR_SeqBAIJ(Mat B,PetscInt bs,const PetscInt ii[],const PetscInt jj[],const PetscScalar V[])
2947: {
2948:   PetscInt       i,m,nz,nz_max=0,*nnz;
2949:   PetscScalar    *values=0;
2950:   PetscBool      roworiented = ((Mat_SeqBAIJ*)B->data)->roworiented;

2954:   if (bs < 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Invalid block size specified, must be positive but it is %D",bs);
2955:   PetscLayoutSetBlockSize(B->rmap,bs);
2956:   PetscLayoutSetBlockSize(B->cmap,bs);
2957:   PetscLayoutSetUp(B->rmap);
2958:   PetscLayoutSetUp(B->cmap);
2959:   PetscLayoutGetBlockSize(B->rmap,&bs);
2960:   m    = B->rmap->n/bs;

2962:   if (ii[0] != 0) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "ii[0] must be 0 but it is %D",ii[0]);
2963:   PetscMalloc1(m+1, &nnz);
2964:   for (i=0; i<m; i++) {
2965:     nz = ii[i+1]- ii[i];
2966:     if (nz < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE, "Local row %D has a negative number of columns %D",i,nz);
2967:     nz_max = PetscMax(nz_max, nz);
2968:     nnz[i] = nz;
2969:   }
2970:   MatSeqBAIJSetPreallocation(B,bs,0,nnz);
2971:   PetscFree(nnz);

2973:   values = (PetscScalar*)V;
2974:   if (!values) {
2975:     PetscCalloc1(bs*bs*(nz_max+1),&values);
2976:   }
2977:   for (i=0; i<m; i++) {
2978:     PetscInt          ncols  = ii[i+1] - ii[i];
2979:     const PetscInt    *icols = jj + ii[i];
2980:     const PetscScalar *svals = values + (V ? (bs*bs*ii[i]) : 0);
2981:     if (!roworiented) {
2982:       MatSetValuesBlocked_SeqBAIJ(B,1,&i,ncols,icols,svals,INSERT_VALUES);
2983:     } else {
2984:       PetscInt j;
2985:       for (j=0; j<ncols; j++) {
2986:         const PetscScalar *svals = values + (V ? (bs*bs*(ii[i]+j)) : 0);
2987:         MatSetValuesBlocked_SeqBAIJ(B,1,&i,1,&icols[j],svals,INSERT_VALUES);
2988:       }
2989:     }
2990:   }
2991:   if (!V) { PetscFree(values); }
2992:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
2993:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
2994:   MatSetOption(B,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
2995:   return(0);
2996: }

2998: /*MC
2999:    MATSEQBAIJ - MATSEQBAIJ = "seqbaij" - A matrix type to be used for sequential block sparse matrices, based on
3000:    block sparse compressed row format.

3002:    Options Database Keys:
3003: . -mat_type seqbaij - sets the matrix type to "seqbaij" during a call to MatSetFromOptions()

3005:   Level: beginner

3007: .seealso: MatCreateSeqBAIJ()
3008: M*/

3010: PETSC_INTERN PetscErrorCode MatConvert_SeqBAIJ_SeqBSTRM(Mat, MatType,MatReuse,Mat*);

3012: PETSC_EXTERN PetscErrorCode MatCreate_SeqBAIJ(Mat B)
3013: {
3015:   PetscMPIInt    size;
3016:   Mat_SeqBAIJ    *b;

3019:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
3020:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Comm must be of size 1");

3022:   PetscNewLog(B,&b);
3023:   B->data = (void*)b;
3024:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));

3026:   b->row          = 0;
3027:   b->col          = 0;
3028:   b->icol         = 0;
3029:   b->reallocs     = 0;
3030:   b->saved_values = 0;

3032:   b->roworiented        = PETSC_TRUE;
3033:   b->nonew              = 0;
3034:   b->diag               = 0;
3035:   B->spptr              = 0;
3036:   B->info.nz_unneeded   = (PetscReal)b->maxnz*b->bs2;
3037:   b->keepnonzeropattern = PETSC_FALSE;

3039:   PetscObjectComposeFunction((PetscObject)B,"MatInvertBlockDiagonal_C",MatInvertBlockDiagonal_SeqBAIJ);
3040:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_SeqBAIJ);
3041:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_SeqBAIJ);
3042:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetColumnIndices_C",MatSeqBAIJSetColumnIndices_SeqBAIJ);
3043:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqaij_C",MatConvert_SeqBAIJ_SeqAIJ);
3044:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_seqsbaij_C",MatConvert_SeqBAIJ_SeqSBAIJ);
3045:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocation_C",MatSeqBAIJSetPreallocation_SeqBAIJ);
3046:   PetscObjectComposeFunction((PetscObject)B,"MatSeqBAIJSetPreallocationCSR_C",MatSeqBAIJSetPreallocationCSR_SeqBAIJ);
3047:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_SeqBAIJ);
3048: #if defined(PETSC_HAVE_HYPRE)
3049:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_hypre_C",MatConvert_AIJ_HYPRE);
3050: #endif
3051:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_seqbaij_is_C",MatConvert_XAIJ_IS);
3052:   PetscObjectComposeFunction((PetscObject)B,"MatPtAP_is_seqbaij_C",MatPtAP_IS_XAIJ);
3053:   PetscObjectChangeTypeName((PetscObject)B,MATSEQBAIJ);
3054:   return(0);
3055: }

3057: PetscErrorCode MatDuplicateNoCreate_SeqBAIJ(Mat C,Mat A,MatDuplicateOption cpvalues,PetscBool mallocmatspace)
3058: {
3059:   Mat_SeqBAIJ    *c = (Mat_SeqBAIJ*)C->data,*a = (Mat_SeqBAIJ*)A->data;
3061:   PetscInt       i,mbs = a->mbs,nz = a->nz,bs2 = a->bs2;

3064:   if (a->i[mbs] != nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Corrupt matrix");

3066:   if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
3067:     c->imax           = a->imax;
3068:     c->ilen           = a->ilen;
3069:     c->free_imax_ilen = PETSC_FALSE;
3070:   } else {
3071:     PetscMalloc2(mbs,&c->imax,mbs,&c->ilen);
3072:     PetscLogObjectMemory((PetscObject)C,2*mbs*sizeof(PetscInt));
3073:     for (i=0; i<mbs; i++) {
3074:       c->imax[i] = a->imax[i];
3075:       c->ilen[i] = a->ilen[i];
3076:     }
3077:     c->free_imax_ilen = PETSC_TRUE;
3078:   }

3080:   /* allocate the matrix space */
3081:   if (mallocmatspace) {
3082:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
3083:       PetscCalloc1(bs2*nz,&c->a);
3084:       PetscLogObjectMemory((PetscObject)C,a->i[mbs]*bs2*sizeof(PetscScalar));

3086:       c->i            = a->i;
3087:       c->j            = a->j;
3088:       c->singlemalloc = PETSC_FALSE;
3089:       c->free_a       = PETSC_TRUE;
3090:       c->free_ij      = PETSC_FALSE;
3091:       c->parent       = A;
3092:       C->preallocated = PETSC_TRUE;
3093:       C->assembled    = PETSC_TRUE;

3095:       PetscObjectReference((PetscObject)A);
3096:       MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3097:       MatSetOption(C,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);
3098:     } else {
3099:       PetscMalloc3(bs2*nz,&c->a,nz,&c->j,mbs+1,&c->i);
3100:       PetscLogObjectMemory((PetscObject)C,a->i[mbs]*(bs2*sizeof(PetscScalar)+sizeof(PetscInt))+(mbs+1)*sizeof(PetscInt));

3102:       c->singlemalloc = PETSC_TRUE;
3103:       c->free_a       = PETSC_TRUE;
3104:       c->free_ij      = PETSC_TRUE;

3106:       PetscMemcpy(c->i,a->i,(mbs+1)*sizeof(PetscInt));
3107:       if (mbs > 0) {
3108:         PetscMemcpy(c->j,a->j,nz*sizeof(PetscInt));
3109:         if (cpvalues == MAT_COPY_VALUES) {
3110:           PetscMemcpy(c->a,a->a,bs2*nz*sizeof(MatScalar));
3111:         } else {
3112:           PetscMemzero(c->a,bs2*nz*sizeof(MatScalar));
3113:         }
3114:       }
3115:       C->preallocated = PETSC_TRUE;
3116:       C->assembled    = PETSC_TRUE;
3117:     }
3118:   }

3120:   c->roworiented = a->roworiented;
3121:   c->nonew       = a->nonew;

3123:   PetscLayoutReference(A->rmap,&C->rmap);
3124:   PetscLayoutReference(A->cmap,&C->cmap);

3126:   c->bs2         = a->bs2;
3127:   c->mbs         = a->mbs;
3128:   c->nbs         = a->nbs;

3130:   if (a->diag) {
3131:     if (cpvalues == MAT_SHARE_NONZERO_PATTERN) {
3132:       c->diag      = a->diag;
3133:       c->free_diag = PETSC_FALSE;
3134:     } else {
3135:       PetscMalloc1(mbs+1,&c->diag);
3136:       PetscLogObjectMemory((PetscObject)C,(mbs+1)*sizeof(PetscInt));
3137:       for (i=0; i<mbs; i++) c->diag[i] = a->diag[i];
3138:       c->free_diag = PETSC_TRUE;
3139:     }
3140:   } else c->diag = 0;

3142:   c->nz         = a->nz;
3143:   c->maxnz      = a->nz;         /* Since we allocate exactly the right amount */
3144:   c->solve_work = NULL;
3145:   c->mult_work  = NULL;
3146:   c->sor_workt  = NULL;
3147:   c->sor_work   = NULL;

3149:   c->compressedrow.use   = a->compressedrow.use;
3150:   c->compressedrow.nrows = a->compressedrow.nrows;
3151:   if (a->compressedrow.use) {
3152:     i    = a->compressedrow.nrows;
3153:     PetscMalloc2(i+1,&c->compressedrow.i,i+1,&c->compressedrow.rindex);
3154:     PetscLogObjectMemory((PetscObject)C,(2*i+1)*sizeof(PetscInt));
3155:     PetscMemcpy(c->compressedrow.i,a->compressedrow.i,(i+1)*sizeof(PetscInt));
3156:     PetscMemcpy(c->compressedrow.rindex,a->compressedrow.rindex,i*sizeof(PetscInt));
3157:   } else {
3158:     c->compressedrow.use    = PETSC_FALSE;
3159:     c->compressedrow.i      = NULL;
3160:     c->compressedrow.rindex = NULL;
3161:   }
3162:   C->nonzerostate = A->nonzerostate;

3164:   PetscFunctionListDuplicate(((PetscObject)A)->qlist,&((PetscObject)C)->qlist);
3165:   return(0);
3166: }

3168: PetscErrorCode MatDuplicate_SeqBAIJ(Mat A,MatDuplicateOption cpvalues,Mat *B)
3169: {

3173:   MatCreate(PetscObjectComm((PetscObject)A),B);
3174:   MatSetSizes(*B,A->rmap->N,A->cmap->n,A->rmap->N,A->cmap->n);
3175:   MatSetType(*B,MATSEQBAIJ);
3176:   MatDuplicateNoCreate_SeqBAIJ(*B,A,cpvalues,PETSC_TRUE);
3177:   return(0);
3178: }

3180: PetscErrorCode MatLoad_SeqBAIJ(Mat newmat,PetscViewer viewer)
3181: {
3182:   Mat_SeqBAIJ    *a;
3184:   PetscInt       i,nz,header[4],*rowlengths=0,M,N,bs = newmat->rmap->bs;
3185:   PetscInt       *mask,mbs,*jj,j,rowcount,nzcount,k,*browlengths,maskcount;
3186:   PetscInt       kmax,jcount,block,idx,point,nzcountb,extra_rows,rows,cols;
3187:   PetscInt       *masked,nmask,tmp,bs2,ishift;
3188:   PetscMPIInt    size;
3189:   int            fd;
3190:   PetscScalar    *aa;
3191:   MPI_Comm       comm;
3192:   PetscBool      isbinary;

3195:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
3196:   if (!isbinary) SETERRQ2(PetscObjectComm((PetscObject)newmat),PETSC_ERR_SUP,"Viewer type %s not yet supported for reading %s matrices",((PetscObject)viewer)->type_name,((PetscObject)newmat)->type_name);

3198:   /* force binary viewer to load .info file if it has not yet done so */
3199:   PetscViewerSetUp(viewer);
3200:   PetscObjectGetComm((PetscObject)viewer,&comm);
3201:   PetscOptionsBegin(comm,NULL,"Options for loading SEQBAIJ matrix","Mat");
3202:   PetscOptionsInt("-matload_block_size","Set the blocksize used to store the matrix","MatLoad",bs,&bs,NULL);
3203:   PetscOptionsEnd();
3204:   if (bs < 0) bs = 1;
3205:   bs2  = bs*bs;

3207:   MPI_Comm_size(comm,&size);
3208:   if (size > 1) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"view must have one processor");
3209:   PetscViewerBinaryGetDescriptor(viewer,&fd);
3210:   PetscBinaryRead(fd,header,4,PETSC_INT);
3211:   if (header[0] != MAT_FILE_CLASSID) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"not Mat object");
3212:   M = header[1]; N = header[2]; nz = header[3];

3214:   if (header[3] < 0) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix stored in special format, cannot load as SeqBAIJ");
3215:   if (M != N) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Can only do square matrices");

3217:   /*
3218:      This code adds extra rows to make sure the number of rows is
3219:     divisible by the blocksize
3220:   */
3221:   mbs        = M/bs;
3222:   extra_rows = bs - M + bs*(mbs);
3223:   if (extra_rows == bs) extra_rows = 0;
3224:   else mbs++;
3225:   if (extra_rows) {
3226:     PetscInfo(viewer,"Padding loaded matrix to match blocksize\n");
3227:   }

3229:   /* Set global sizes if not already set */
3230:   if (newmat->rmap->n < 0 && newmat->rmap->N < 0 && newmat->cmap->n < 0 && newmat->cmap->N < 0) {
3231:     MatSetSizes(newmat,PETSC_DECIDE,PETSC_DECIDE,M+extra_rows,N+extra_rows);
3232:   } else { /* Check if the matrix global sizes are correct */
3233:     MatGetSize(newmat,&rows,&cols);
3234:     if (rows < 0 && cols < 0) { /* user might provide local size instead of global size */
3235:       MatGetLocalSize(newmat,&rows,&cols);
3236:     }
3237:     if (M != rows ||  N != cols) SETERRQ4(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Matrix in file of different length (%d, %d) than the input matrix (%d, %d)",M,N,rows,cols);
3238:   }

3240:   /* read in row lengths */
3241:   PetscMalloc1(M+extra_rows,&rowlengths);
3242:   PetscBinaryRead(fd,rowlengths,M,PETSC_INT);
3243:   for (i=0; i<extra_rows; i++) rowlengths[M+i] = 1;

3245:   /* read in column indices */
3246:   PetscMalloc1(nz+extra_rows,&jj);
3247:   PetscBinaryRead(fd,jj,nz,PETSC_INT);
3248:   for (i=0; i<extra_rows; i++) jj[nz+i] = M+i;

3250:   /* loop over row lengths determining block row lengths */
3251:   PetscCalloc1(mbs,&browlengths);
3252:   PetscMalloc2(mbs,&mask,mbs,&masked);
3253:   PetscMemzero(mask,mbs*sizeof(PetscInt));
3254:   rowcount = 0;
3255:   nzcount  = 0;
3256:   for (i=0; i<mbs; i++) {
3257:     nmask = 0;
3258:     for (j=0; j<bs; j++) {
3259:       kmax = rowlengths[rowcount];
3260:       for (k=0; k<kmax; k++) {
3261:         tmp = jj[nzcount++]/bs;
3262:         if (!mask[tmp]) {masked[nmask++] = tmp; mask[tmp] = 1;}
3263:       }
3264:       rowcount++;
3265:     }
3266:     browlengths[i] += nmask;
3267:     /* zero out the mask elements we set */
3268:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
3269:   }

3271:   /* Do preallocation  */
3272:   MatSeqBAIJSetPreallocation(newmat,bs,0,browlengths);
3273:   a    = (Mat_SeqBAIJ*)newmat->data;

3275:   /* set matrix "i" values */
3276:   a->i[0] = 0;
3277:   for (i=1; i<= mbs; i++) {
3278:     a->i[i]      = a->i[i-1] + browlengths[i-1];
3279:     a->ilen[i-1] = browlengths[i-1];
3280:   }
3281:   a->nz = 0;
3282:   for (i=0; i<mbs; i++) a->nz += browlengths[i];

3284:   /* read in nonzero values */
3285:   PetscMalloc1(nz+extra_rows,&aa);
3286:   PetscBinaryRead(fd,aa,nz,PETSC_SCALAR);
3287:   for (i=0; i<extra_rows; i++) aa[nz+i] = 1.0;

3289:   /* set "a" and "j" values into matrix */
3290:   nzcount = 0; jcount = 0;
3291:   for (i=0; i<mbs; i++) {
3292:     nzcountb = nzcount;
3293:     nmask    = 0;
3294:     for (j=0; j<bs; j++) {
3295:       kmax = rowlengths[i*bs+j];
3296:       for (k=0; k<kmax; k++) {
3297:         tmp = jj[nzcount++]/bs;
3298:         if (!mask[tmp]) { masked[nmask++] = tmp; mask[tmp] = 1;}
3299:       }
3300:     }
3301:     /* sort the masked values */
3302:     PetscSortInt(nmask,masked);

3304:     /* set "j" values into matrix */
3305:     maskcount = 1;
3306:     for (j=0; j<nmask; j++) {
3307:       a->j[jcount++]  = masked[j];
3308:       mask[masked[j]] = maskcount++;
3309:     }
3310:     /* set "a" values into matrix */
3311:     ishift = bs2*a->i[i];
3312:     for (j=0; j<bs; j++) {
3313:       kmax = rowlengths[i*bs+j];
3314:       for (k=0; k<kmax; k++) {
3315:         tmp       = jj[nzcountb]/bs;
3316:         block     = mask[tmp] - 1;
3317:         point     = jj[nzcountb] - bs*tmp;
3318:         idx       = ishift + bs2*block + j + bs*point;
3319:         a->a[idx] = (MatScalar)aa[nzcountb++];
3320:       }
3321:     }
3322:     /* zero out the mask elements we set */
3323:     for (j=0; j<nmask; j++) mask[masked[j]] = 0;
3324:   }
3325:   if (jcount != a->nz) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_FILE_UNEXPECTED,"Bad binary matrix");

3327:   PetscFree(rowlengths);
3328:   PetscFree(browlengths);
3329:   PetscFree(aa);
3330:   PetscFree(jj);
3331:   PetscFree2(mask,masked);

3333:   MatAssemblyBegin(newmat,MAT_FINAL_ASSEMBLY);
3334:   MatAssemblyEnd(newmat,MAT_FINAL_ASSEMBLY);
3335:   return(0);
3336: }

3338: /*@C
3339:    MatCreateSeqBAIJ - Creates a sparse matrix in block AIJ (block
3340:    compressed row) format.  For good matrix assembly performance the
3341:    user should preallocate the matrix storage by setting the parameter nz
3342:    (or the array nnz).  By setting these parameters accurately, performance
3343:    during matrix assembly can be increased by more than a factor of 50.

3345:    Collective on MPI_Comm

3347:    Input Parameters:
3348: +  comm - MPI communicator, set to PETSC_COMM_SELF
3349: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
3350:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
3351: .  m - number of rows
3352: .  n - number of columns
3353: .  nz - number of nonzero blocks  per block row (same for all rows)
3354: -  nnz - array containing the number of nonzero blocks in the various block rows
3355:          (possibly different for each block row) or NULL

3357:    Output Parameter:
3358: .  A - the matrix

3360:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
3361:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
3362:    [MatXXXXSetPreallocation() is, for example, MatSeqAIJSetPreallocation]

3364:    Options Database Keys:
3365: .   -mat_no_unroll - uses code that does not unroll the loops in the
3366:                      block calculations (much slower)
3367: .    -mat_block_size - size of the blocks to use

3369:    Level: intermediate

3371:    Notes:
3372:    The number of rows and columns must be divisible by blocksize.

3374:    If the nnz parameter is given then the nz parameter is ignored

3376:    A nonzero block is any block that as 1 or more nonzeros in it

3378:    The block AIJ format is fully compatible with standard Fortran 77
3379:    storage.  That is, the stored row and column indices can begin at
3380:    either one (as in Fortran) or zero.  See the users' manual for details.

3382:    Specify the preallocated storage with either nz or nnz (not both).
3383:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
3384:    allocation.  See Users-Manual: ch_mat for details.
3385:    matrices.

3387: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ()
3388: @*/
3389: PetscErrorCode  MatCreateSeqBAIJ(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt nz,const PetscInt nnz[],Mat *A)
3390: {

3394:   MatCreate(comm,A);
3395:   MatSetSizes(*A,m,n,m,n);
3396:   MatSetType(*A,MATSEQBAIJ);
3397:   MatSeqBAIJSetPreallocation(*A,bs,nz,(PetscInt*)nnz);
3398:   return(0);
3399: }

3401: /*@C
3402:    MatSeqBAIJSetPreallocation - Sets the block size and expected nonzeros
3403:    per row in the matrix. For good matrix assembly performance the
3404:    user should preallocate the matrix storage by setting the parameter nz
3405:    (or the array nnz).  By setting these parameters accurately, performance
3406:    during matrix assembly can be increased by more than a factor of 50.

3408:    Collective on MPI_Comm

3410:    Input Parameters:
3411: +  B - the matrix
3412: .  bs - size of block, the blocks are ALWAYS square. One can use MatSetBlockSizes() to set a different row and column blocksize but the row
3413:           blocksize always defines the size of the blocks. The column blocksize sets the blocksize of the vectors obtained with MatCreateVecs()
3414: .  nz - number of block nonzeros per block row (same for all rows)
3415: -  nnz - array containing the number of block nonzeros in the various block rows
3416:          (possibly different for each block row) or NULL

3418:    Options Database Keys:
3419: .   -mat_no_unroll - uses code that does not unroll the loops in the
3420:                      block calculations (much slower)
3421: .   -mat_block_size - size of the blocks to use

3423:    Level: intermediate

3425:    Notes:
3426:    If the nnz parameter is given then the nz parameter is ignored

3428:    You can call MatGetInfo() to get information on how effective the preallocation was;
3429:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
3430:    You can also run with the option -info and look for messages with the string
3431:    malloc in them to see if additional memory allocation was needed.

3433:    The block AIJ format is fully compatible with standard Fortran 77
3434:    storage.  That is, the stored row and column indices can begin at
3435:    either one (as in Fortran) or zero.  See the users' manual for details.

3437:    Specify the preallocated storage with either nz or nnz (not both).
3438:    Set nz=PETSC_DEFAULT and nnz=NULL for PETSc to control dynamic memory
3439:    allocation.  See Users-Manual: ch_mat for details.

3441: .seealso: MatCreate(), MatCreateSeqAIJ(), MatSetValues(), MatCreateBAIJ(), MatGetInfo()
3442: @*/
3443: PetscErrorCode  MatSeqBAIJSetPreallocation(Mat B,PetscInt bs,PetscInt nz,const PetscInt nnz[])
3444: {

3451:   PetscTryMethod(B,"MatSeqBAIJSetPreallocation_C",(Mat,PetscInt,PetscInt,const PetscInt[]),(B,bs,nz,nnz));
3452:   return(0);
3453: }

3455: /*@C
3456:    MatSeqBAIJSetPreallocationCSR - Allocates memory for a sparse sequential matrix in AIJ format
3457:    (the default sequential PETSc format).

3459:    Collective on MPI_Comm

3461:    Input Parameters:
3462: +  B - the matrix
3463: .  i - the indices into j for the start of each local row (starts with zero)
3464: .  j - the column indices for each local row (starts with zero) these must be sorted for each row
3465: -  v - optional values in the matrix

3467:    Level: developer

3469:    Notes:
3470:    The order of the entries in values is specified by the MatOption MAT_ROW_ORIENTED.  For example, C programs
3471:    may want to use the default MAT_ROW_ORIENTED=PETSC_TRUE and use an array v[nnz][bs][bs] where the second index is
3472:    over rows within a block and the last index is over columns within a block row.  Fortran programs will likely set
3473:    MAT_ROW_ORIENTED=PETSC_FALSE and use a Fortran array v(bs,bs,nnz) in which the first index is over rows within a
3474:    block column and the second index is over columns within a block.

3476: .keywords: matrix, aij, compressed row, sparse

3478: .seealso: MatCreate(), MatCreateSeqBAIJ(), MatSetValues(), MatSeqBAIJSetPreallocation(), MATSEQBAIJ
3479: @*/
3480: PetscErrorCode  MatSeqBAIJSetPreallocationCSR(Mat B,PetscInt bs,const PetscInt i[],const PetscInt j[], const PetscScalar v[])
3481: {

3488:   PetscTryMethod(B,"MatSeqBAIJSetPreallocationCSR_C",(Mat,PetscInt,const PetscInt[],const PetscInt[],const PetscScalar[]),(B,bs,i,j,v));
3489:   return(0);
3490: }


3493: /*@
3494:      MatCreateSeqBAIJWithArrays - Creates an sequential BAIJ matrix using matrix elements provided by the user.

3496:      Collective on MPI_Comm

3498:    Input Parameters:
3499: +  comm - must be an MPI communicator of size 1
3500: .  bs - size of block
3501: .  m - number of rows
3502: .  n - number of columns
3503: .  i - row indices; that is i[0] = 0, i[row] = i[row-1] + number of elements in that row block row of the matrix
3504: .  j - column indices
3505: -  a - matrix values

3507:    Output Parameter:
3508: .  mat - the matrix

3510:    Level: advanced

3512:    Notes:
3513:        The i, j, and a arrays are not copied by this routine, the user must free these arrays
3514:     once the matrix is destroyed

3516:        You cannot set new nonzero locations into this matrix, that will generate an error.

3518:        The i and j indices are 0 based

3520:        When block size is greater than 1 the matrix values must be stored using the BAIJ storage format (see the BAIJ code to determine this).

3522:       The order of the entries in values is the same as the block compressed sparse row storage format; that is, it is
3523:       the same as a three dimensional array in Fortran values(bs,bs,nnz) that contains the first column of the first
3524:       block, followed by the second column of the first block etc etc.  That is, the blocks are contiguous in memory
3525:       with column-major ordering within blocks.

3527: .seealso: MatCreate(), MatCreateBAIJ(), MatCreateSeqBAIJ()

3529: @*/
3530: PetscErrorCode  MatCreateSeqBAIJWithArrays(MPI_Comm comm,PetscInt bs,PetscInt m,PetscInt n,PetscInt i[],PetscInt j[],PetscScalar a[],Mat *mat)
3531: {
3533:   PetscInt       ii;
3534:   Mat_SeqBAIJ    *baij;

3537:   if (bs != 1) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"block size %D > 1 is not supported yet",bs);
3538:   if (m > 0 && i[0]) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"i (row indices) must start with 0");

3540:   MatCreate(comm,mat);
3541:   MatSetSizes(*mat,m,n,m,n);
3542:   MatSetType(*mat,MATSEQBAIJ);
3543:   MatSeqBAIJSetPreallocation(*mat,bs,MAT_SKIP_ALLOCATION,0);
3544:   baij = (Mat_SeqBAIJ*)(*mat)->data;
3545:   PetscMalloc2(m,&baij->imax,m,&baij->ilen);
3546:   PetscLogObjectMemory((PetscObject)*mat,2*m*sizeof(PetscInt));

3548:   baij->i = i;
3549:   baij->j = j;
3550:   baij->a = a;

3552:   baij->singlemalloc = PETSC_FALSE;
3553:   baij->nonew        = -1;             /*this indicates that inserting a new value in the matrix that generates a new nonzero is an error*/
3554:   baij->free_a       = PETSC_FALSE;
3555:   baij->free_ij      = PETSC_FALSE;

3557:   for (ii=0; ii<m; ii++) {
3558:     baij->ilen[ii] = baij->imax[ii] = i[ii+1] - i[ii];
3559: #if defined(PETSC_USE_DEBUG)
3560:     if (i[ii+1] - i[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row length in i (row indices) row = %d length = %d",ii,i[ii+1] - i[ii]);
3561: #endif
3562:   }
3563: #if defined(PETSC_USE_DEBUG)
3564:   for (ii=0; ii<baij->i[m]; ii++) {
3565:     if (j[ii] < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column index at location = %d index = %d",ii,j[ii]);
3566:     if (j[ii] > n - 1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column index to large at location = %d index = %d",ii,j[ii]);
3567:   }
3568: #endif

3570:   MatAssemblyBegin(*mat,MAT_FINAL_ASSEMBLY);
3571:   MatAssemblyEnd(*mat,MAT_FINAL_ASSEMBLY);
3572:   return(0);
3573: }

3575: PetscErrorCode MatCreateMPIMatConcatenateSeqMat_SeqBAIJ(MPI_Comm comm,Mat inmat,PetscInt n,MatReuse scall,Mat *outmat)
3576: {
3578:   PetscMPIInt    size;

3581:   MPI_Comm_size(comm,&size);
3582:   if (size == 1 && scall == MAT_REUSE_MATRIX) {
3583:     MatCopy(inmat,*outmat,SAME_NONZERO_PATTERN);
3584:   } else {
3585:     MatCreateMPIMatConcatenateSeqMat_MPIBAIJ(comm,inmat,n,scall,outmat);
3586:   }
3587:   return(0);
3588: }