xref: /petsc/src/mat/impls/aij/mpi/fdmpiaij.c (revision 6fe1374c95207fb3dac8da6bbf6c8bb60f5f290d)
1 
2 #include <../src/mat/impls/aij/mpi/mpiaij.h>
3 #include <../src/mat/impls/baij/mpi/mpibaij.h>
4 #include <petsc/private/isimpl.h>
5 
6 #undef __FUNCT__
7 #define __FUNCT__ "MatFDColoringApply_BAIJ"
8 PetscErrorCode  MatFDColoringApply_BAIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx)
9 {
10   PetscErrorCode    (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f;
11   PetscErrorCode    ierr;
12   PetscInt          k,cstart,cend,l,row,col,nz,spidx,i,j;
13   PetscScalar       dx=0.0,*w3_array,*dy_i,*dy=coloring->dy;
14   PetscScalar       *vscale_array;
15   const PetscScalar *xx;
16   PetscReal         epsilon=coloring->error_rel,umin=coloring->umin,unorm;
17   Vec               w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale;
18   void              *fctx=coloring->fctx;
19   PetscInt          ctype=coloring->ctype,nxloc,nrows_k;
20   PetscScalar       *valaddr;
21   MatEntry          *Jentry=coloring->matentry;
22   MatEntry2         *Jentry2=coloring->matentry2;
23   const PetscInt    ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows;
24   PetscInt          bs=J->rmap->bs;
25 
26   PetscFunctionBegin;
27   /* (1) Set w1 = F(x1) */
28   if (!coloring->fset) {
29     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
30     ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr);
31     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
32   } else {
33     coloring->fset = PETSC_FALSE;
34   }
35 
36   /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */
37   ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr);
38   if (coloring->htype[0] == 'w') {
39     /* vscale = dx is a constant scalar */
40     ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr);
41     dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon);
42   } else {
43     ierr = VecGetArrayRead(x1,&xx);CHKERRQ(ierr);
44     ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr);
45     for (col=0; col<nxloc; col++) {
46       dx = xx[col];
47       if (PetscAbsScalar(dx) < umin) {
48         if (PetscRealPart(dx) >= 0.0)      dx = umin;
49         else if (PetscRealPart(dx) < 0.0 ) dx = -umin;
50       }
51       dx               *= epsilon;
52       vscale_array[col] = 1.0/dx;
53     }
54     ierr = VecRestoreArrayRead(x1,&xx);CHKERRQ(ierr);
55     ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr);
56   }
57   if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') {
58     ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
59     ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
60   }
61 
62   /* (3) Loop over each color */
63   if (!coloring->w3) {
64     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
65     ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr);
66   }
67   w3 = coloring->w3;
68 
69   ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */
70   if (vscale) {
71     ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr);
72   }
73   nz   = 0;
74   for (k=0; k<ncolors; k++) {
75     coloring->currentcolor = k;
76 
77     /*
78       (3-1) Loop over each column associated with color
79       adding the perturbation to the vector w3 = x1 + dx.
80     */
81     ierr = VecCopy(x1,w3);CHKERRQ(ierr);
82     dy_i = dy;
83     for (i=0; i<bs; i++) {     /* Loop over a block of columns */
84       ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
85       if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */
86       if (coloring->htype[0] == 'w') {
87         for (l=0; l<ncolumns[k]; l++) {
88           col            = i + bs*coloring->columns[k][l];  /* local column (in global index!) of the matrix we are probing for */
89           w3_array[col] += 1.0/dx;
90           if (i) w3_array[col-1] -= 1.0/dx; /* resume original w3[col-1] */
91         }
92       } else { /* htype == 'ds' */
93         vscale_array -= cstart; /* shift pointer so global index can be used */
94         for (l=0; l<ncolumns[k]; l++) {
95           col = i + bs*coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */
96           w3_array[col] += 1.0/vscale_array[col];
97           if (i) w3_array[col-1] -=  1.0/vscale_array[col-1]; /* resume original w3[col-1] */
98         }
99         vscale_array += cstart;
100       }
101       if (ctype == IS_COLORING_GLOBAL) w3_array += cstart;
102       ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
103 
104       /*
105        (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
106                            w2 = F(x1 + dx) - F(x1)
107        */
108       ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
109       ierr = VecPlaceArray(w2,dy_i);CHKERRQ(ierr); /* place w2 to the array dy_i */
110       ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
111       ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
112       ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
113       ierr = VecResetArray(w2);CHKERRQ(ierr);
114       dy_i += nxloc; /* points to dy+i*nxloc */
115     }
116 
117     /*
118      (3-3) Loop over rows of vector, putting results into Jacobian matrix
119     */
120     nrows_k = nrows[k];
121     if (coloring->htype[0] == 'w') {
122       for (l=0; l<nrows_k; l++) {
123         row     = bs*Jentry2[nz].row;   /* local row index */
124         valaddr = Jentry2[nz++].valaddr;
125         spidx   = 0;
126         dy_i    = dy;
127         for (i=0; i<bs; i++) {   /* column of the block */
128           for (j=0; j<bs; j++) { /* row of the block */
129             valaddr[spidx++] = dy_i[row+j]*dx;
130           }
131           dy_i += nxloc; /* points to dy+i*nxloc */
132         }
133       }
134     } else { /* htype == 'ds' */
135       for (l=0; l<nrows_k; l++) {
136         row     = bs*Jentry[nz].row;   /* local row index */
137         col     = bs*Jentry[nz].col;   /* local column index */
138         valaddr = Jentry[nz++].valaddr;
139         spidx   = 0;
140         dy_i    = dy;
141         for (i=0; i<bs; i++) {   /* column of the block */
142           for (j=0; j<bs; j++) { /* row of the block */
143             valaddr[spidx++] = dy_i[row+j]*vscale_array[col+i];
144           }
145           dy_i += nxloc; /* points to dy+i*nxloc */
146         }
147       }
148     }
149   }
150   ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
151   ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
152   if (vscale) {
153     ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr);
154   }
155 
156   coloring->currentcolor = -1;
157   PetscFunctionReturn(0);
158 }
159 
160 #undef __FUNCT__
161 #define __FUNCT__ "MatFDColoringApply_AIJ"
162 PetscErrorCode  MatFDColoringApply_AIJ(Mat J,MatFDColoring coloring,Vec x1,void *sctx)
163 {
164   PetscErrorCode    (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f;
165   PetscErrorCode    ierr;
166   PetscInt          k,cstart,cend,l,row,col,nz;
167   PetscScalar       dx=0.0,*y,*w3_array;
168   const PetscScalar *xx;
169   PetscScalar       *vscale_array;
170   PetscReal         epsilon=coloring->error_rel,umin=coloring->umin,unorm;
171   Vec               w1=coloring->w1,w2=coloring->w2,w3,vscale=coloring->vscale;
172   void              *fctx=coloring->fctx;
173   PetscInt          ctype=coloring->ctype,nxloc,nrows_k;
174   MatEntry          *Jentry=coloring->matentry;
175   MatEntry2         *Jentry2=coloring->matentry2;
176   const PetscInt    ncolors=coloring->ncolors,*ncolumns=coloring->ncolumns,*nrows=coloring->nrows;
177 
178   PetscFunctionBegin;
179   /* (1) Set w1 = F(x1) */
180   if (!coloring->fset) {
181     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
182     ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr);
183     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
184   } else {
185     coloring->fset = PETSC_FALSE;
186   }
187 
188   /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */
189   if (coloring->htype[0] == 'w') {
190     /* vscale = 1./dx is a constant scalar */
191     ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr);
192     dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon);
193   } else {
194     ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr);
195     ierr = VecGetArrayRead(x1,&xx);CHKERRQ(ierr);
196     ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr);
197     for (col=0; col<nxloc; col++) {
198       dx = xx[col];
199       if (PetscAbsScalar(dx) < umin) {
200         if (PetscRealPart(dx) >= 0.0)      dx = umin;
201         else if (PetscRealPart(dx) < 0.0 ) dx = -umin;
202       }
203       dx               *= epsilon;
204       vscale_array[col] = 1.0/dx;
205     }
206     ierr = VecRestoreArrayRead(x1,&xx);CHKERRQ(ierr);
207     ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr);
208   }
209   if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') {
210     ierr = VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
211     ierr = VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
212   }
213 
214   /* (3) Loop over each color */
215   if (!coloring->w3) {
216     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
217     ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr);
218   }
219   w3 = coloring->w3;
220 
221   ierr = VecGetOwnershipRange(x1,&cstart,&cend);CHKERRQ(ierr); /* used by ghosted vscale */
222   if (vscale) {
223     ierr = VecGetArray(vscale,&vscale_array);CHKERRQ(ierr);
224   }
225   nz   = 0;
226 
227   if (coloring->bcols > 1) { /* use blocked insertion of Jentry */
228     PetscInt    i,m=J->rmap->n,nbcols,bcols=coloring->bcols;
229     PetscScalar *dy=coloring->dy,*dy_k;
230 
231     nbcols = 0;
232     for (k=0; k<ncolors; k+=bcols) {
233       coloring->currentcolor = k;
234 
235       /*
236        (3-1) Loop over each column associated with color
237        adding the perturbation to the vector w3 = x1 + dx.
238        */
239 
240       dy_k = dy;
241       if (k + bcols > ncolors) bcols = ncolors - k;
242       for (i=0; i<bcols; i++) {
243 
244         ierr = VecCopy(x1,w3);CHKERRQ(ierr);
245         ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
246         if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */
247         if (coloring->htype[0] == 'w') {
248           for (l=0; l<ncolumns[k+i]; l++) {
249             col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */
250             w3_array[col] += 1.0/dx;
251           }
252         } else { /* htype == 'ds' */
253           vscale_array -= cstart; /* shift pointer so global index can be used */
254           for (l=0; l<ncolumns[k+i]; l++) {
255             col = coloring->columns[k+i][l]; /* local column (in global index!) of the matrix we are probing for */
256             w3_array[col] += 1.0/vscale_array[col];
257           }
258           vscale_array += cstart;
259         }
260         if (ctype == IS_COLORING_GLOBAL) w3_array += cstart;
261         ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
262 
263         /*
264          (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
265                            w2 = F(x1 + dx) - F(x1)
266          */
267         ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
268         ierr = VecPlaceArray(w2,dy_k);CHKERRQ(ierr); /* place w2 to the array dy_i */
269         ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
270         ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
271         ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
272         ierr = VecResetArray(w2);CHKERRQ(ierr);
273         dy_k += m; /* points to dy+i*nxloc */
274       }
275 
276       /*
277        (3-3) Loop over block rows of vector, putting results into Jacobian matrix
278        */
279       nrows_k = nrows[nbcols++];
280       ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
281 
282       if (coloring->htype[0] == 'w') {
283         for (l=0; l<nrows_k; l++) {
284           row                      = Jentry2[nz].row;   /* local row index */
285           *(Jentry2[nz++].valaddr) = dy[row]*dx;
286         }
287       } else { /* htype == 'ds' */
288         for (l=0; l<nrows_k; l++) {
289           row                   = Jentry[nz].row;   /* local row index */
290           *(Jentry[nz].valaddr) = dy[row]*vscale_array[Jentry[nz].col];
291           nz++;
292         }
293       }
294       ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
295     }
296   } else { /* bcols == 1 */
297     for (k=0; k<ncolors; k++) {
298       coloring->currentcolor = k;
299 
300       /*
301        (3-1) Loop over each column associated with color
302        adding the perturbation to the vector w3 = x1 + dx.
303        */
304       ierr = VecCopy(x1,w3);CHKERRQ(ierr);
305       ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
306       if (ctype == IS_COLORING_GLOBAL) w3_array -= cstart; /* shift pointer so global index can be used */
307       if (coloring->htype[0] == 'w') {
308         for (l=0; l<ncolumns[k]; l++) {
309           col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */
310           w3_array[col] += 1.0/dx;
311         }
312       } else { /* htype == 'ds' */
313         vscale_array -= cstart; /* shift pointer so global index can be used */
314         for (l=0; l<ncolumns[k]; l++) {
315           col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */
316           w3_array[col] += 1.0/vscale_array[col];
317         }
318         vscale_array += cstart;
319       }
320       if (ctype == IS_COLORING_GLOBAL) w3_array += cstart;
321       ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
322 
323       /*
324        (3-2) Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
325                            w2 = F(x1 + dx) - F(x1)
326        */
327       ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
328       ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
329       ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
330       ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
331 
332       /*
333        (3-3) Loop over rows of vector, putting results into Jacobian matrix
334        */
335       nrows_k = nrows[k];
336       ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
337       if (coloring->htype[0] == 'w') {
338         for (l=0; l<nrows_k; l++) {
339           row                      = Jentry2[nz].row;   /* local row index */
340           *(Jentry2[nz++].valaddr) = y[row]*dx;
341         }
342       } else { /* htype == 'ds' */
343         for (l=0; l<nrows_k; l++) {
344           row                   = Jentry[nz].row;   /* local row index */
345           *(Jentry[nz].valaddr) = y[row]*vscale_array[Jentry[nz].col];
346           nz++;
347         }
348       }
349       ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
350     }
351   }
352 
353   ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
354   ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
355   if (vscale) {
356     ierr = VecRestoreArray(vscale,&vscale_array);CHKERRQ(ierr);
357   }
358   coloring->currentcolor = -1;
359   PetscFunctionReturn(0);
360 }
361 
362 #undef __FUNCT__
363 #define __FUNCT__ "MatFDColoringSetUp_MPIXAIJ"
364 PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
365 {
366   PetscErrorCode         ierr;
367   PetscMPIInt            size,*ncolsonproc,*disp,nn,rank;
368   PetscInt               i,n,nrows,nrows_i,j,k,m,ncols,col,*rowhit,cstart,cend,colb;
369   const PetscInt         *is,*A_ci,*A_cj,*B_ci,*B_cj,*row=NULL,*ltog=NULL;
370   PetscInt               nis=iscoloring->n,nctot,*cols,*cols_new;
371   IS                     *isa;
372   ISLocalToGlobalMapping map=mat->cmap->mapping;
373   PetscInt               ctype=c->ctype,*spidxA,*spidxB,nz,bs,bs2,spidx;
374   Mat                    A,B;
375   PetscScalar            *A_val,*B_val,**valaddrhit;
376   MatEntry               *Jentry;
377   MatEntry2              *Jentry2;
378   PetscBool              isBAIJ;
379   PetscInt               bcols=c->bcols;
380   MPI_Comm               comm;
381   PetscMPIInt            tag,nrecvs,proc;
382   MPI_Request            *rwaits = NULL,*swaits = NULL;
383   MPI_Status             status;
384 #if defined(PETSC_USE_CTABLE)
385   PetscTable             colmap=NULL;
386 #else
387   PetscInt               *colmap=NULL;     /* local col number of off-diag col */
388 #endif
389 
390   PetscFunctionBegin;
391   ierr = PetscObjectGetComm((PetscObject)mat,&comm);CHKERRQ(ierr);
392   ierr = MPI_Comm_rank(comm,&rank);CHKERRQ(ierr);
393 
394   if (ctype == IS_COLORING_GHOSTED) {
395     if (!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping");
396     ierr = ISLocalToGlobalMappingGetIndices(map,&ltog);CHKERRQ(ierr);
397   }
398 
399   ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr);
400   ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr);
401   if (isBAIJ) {
402     Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data;
403     Mat_SeqBAIJ *spA,*spB;
404     A = baij->A;  spA = (Mat_SeqBAIJ*)A->data; A_val = spA->a;
405     B = baij->B;  spB = (Mat_SeqBAIJ*)B->data; B_val = spB->a;
406     nz = spA->nz + spB->nz; /* total nonzero entries of mat */
407     if (!baij->colmap) {
408       ierr = MatCreateColmap_MPIBAIJ_Private(mat);CHKERRQ(ierr);
409     }
410     colmap = baij->colmap;
411     ierr = MatGetColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr);
412     ierr = MatGetColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr);
413 
414     if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') {  /* create vscale for storing dx */
415       PetscInt    *garray;
416       ierr = PetscMalloc1(B->cmap->n,&garray);CHKERRQ(ierr);
417       for (i=0; i<baij->B->cmap->n/bs; i++) {
418         for (j=0; j<bs; j++) {
419           garray[i*bs+j] = bs*baij->garray[i]+j;
420         }
421       }
422       ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,garray,&c->vscale);CHKERRQ(ierr);
423       ierr = PetscFree(garray);CHKERRQ(ierr);
424     }
425   } else {
426     Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data;
427     Mat_SeqAIJ *spA,*spB;
428     A = aij->A;  spA = (Mat_SeqAIJ*)A->data; A_val = spA->a;
429     B = aij->B;  spB = (Mat_SeqAIJ*)B->data; B_val = spB->a;
430     nz = spA->nz + spB->nz; /* total nonzero entries of mat */
431     if (!aij->colmap) {
432       /* Allow access to data structures of local part of matrix
433        - creates aij->colmap which maps global column number to local number in part B */
434       ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr);
435     }
436     colmap = aij->colmap;
437     ierr = MatGetColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr);
438     ierr = MatGetColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr);
439 
440     bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */
441 
442     if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */
443       ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr);
444     }
445   }
446 
447   m         = mat->rmap->n/bs;
448   cstart    = mat->cmap->rstart/bs;
449   cend      = mat->cmap->rend/bs;
450 
451   ierr       = PetscMalloc1(nis,&c->ncolumns);CHKERRQ(ierr);
452   ierr       = PetscMalloc1(nis,&c->columns);CHKERRQ(ierr);
453   ierr       = PetscMalloc1(nis,&c->nrows);CHKERRQ(ierr);
454   ierr       = PetscLogObjectMemory((PetscObject)c,3*nis*sizeof(PetscInt));CHKERRQ(ierr);
455 
456   if (c->htype[0] == 'd') {
457     ierr       = PetscMalloc1(nz,&Jentry);CHKERRQ(ierr);
458     ierr       = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry));CHKERRQ(ierr);
459     c->matentry = Jentry;
460   } else if (c->htype[0] == 'w') {
461     ierr       = PetscMalloc1(nz,&Jentry2);CHKERRQ(ierr);
462     ierr       = PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry2));CHKERRQ(ierr);
463     c->matentry2 = Jentry2;
464   } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"htype is not supported");
465 
466   ierr = PetscMalloc2(m+1,&rowhit,m+1,&valaddrhit);CHKERRQ(ierr);
467   nz = 0;
468   ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr);
469   for (i=0; i<nis; i++) { /* for each local color */
470     ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr);
471     ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr);
472 
473     c->ncolumns[i] = n; /* local number of columns of this color on this process */
474     if (n) {
475       ierr = PetscMalloc1(n,&c->columns[i]);CHKERRQ(ierr);
476       ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr);
477       ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr);
478     } else {
479       c->columns[i] = 0;
480     }
481 
482     if (ctype == IS_COLORING_GLOBAL) {
483       /* Determine nctot, the total (parallel) number of columns of this color */
484       ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
485       ierr = PetscMalloc2(size,&ncolsonproc,size,&disp);CHKERRQ(ierr);
486 
487       /* ncolsonproc[j]: local ncolumns on proc[j] of this color */
488       ierr  = PetscMPIIntCast(n,&nn);CHKERRQ(ierr);
489       ierr  = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
490       nctot = 0;
491       for (j=0; j<size; j++) nctot += ncolsonproc[j];
492       if (!nctot) {
493         ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr);
494       }
495 
496       disp[0] = 0;
497       for (j=1; j<size; j++) {
498         disp[j] = disp[j-1] + ncolsonproc[j-1];
499       }
500 
501       /* Get cols, the complete list of columns for this color on each process */
502       ierr = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr);
503 
504       /****************** non-scalable !!! *********************/
505       /* ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr); */
506       cols_new = cols;
507 
508       nrecvs = size-1;
509       ierr = PetscCommGetNewTag(comm,&tag);CHKERRQ(ierr);
510       ierr = PetscMalloc2(nrecvs,&rwaits,nrecvs,&swaits);CHKERRQ(ierr);
511 
512       j=0;
513       for (proc=0; proc<size; proc++) {
514         if (proc == rank) continue;
515         /* printf("[%d] Irecv %d from [%d] \n",rank,ncolsonproc[proc],proc); */
516         ierr = MPI_Irecv(cols_new+disp[proc],ncolsonproc[proc],MPIU_INT,proc,tag,comm,rwaits+j);CHKERRQ(ierr);
517         j++;
518       }
519 
520       j=0;
521       for (proc=0; proc<size; proc++) {
522         if (proc == rank) continue;
523         /* printf("[%d] Isend %d is to [%d] \n",rank,n,proc); */
524         ierr = MPI_Isend((void*)is,n,MPIU_INT,proc,tag,comm,swaits+j);CHKERRQ(ierr);
525         j++;
526       }
527 
528       for (j=0; j<ncolsonproc[rank]; j++) {
529         cols_new[disp[rank] + j] = is[j];
530       }
531 
532       j = nrecvs;
533       while (j--) {
534         ierr = MPI_Waitany(nrecvs,rwaits,&k,&status);CHKERRQ(ierr);
535       }
536       ierr = MPI_Waitall(nrecvs,swaits,MPI_STATUSES_IGNORE);CHKERRQ(ierr);
537       ierr = PetscFree2(rwaits,swaits);CHKERRQ(ierr);
538 
539       /******************/
540       ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr);
541     } else if (ctype == IS_COLORING_GHOSTED) {
542       /* Determine local number of columns of this color on this process, including ghost points */
543       nctot = n;
544       ierr  = PetscMalloc1(nctot+1,&cols);CHKERRQ(ierr);
545       ierr  = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr);
546     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type");
547 
548     /* Mark all rows affect by these columns */
549     ierr    = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr);
550     bs2     = bs*bs;
551     nrows_i = 0;
552     for (j=0; j<nctot; j++) { /* loop over columns*/
553       if (ctype == IS_COLORING_GHOSTED) {
554         col = ltog[cols[j]];
555       } else {
556         col = cols[j];
557       }
558       if (col >= cstart && col < cend) { /* column is in A, diagonal block of mat */
559         row      = A_cj + A_ci[col-cstart];
560         nrows    = A_ci[col-cstart+1] - A_ci[col-cstart];
561         nrows_i += nrows;
562         /* loop over columns of A marking them in rowhit */
563         for (k=0; k<nrows; k++) {
564           /* set valaddrhit for part A */
565           spidx            = bs2*spidxA[A_ci[col-cstart] + k];
566           valaddrhit[*row] = &A_val[spidx];
567           rowhit[*row++]   = col - cstart + 1; /* local column index */
568         }
569       } else { /* column is in B, off-diagonal block of mat */
570 #if defined(PETSC_USE_CTABLE)
571         ierr = PetscTableFind(colmap,col+1,&colb);CHKERRQ(ierr);
572         colb--;
573 #else
574         colb = colmap[col] - 1; /* local column index */
575 #endif
576         if (colb == -1) {
577           nrows = 0;
578         } else {
579           colb  = colb/bs;
580           row   = B_cj + B_ci[colb];
581           nrows = B_ci[colb+1] - B_ci[colb];
582         }
583         nrows_i += nrows;
584         /* loop over columns of B marking them in rowhit */
585         for (k=0; k<nrows; k++) {
586           /* set valaddrhit for part B */
587           spidx            = bs2*spidxB[B_ci[colb] + k];
588           valaddrhit[*row] = &B_val[spidx];
589           rowhit[*row++]   = colb + 1 + cend - cstart; /* local column index */
590         }
591       }
592     }
593     ierr = PetscFree(cols);CHKERRQ(ierr);
594     c->nrows[i] = nrows_i;
595 
596     if (c->htype[0] == 'd') {
597       for (j=0; j<m; j++) {
598         if (rowhit[j]) {
599           Jentry[nz].row     = j;              /* local row index */
600           Jentry[nz].col     = rowhit[j] - 1;  /* local column index */
601           Jentry[nz].valaddr = valaddrhit[j];  /* address of mat value for this entry */
602           nz++;
603         }
604       }
605     } else { /* c->htype == 'wp' */
606       for (j=0; j<m; j++) {
607         if (rowhit[j]) {
608           Jentry2[nz].row     = j;              /* local row index */
609           Jentry2[nz].valaddr = valaddrhit[j];  /* address of mat value for this entry */
610           nz++;
611         }
612       }
613     }
614   }
615 
616   if (bcols > 1) { /* reorder Jentry for faster MatFDColoringApply() */
617     ierr = MatFDColoringSetUpBlocked_AIJ_Private(mat,c,nz);CHKERRQ(ierr);
618   }
619 
620   if (isBAIJ) {
621     ierr = MatRestoreColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr);
622     ierr = MatRestoreColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr);
623     ierr = PetscMalloc1(bs*mat->rmap->n,&c->dy);CHKERRQ(ierr);
624   } else {
625     ierr = MatRestoreColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr);
626     ierr = MatRestoreColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr);
627   }
628 
629   ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr);
630   ierr = PetscFree2(rowhit,valaddrhit);CHKERRQ(ierr);
631 
632   if (ctype == IS_COLORING_GHOSTED) {
633     ierr = ISLocalToGlobalMappingRestoreIndices(map,&ltog);CHKERRQ(ierr);
634   }
635   ierr = PetscInfo3(c,"ncolors %D, brows %D and bcols %D are used.\n",c->ncolors,c->brows,c->bcols);CHKERRQ(ierr);
636   PetscFunctionReturn(0);
637 }
638 
639 #undef __FUNCT__
640 #define __FUNCT__ "MatFDColoringCreate_MPIXAIJ"
641 PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
642 {
643   PetscErrorCode ierr;
644   PetscInt       bs,nis=iscoloring->n,m=mat->rmap->n;
645   PetscBool      isBAIJ;
646 
647   PetscFunctionBegin;
648   /* set default brows and bcols for speedup inserting the dense matrix into sparse Jacobian;
649    bcols is chosen s.t. dy-array takes 50% of memory space as mat */
650   ierr = MatGetBlockSize(mat,&bs);CHKERRQ(ierr);
651   ierr = PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);CHKERRQ(ierr);
652   if (isBAIJ || m == 0) {
653     c->brows = m;
654     c->bcols = 1;
655   } else { /* mpiaij matrix */
656     /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */
657     Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data;
658     Mat_SeqAIJ *spA,*spB;
659     Mat        A,B;
660     PetscInt   nz,brows,bcols;
661     PetscReal  mem;
662 
663     bs    = 1; /* only bs=1 is supported for MPIAIJ matrix */
664 
665     A = aij->A;  spA = (Mat_SeqAIJ*)A->data;
666     B = aij->B;  spB = (Mat_SeqAIJ*)B->data;
667     nz = spA->nz + spB->nz; /* total local nonzero entries of mat */
668     mem = nz*(sizeof(PetscScalar) + sizeof(PetscInt)) + 3*m*sizeof(PetscInt);
669     bcols = (PetscInt)(0.5*mem /(m*sizeof(PetscScalar)));
670     brows = 1000/bcols;
671     if (bcols > nis) bcols = nis;
672     if (brows == 0 || brows > m) brows = m;
673     c->brows = brows;
674     c->bcols = bcols;
675   }
676 
677   c->M       = mat->rmap->N/bs;         /* set the global rows and columns and local rows */
678   c->N       = mat->cmap->N/bs;
679   c->m       = mat->rmap->n/bs;
680   c->rstart  = mat->rmap->rstart/bs;
681   c->ncolors = nis;
682   PetscFunctionReturn(0);
683 }
684