xref: /petsc/src/mat/impls/aij/mpi/fdmpiaij.c (revision 4183b19d1aaa6e6deb171185e755cd4b2d6e5448)
1 
2 #include <../src/mat/impls/aij/mpi/mpiaij.h>
3 
4 extern PetscErrorCode MatCreateColmap_MPIAIJ_Private(Mat);
5 
6 #undef __FUNCT__
7 #define __FUNCT__ "MatFDColoringApply_MPIAIJ"
8 PetscErrorCode  MatFDColoringApply_MPIAIJ(Mat J,MatFDColoring coloring,Vec x1,MatStructure *flag,void *sctx)
9 {
10   PetscErrorCode (*f)(void*,Vec,Vec,void*) = (PetscErrorCode (*)(void*,Vec,Vec,void*))coloring->f;
11   PetscErrorCode ierr;
12   PetscInt       k,start,end,l,row,col,colb,**columnsforrow=coloring->columnsforrow,nz;
13   PetscScalar    dx,*y,*xx,*w3_array;
14   PetscScalar    *vscale_array;
15   PetscReal      epsilon = coloring->error_rel,umin = coloring->umin,unorm;
16   Vec            w1      = coloring->w1,w2=coloring->w2,w3;
17   void           *fctx   = coloring->fctx;
18   PetscBool      flg     = PETSC_FALSE;
19   PetscInt       ctype   = coloring->ctype,nxloc;
20   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)J->data;
21   Mat            A=aij->A,B=aij->B;
22   Mat_SeqAIJ     *cspA=(Mat_SeqAIJ*)A->data, *cspB=(Mat_SeqAIJ*)B->data;
23   PetscMPIInt    rank;
24 
25   PetscFunctionBegin;
26   ierr = MPI_Comm_rank(PetscObjectComm((PetscObject)J), &rank);CHKERRQ(ierr);
27   ierr = MatSetUnfactored(J);CHKERRQ(ierr);
28   ierr = PetscOptionsGetBool(NULL,"-mat_fd_coloring_dont_rezero",&flg,NULL);CHKERRQ(ierr);
29   if (flg) {
30     ierr = PetscInfo(coloring,"Not calling MatZeroEntries()\n");CHKERRQ(ierr);
31   } else {
32     PetscBool assembled;
33     ierr = MatAssembled(J,&assembled);CHKERRQ(ierr);
34     if (assembled) {
35       ierr = MatZeroEntries(J);CHKERRQ(ierr);
36     }
37   }
38 
39   if (!coloring->vscale) { //ctype == IS_COLORING_GHOSTED ?
40     printf("[%d] create a non-ghostedcoloring->vscale\n",rank);
41     ierr = VecDuplicate(x1,&coloring->vscale);CHKERRQ(ierr);
42     //SETERRQ(PetscObjectComm((PetscObject)J),PETSC_ERR_ARG_NULL,"Null Object: coloring->scale");
43   }
44 
45   /* Set w1 = F(x1) */
46   if (!coloring->fset) {
47     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
48     ierr = (*f)(sctx,x1,w1,fctx);CHKERRQ(ierr);
49     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
50   } else {
51     coloring->fset = PETSC_FALSE;
52   }
53 
54   if (!coloring->w3) {
55     ierr = VecDuplicate(x1,&coloring->w3);CHKERRQ(ierr);
56     ierr = PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);CHKERRQ(ierr);
57   }
58   w3 = coloring->w3;
59 
60   /* Compute vscale = 1./dx - the local scale factors, including ghost points */
61   ierr = VecGetOwnershipRange(w1,&start,&end);CHKERRQ(ierr); /* =J's row ownershipRange, used by ghosted x! */
62   //printf("[%d] start end %d %d\n",rank,start,end);
63 
64   if (coloring->htype[0] == 'w') {
65     /* tacky test; need to make systematic if we add other approaches to computing h*/
66     ierr = VecNorm(x1,NORM_2,&unorm);CHKERRQ(ierr);
67     dx = 1.0/((1.0 + unorm)*epsilon);
68     ierr = VecSet(coloring->vscale,dx);CHKERRQ(ierr);
69   } else {
70     ierr = VecGetLocalSize(x1,&nxloc);CHKERRQ(ierr);
71     ierr = VecGetArray(x1,&xx);CHKERRQ(ierr);
72     ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
73     for (col=0; col<nxloc; col++) {
74       dx = xx[col];
75       if (PetscAbsScalar(dx) < umin) {
76         if (PetscRealPart(dx) >= 0.0)      dx = umin;
77         else if (PetscRealPart(dx) < 0.0 ) dx = -umin;
78       }
79       dx               *= epsilon;
80       vscale_array[col] = 1.0/dx;
81     }
82     ierr = VecRestoreArray(x1,&xx);CHKERRQ(ierr);
83     ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
84   }
85   if (ctype == IS_COLORING_GLOBAL) {
86     ierr = VecGhostUpdateBegin(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
87     ierr = VecGhostUpdateEnd(coloring->vscale,INSERT_VALUES,SCATTER_FORWARD);CHKERRQ(ierr);
88   }
89 
90   /* Loop over each color */
91   nz = 0;
92   ierr = VecGetArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
93   for (k=0; k<coloring->ncolors; k++) {
94     coloring->currentcolor = k;
95 
96     /*
97       Loop over each column associated with color
98       adding the perturbation to the vector w3 = x1 + dx.
99     */
100     ierr = VecCopy(x1,w3);CHKERRQ(ierr);
101     ierr = VecGetArray(w3,&w3_array);CHKERRQ(ierr);
102     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array - start;
103 
104     for (l=0; l<coloring->ncolumns[k]; l++) {
105       col = coloring->columns[k][l]; /* local column (in global index!) of the matrix we are probing for */
106       /* convert global col to local colb */
107       if (col >= start && col < end) {
108         colb = col-start;
109       } else {
110 #if defined(PETSC_USE_CTABLE)
111         ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr);
112         colb--;
113 #else
114         colb = aij->colmap[col] - 1; /* local column index */
115 #endif
116         colb += end - start;
117       }
118       w3_array[col] += 1.0/vscale_array[colb];
119     }
120     if (ctype == IS_COLORING_GLOBAL) w3_array = w3_array + start;
121     ierr = VecRestoreArray(w3,&w3_array);CHKERRQ(ierr);
122 
123     /*
124       Evaluate function at w3 = x1 + dx (here dx is a vector of perturbations)
125                            w2 = F(x1 + dx) - F(x1)
126     */
127     ierr = PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
128     ierr = (*f)(sctx,w3,w2,fctx);CHKERRQ(ierr);
129     ierr = PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);CHKERRQ(ierr);
130     ierr = VecAXPY(w2,-1.0,w1);CHKERRQ(ierr);
131 
132     /* Loop over rows of vector, putting results into Jacobian matrix */
133     ierr = VecGetArray(w2,&y);CHKERRQ(ierr);
134     for (l=0; l<coloring->nrows[k]; l++) {
135       row                        = coloring->rows[k][l];   /* local row index */
136       *(coloring->valaddr[nz++]) = y[row]*vscale_array[columnsforrow[k][l]];
137     }
138     ierr = VecRestoreArray(w2,&y);CHKERRQ(ierr);
139   } /* endof for each color */
140   if (nz != cspA->nz + cspB->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"nz %d != mat->nz %d\n",nz,cspA->nz+cspB->nz);
141   ierr = MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
142   ierr = MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
143   ierr = VecRestoreArray(coloring->vscale,&vscale_array);CHKERRQ(ierr);
144 
145   coloring->currentcolor = -1;
146   PetscFunctionReturn(0);
147 }
148 
149 #undef __FUNCT__
150 #define __FUNCT__ "MatFDColoringCreate_MPIAIJ_new"
151 PetscErrorCode MatFDColoringCreate_MPIAIJ_new(Mat mat,ISColoring iscoloring,MatFDColoring c)
152 {
153   Mat_MPIAIJ             *aij = (Mat_MPIAIJ*)mat->data;
154   PetscErrorCode         ierr;
155   PetscMPIInt            size,*ncolsonproc,*disp,nn;
156   PetscInt               i,n,nrows,j,k,m,ncols,col;
157   const PetscInt         *is,*A_ci,*A_cj,*B_ci,*B_cj,*row = NULL,*ltog=NULL;
158   PetscInt               nis = iscoloring->n,nctot,*cols;
159   PetscInt               *rowhit,cstart,cend,colb;
160   IS                     *isa;
161   ISLocalToGlobalMapping map = mat->cmap->mapping;
162   PetscInt               ctype=c->ctype;
163   Mat                    A=aij->A,B=aij->B;
164   Mat_SeqAIJ             *cspA=(Mat_SeqAIJ*)A->data, *cspB=(Mat_SeqAIJ*)B->data;
165   PetscScalar            *A_val=cspA->a,*B_val=cspB->a;
166   PetscInt               spidx;
167   PetscInt               *spidxA,*spidxB,nz;
168   PetscScalar            **valaddrhit;
169 
170   PetscFunctionBegin;
171   if (ctype == IS_COLORING_GHOSTED) {
172     if(!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping");
173     ierr = ISLocalToGlobalMappingGetIndices(map,&ltog);CHKERRQ(ierr);
174   }
175 
176   m         = mat->rmap->n;
177   cstart    = mat->cmap->rstart;
178   cend      = mat->cmap->rend;
179   c->M      = mat->rmap->N;         /* set the global rows and columns and local rows */
180   c->N      = mat->cmap->N;
181   c->m      = m;
182   c->rstart = mat->rmap->rstart;
183 
184   c->ncolors = nis;
185   ierr       = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr);
186   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr);
187   ierr       = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr);
188   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr);
189   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr);
190   ierr       = PetscLogObjectMemory((PetscObject)c,5*nis*sizeof(PetscInt));CHKERRQ(ierr);
191 
192   nz         = cspA->nz + cspB->nz; /* total nonzero entries of mat */
193   ierr       = PetscMalloc(nz*sizeof(PetscScalar*),&c->valaddr);CHKERRQ(ierr);
194   ierr       = PetscLogObjectMemory((PetscObject)c,nz*sizeof(PetscScalar*));CHKERRQ(ierr);
195 
196   /* Allow access to data structures of local part of matrix
197    - creates aij->colmap which maps global column number to local number in part B */
198   if (!aij->colmap) {
199     ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr);
200   }
201   ierr = MatGetColumnIJ_SeqAIJ_Color(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr);
202   ierr = MatGetColumnIJ_SeqAIJ_Color(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr);
203 
204   ierr = PetscMalloc2(m+1,PetscInt,&rowhit,m+1,PetscScalar*,&valaddrhit);CHKERRQ(ierr);
205   nz = 0;
206   ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr);
207   for (i=0; i<nis; i++) { /* for each local color */
208     ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr);
209     ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr);
210 
211     c->ncolumns[i] = n; /* local number of columns of this color on this process */
212     if (n) {
213       ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr);
214       ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr);
215       ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr);
216     } else {
217       c->columns[i] = 0;
218     }
219 
220     if (ctype == IS_COLORING_GLOBAL) {
221       /* Determine nctot, the total (parallel) number of columns of this color */
222       ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
223       ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr);
224 
225       /* ncolsonproc[j]: local ncolumns on proc[j] of this color */
226       ierr  = PetscMPIIntCast(n,&nn);CHKERRQ(ierr);
227       ierr  = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
228       nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j];
229       if (!nctot) {
230         ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr);
231       }
232 
233       disp[0] = 0;
234       for (j=1; j<size; j++) {
235         disp[j] = disp[j-1] + ncolsonproc[j-1];
236       }
237 
238       /* Get cols, the complete list of columns for this color on each process */
239       ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr);
240       ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
241       ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr);
242     } else if (ctype == IS_COLORING_GHOSTED) {
243       /* Determine local number of columns of this color on this process, including ghost points */
244       nctot = n;
245       ierr  = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr);
246       ierr  = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr);
247     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type");
248 
249     /* Mark all rows affect by these columns */
250     ierr = PetscMemzero(rowhit,m*sizeof(PetscInt));CHKERRQ(ierr);
251     for (j=0; j<nctot; j++) { /* loop over columns*/
252       if (ctype == IS_COLORING_GHOSTED) {
253         col = ltog[cols[j]];
254       } else {
255         col = cols[j];
256       }
257       if (col >= cstart && col < cend) { /* column is in diagonal block of matrix A */
258         row = A_cj + A_ci[col-cstart];
259         nrows = A_ci[col-cstart+1] - A_ci[col-cstart];
260         /* loop over columns of A marking them in rowhit */
261         for (k=0; k<nrows; k++) {
262           /* set valaddrhit for part A */
263           spidx            = spidxA[A_ci[col-cstart] + k];
264           valaddrhit[*row] = &A_val[spidx];
265           rowhit[*row++]   = col - cstart + 1; /* local column index */
266         }
267       } else { /* column is in off-diagonal block of matrix B */
268 #if defined(PETSC_USE_CTABLE)
269         ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr);
270         colb--;
271 #else
272         colb = aij->colmap[col] - 1; /* local column index */
273 #endif
274         if (colb == -1) {
275           nrows = 0;
276         } else {
277           row   = B_cj + B_ci[colb];
278           nrows = B_ci[colb+1] - B_ci[colb];
279         }
280         /* loop over columns of B marking them in rowhit */
281         for (k=0; k<nrows; k++) {
282           /* set valaddrhit for part B */
283           spidx            = spidxB[B_ci[colb] + k];
284           valaddrhit[*row] = &B_val[spidx];
285           rowhit[*row++]   = colb + 1 + cend - cstart; /* local column index */
286         }
287       }
288     }
289 
290     /* count the number of hits */
291     nrows = 0;
292     for (j=0; j<m; j++) {
293       if (rowhit[j]) nrows++;
294     }
295     c->nrows[i] = nrows;
296     ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr);
297     ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr);
298     ierr        = PetscLogObjectMemory((PetscObject)c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr);
299     nrows       = 0;
300     for (j=0; j<m; j++) {
301       if (rowhit[j]) {
302         c->rows[i][nrows]          = j;              /* local row index */
303         c->columnsforrow[i][nrows] = rowhit[j] - 1;  /* local column index */
304         c->valaddr[nz++]           = valaddrhit[j];  /* address of mat value for this entry */
305         nrows++;
306       }
307     }
308     ierr = PetscFree(cols);CHKERRQ(ierr);
309   }
310   if (nz != cspA->nz + cspB->nz) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONGSTATE,"nz %d != mat->nz %d\n",nz,cspA->nz+cspB->nz);
311 
312   /* create vscale for storing dx */
313   if (ctype == IS_COLORING_GLOBAL) {
314     ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),m,PETSC_DETERMINE,B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr);
315   }
316 
317   ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr);
318 
319   ierr = PetscFree2(rowhit,valaddrhit);CHKERRQ(ierr);
320   ierr = MatRestoreColumnIJ_SeqAIJ_Color(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);CHKERRQ(ierr);
321   ierr = MatRestoreColumnIJ_SeqAIJ_Color(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);CHKERRQ(ierr);
322   if (ctype == IS_COLORING_GHOSTED) {
323     ierr = ISLocalToGlobalMappingRestoreIndices(map,&ltog);CHKERRQ(ierr);
324   }
325 
326   mat->ops->fdcoloringapply = MatFDColoringApply_MPIAIJ;
327   PetscFunctionReturn(0);
328 }
329 
330 /*------------------------------------------------------*/
331 #undef __FUNCT__
332 #define __FUNCT__ "MatFDColoringCreate_MPIAIJ"
333 PetscErrorCode MatFDColoringCreate_MPIAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
334 {
335   Mat_MPIAIJ             *aij = (Mat_MPIAIJ*)mat->data;
336   PetscErrorCode         ierr;
337   PetscMPIInt            size,*ncolsonproc,*disp,nn;
338   PetscInt               i,n,nrows,j,k,m,ncols,col;
339   const PetscInt         *is,*A_ci,*A_cj,*B_ci,*B_cj,*rows = 0,*ltog;
340   PetscInt               nis = iscoloring->n,nctot,*cols;
341   PetscInt               *rowhit,M,cstart,cend,colb;
342   PetscInt               *columnsforrow,l;
343   IS                     *isa;
344   PetscBool              done,flg;
345   ISLocalToGlobalMapping map   = mat->cmap->mapping;
346   PetscInt               ctype=c->ctype;
347   PetscBool              new_impl=PETSC_FALSE;
348 
349   PetscFunctionBegin;
350   ierr = PetscOptionsName("-new","using new impls","",&new_impl);CHKERRQ(ierr);
351   if (new_impl){
352     ierr =  MatFDColoringCreate_MPIAIJ_new(mat,iscoloring,c);CHKERRQ(ierr);
353     PetscFunctionReturn(0);
354   }
355   if (ctype == IS_COLORING_GHOSTED && !map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping");
356 
357   if (map) {ierr = ISLocalToGlobalMappingGetIndices(map,&ltog);CHKERRQ(ierr);}
358   else     ltog = NULL;
359   ierr = ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);CHKERRQ(ierr);
360 
361   M         = mat->rmap->n;
362   cstart    = mat->cmap->rstart;
363   cend      = mat->cmap->rend;
364   c->M      = mat->rmap->N;         /* set the global rows and columns and local rows */
365   c->N      = mat->cmap->N;
366   c->m      = mat->rmap->n;
367   c->rstart = mat->rmap->rstart;
368 
369   c->ncolors = nis;
370   ierr       = PetscMalloc(nis*sizeof(PetscInt),&c->ncolumns);CHKERRQ(ierr);
371   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->columns);CHKERRQ(ierr);
372   ierr       = PetscMalloc(nis*sizeof(PetscInt),&c->nrows);CHKERRQ(ierr);
373   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->rows);CHKERRQ(ierr);
374   ierr       = PetscMalloc(nis*sizeof(PetscInt*),&c->columnsforrow);CHKERRQ(ierr);
375   ierr       = PetscLogObjectMemory((PetscObject)c,5*nis*sizeof(PetscInt));CHKERRQ(ierr);
376 
377   /* Allow access to data structures of local part of matrix */
378   if (!aij->colmap) {
379     ierr = MatCreateColmap_MPIAIJ_Private(mat);CHKERRQ(ierr);
380   }
381   ierr = MatGetColumnIJ(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr);
382   ierr = MatGetColumnIJ(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr);
383 
384   ierr = PetscMalloc((M+1)*sizeof(PetscInt),&rowhit);CHKERRQ(ierr);
385   ierr = PetscMalloc((M+1)*sizeof(PetscInt),&columnsforrow);CHKERRQ(ierr);
386 
387   for (i=0; i<nis; i++) {
388     ierr = ISGetLocalSize(isa[i],&n);CHKERRQ(ierr);
389     ierr = ISGetIndices(isa[i],&is);CHKERRQ(ierr);
390 
391     c->ncolumns[i] = n; /* local number of columns of this color on this process */
392     if (n) {
393       ierr = PetscMalloc(n*sizeof(PetscInt),&c->columns[i]);CHKERRQ(ierr);
394       ierr = PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));CHKERRQ(ierr);
395       ierr = PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));CHKERRQ(ierr);
396     } else {
397       c->columns[i] = 0;
398     }
399 
400     if (ctype == IS_COLORING_GLOBAL) {
401       /* Determine the total (parallel) number of columns of this color */
402       ierr = MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);CHKERRQ(ierr);
403       ierr = PetscMalloc2(size,PetscMPIInt,&ncolsonproc,size,PetscMPIInt,&disp);CHKERRQ(ierr);
404 
405       ierr  = PetscMPIIntCast(n,&nn);CHKERRQ(ierr);
406       ierr  = MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
407       nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j];
408       if (!nctot) {
409         ierr = PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");CHKERRQ(ierr);
410       }
411 
412       disp[0] = 0;
413       for (j=1; j<size; j++) {
414         disp[j] = disp[j-1] + ncolsonproc[j-1];
415       }
416 
417       /* Get complete list of columns for color on each processor */
418       ierr = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr);
419       ierr = MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));CHKERRQ(ierr);
420       ierr = PetscFree2(ncolsonproc,disp);CHKERRQ(ierr);
421     } else if (ctype == IS_COLORING_GHOSTED) {
422       /* Determine local number of columns of this color on this process, including ghost points */
423       nctot = n;
424       ierr  = PetscMalloc((nctot+1)*sizeof(PetscInt),&cols);CHKERRQ(ierr);
425       ierr  = PetscMemcpy(cols,is,n*sizeof(PetscInt));CHKERRQ(ierr);
426     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type");
427 
428     /*
429        Mark all rows affect by these columns
430     */
431     /* Temporary option to allow for debugging/testing */
432     flg  = PETSC_FALSE;
433     ierr = PetscOptionsGetBool(NULL,"-matfdcoloring_slow",&flg,NULL);CHKERRQ(ierr);
434     if (!flg) { /*-----------------------------------------------------------------------------*/
435       /* crude, fast version */
436       ierr = PetscMemzero(rowhit,M*sizeof(PetscInt));CHKERRQ(ierr);
437       /* loop over columns*/
438       for (j=0; j<nctot; j++) {
439         if (ctype == IS_COLORING_GHOSTED) {
440           col = ltog[cols[j]];
441         } else {
442           col = cols[j];
443         }
444         if (col >= cstart && col < cend) {
445           /* column is in diagonal block of matrix */
446           rows = A_cj + A_ci[col-cstart];
447           m    = A_ci[col-cstart+1] - A_ci[col-cstart];
448         } else {
449 #if defined(PETSC_USE_CTABLE)
450           ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr);
451           colb--;
452 #else
453           colb = aij->colmap[col] - 1;
454 #endif
455           if (colb == -1) {
456             m = 0;
457           } else {
458             rows = B_cj + B_ci[colb];
459             m    = B_ci[colb+1] - B_ci[colb];
460           }
461         }
462         /* loop over columns marking them in rowhit */
463         for (k=0; k<m; k++) {
464           rowhit[*rows++] = col + 1;
465         }
466       }
467 
468       /* count the number of hits */
469       nrows = 0;
470       for (j=0; j<M; j++) {
471         if (rowhit[j]) nrows++;
472       }
473       c->nrows[i] = nrows;
474       ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr);
475       ierr        = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr);
476       ierr        = PetscLogObjectMemory((PetscObject)c,2*(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr);
477       nrows       = 0;
478       for (j=0; j<M; j++) {
479         if (rowhit[j]) {
480           c->rows[i][nrows]          = j;              /* local row index */
481           c->columnsforrow[i][nrows] = rowhit[j] - 1;  /* global column index */
482           nrows++;
483         }
484       }
485     } else { /*-------------------------------------------------------------------------------*/
486       /* slow version, using rowhit as a linked list */
487       PetscInt currentcol,fm,mfm;
488       rowhit[M] = M;
489       nrows     = 0;
490       /* loop over columns*/
491       for (j=0; j<nctot; j++) {
492         if (ctype == IS_COLORING_GHOSTED) {
493           col = ltog[cols[j]];
494         } else {
495           col = cols[j];
496         }
497         if (col >= cstart && col < cend) {
498           /* column is in diagonal block of matrix */
499           rows = A_cj + A_ci[col-cstart];
500           m    = A_ci[col-cstart+1] - A_ci[col-cstart];
501         } else {
502 #if defined(PETSC_USE_CTABLE)
503           ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr);
504           colb--;
505 #else
506           colb = aij->colmap[col] - 1;
507 #endif
508           if (colb == -1) {
509             m = 0;
510           } else {
511             rows = B_cj + B_ci[colb];
512             m    = B_ci[colb+1] - B_ci[colb];
513           }
514         }
515 
516         /* loop over columns marking them in rowhit */
517         fm = M;    /* fm points to first entry in linked list */
518         for (k=0; k<m; k++) {
519           currentcol = *rows++;
520           /* is it already in the list? */
521           do {
522             mfm = fm;
523             fm  = rowhit[fm];
524           } while (fm < currentcol);
525           /* not in list so add it */
526           if (fm != currentcol) {
527             nrows++;
528             columnsforrow[currentcol] = col;
529             /* next three lines insert new entry into linked list */
530             rowhit[mfm]        = currentcol;
531             rowhit[currentcol] = fm;
532             fm                 = currentcol;
533             /* fm points to present position in list since we know the columns are sorted */
534           } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Invalid coloring of matrix detected");
535         }
536       }
537       c->nrows[i] = nrows;
538 
539       ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->rows[i]);CHKERRQ(ierr);
540       ierr = PetscMalloc((nrows+1)*sizeof(PetscInt),&c->columnsforrow[i]);CHKERRQ(ierr);
541       ierr = PetscLogObjectMemory((PetscObject)c,(nrows+1)*sizeof(PetscInt));CHKERRQ(ierr);
542       /* now store the linked list of rows into c->rows[i] */
543       nrows = 0;
544       fm    = rowhit[M];
545       do {
546         c->rows[i][nrows]            = fm;
547         c->columnsforrow[i][nrows++] = columnsforrow[fm];
548         fm                           = rowhit[fm];
549       } while (fm < M);
550     } /* ---------------------------------------------------------------------------------------*/
551     ierr = PetscFree(cols);CHKERRQ(ierr);
552   }
553 
554   /* Optimize by adding the vscale, and scaleforrow[][] fields */
555   /*
556        vscale will contain the "diagonal" on processor scalings followed by the off processor
557   */
558   if (ctype == IS_COLORING_GLOBAL) {
559     ierr = VecCreateGhost(PetscObjectComm((PetscObject)mat),aij->A->rmap->n,PETSC_DETERMINE,aij->B->cmap->n,aij->garray,&c->vscale);CHKERRQ(ierr);
560     ierr = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr);
561     for (k=0; k<c->ncolors; k++) {
562       ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr);
563       for (l=0; l<c->nrows[k]; l++) {
564         col = c->columnsforrow[k][l];
565         if (col >= cstart && col < cend) {
566           /* column is in diagonal block of matrix */
567           colb = col - cstart;
568         } else {
569           /* column  is in "off-processor" part */
570 #if defined(PETSC_USE_CTABLE)
571           ierr = PetscTableFind(aij->colmap,col+1,&colb);CHKERRQ(ierr);
572           colb--;
573 #else
574           colb = aij->colmap[col] - 1;
575 #endif
576           colb += cend - cstart;
577         }
578         c->vscaleforrow[k][l] = colb;
579       }
580     }
581   } else if (ctype == IS_COLORING_GHOSTED) {
582     /* Get gtol mapping */
583     PetscInt N = mat->cmap->N,nlocal,*gtol;
584     ierr = PetscMalloc((N+1)*sizeof(PetscInt),&gtol);CHKERRQ(ierr);
585     for (i=0; i<N; i++) gtol[i] = -1;
586     ierr = ISLocalToGlobalMappingGetSize(map,&nlocal);CHKERRQ(ierr);
587     for (i=0; i<nlocal; i++) gtol[ltog[i]] = i;
588 
589     c->vscale = 0; /* will be created in MatFDColoringApply() */
590     ierr      = PetscMalloc(c->ncolors*sizeof(PetscInt*),&c->vscaleforrow);CHKERRQ(ierr);
591     for (k=0; k<c->ncolors; k++) {
592       ierr = PetscMalloc((c->nrows[k]+1)*sizeof(PetscInt),&c->vscaleforrow[k]);CHKERRQ(ierr);
593       for (l=0; l<c->nrows[k]; l++) {
594         col = c->columnsforrow[k][l];      /* global column index */
595         c->vscaleforrow[k][l] = gtol[col]; /* local column index */
596       }
597     }
598     ierr = PetscFree(gtol);CHKERRQ(ierr);
599   }
600   ierr = ISColoringRestoreIS(iscoloring,&isa);CHKERRQ(ierr);
601 
602   ierr = PetscFree(rowhit);CHKERRQ(ierr);
603   ierr = PetscFree(columnsforrow);CHKERRQ(ierr);
604   ierr = MatRestoreColumnIJ(aij->A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&done);CHKERRQ(ierr);
605   ierr = MatRestoreColumnIJ(aij->B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&done);CHKERRQ(ierr);
606   if (map) {ierr = ISLocalToGlobalMappingRestoreIndices(map,&ltog);CHKERRQ(ierr);}
607   PetscFunctionReturn(0);
608 }
609 
610 
611 
612 
613 
614 
615