Actual source code: fdmpiaij.c
petsc-3.7.1 2016-05-15
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      2: #include <../src/mat/impls/aij/mpi/mpiaij.h>
      3: #include <../src/mat/impls/baij/mpi/mpibaij.h>
      4: #include <petsc/private/isimpl.h>

      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;

     27:   /* (1) Set w1 = F(x1) */
     28:   if (!coloring->fset) {
     29:     PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);
     30:     (*f)(sctx,x1,w1,fctx);
     31:     PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);
     32:   } else {
     33:     coloring->fset = PETSC_FALSE;
     34:   }

     36:   /* (2) Compute vscale = 1./dx - the local scale factors, including ghost points */
     37:   VecGetLocalSize(x1,&nxloc);
     38:   if (coloring->htype[0] == 'w') {
     39:     /* vscale = dx is a constant scalar */
     40:     VecNorm(x1,NORM_2,&unorm);
     41:     dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon);
     42:   } else {
     43:     VecGetArrayRead(x1,&xx);
     44:     VecGetArray(vscale,&vscale_array);
     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:     VecRestoreArrayRead(x1,&xx);
     55:     VecRestoreArray(vscale,&vscale_array);
     56:   }
     57:   if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') {
     58:     VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);
     59:     VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);
     60:   }

     62:   /* (3) Loop over each color */
     63:   if (!coloring->w3) {
     64:     VecDuplicate(x1,&coloring->w3);
     65:     PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);
     66:   }
     67:   w3 = coloring->w3;

     69:   VecGetOwnershipRange(x1,&cstart,&cend); /* used by ghosted vscale */
     70:   if (vscale) {
     71:     VecGetArray(vscale,&vscale_array);
     72:   }
     73:   nz   = 0;
     74:   for (k=0; k<ncolors; k++) {
     75:     coloring->currentcolor = k;

     77:     /*
     78:       (3-1) Loop over each column associated with color
     79:       adding the perturbation to the vector w3 = x1 + dx.
     80:     */
     81:     VecCopy(x1,w3);
     82:     dy_i = dy;
     83:     for (i=0; i<bs; i++) {     /* Loop over a block of columns */
     84:       VecGetArray(w3,&w3_array);
     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:       VecRestoreArray(w3,&w3_array);

    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:       PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);
    109:       VecPlaceArray(w2,dy_i); /* place w2 to the array dy_i */
    110:       (*f)(sctx,w3,w2,fctx);
    111:       PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);
    112:       VecAXPY(w2,-1.0,w1);
    113:       VecResetArray(w2);
    114:       dy_i += nxloc; /* points to dy+i*nxloc */
    115:     }

    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:   MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);
    151:   MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);
    152:   if (vscale) {
    153:     VecRestoreArray(vscale,&vscale_array);
    154:   }

    156:   coloring->currentcolor = -1;
    157:   return(0);
    158: }

    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;

    179:   /* (1) Set w1 = F(x1) */
    180:   if (!coloring->fset) {
    181:     PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);
    182:     (*f)(sctx,x1,w1,fctx);
    183:     PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);
    184:   } else {
    185:     coloring->fset = PETSC_FALSE;
    186:   }

    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:     VecNorm(x1,NORM_2,&unorm);
    192:     dx = 1.0/(PetscSqrtReal(1.0 + unorm)*epsilon);
    193:   } else {
    194:     VecGetLocalSize(x1,&nxloc);
    195:     VecGetArrayRead(x1,&xx);
    196:     VecGetArray(vscale,&vscale_array);
    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:     VecRestoreArrayRead(x1,&xx);
    207:     VecRestoreArray(vscale,&vscale_array);
    208:   }
    209:   if (ctype == IS_COLORING_GLOBAL && coloring->htype[0] == 'd') {
    210:     VecGhostUpdateBegin(vscale,INSERT_VALUES,SCATTER_FORWARD);
    211:     VecGhostUpdateEnd(vscale,INSERT_VALUES,SCATTER_FORWARD);
    212:   }

    214:   /* (3) Loop over each color */
    215:   if (!coloring->w3) {
    216:     VecDuplicate(x1,&coloring->w3);
    217:     PetscLogObjectParent((PetscObject)coloring,(PetscObject)coloring->w3);
    218:   }
    219:   w3 = coloring->w3;

    221:   VecGetOwnershipRange(x1,&cstart,&cend); /* used by ghosted vscale */
    222:   if (vscale) {
    223:     VecGetArray(vscale,&vscale_array);
    224:   }
    225:   nz   = 0;

    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;

    231:     nbcols = 0;
    232:     for (k=0; k<ncolors; k+=bcols) {
    233:       coloring->currentcolor = k;

    235:       /*
    236:        (3-1) Loop over each column associated with color
    237:        adding the perturbation to the vector w3 = x1 + dx.
    238:        */

    240:       dy_k = dy;
    241:       if (k + bcols > ncolors) bcols = ncolors - k;
    242:       for (i=0; i<bcols; i++) {

    244:         VecCopy(x1,w3);
    245:         VecGetArray(w3,&w3_array);
    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:         VecRestoreArray(w3,&w3_array);

    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:         PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);
    268:         VecPlaceArray(w2,dy_k); /* place w2 to the array dy_i */
    269:         (*f)(sctx,w3,w2,fctx);
    270:         PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);
    271:         VecAXPY(w2,-1.0,w1);
    272:         VecResetArray(w2);
    273:         dy_k += m; /* points to dy+i*nxloc */
    274:       }

    276:       /*
    277:        (3-3) Loop over block rows of vector, putting results into Jacobian matrix
    278:        */
    279:       nrows_k = nrows[nbcols++];
    280:       VecGetArray(w2,&y);

    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:       VecRestoreArray(w2,&y);
    295:     }
    296:   } else { /* bcols == 1 */
    297:     for (k=0; k<ncolors; k++) {
    298:       coloring->currentcolor = k;

    300:       /*
    301:        (3-1) Loop over each column associated with color
    302:        adding the perturbation to the vector w3 = x1 + dx.
    303:        */
    304:       VecCopy(x1,w3);
    305:       VecGetArray(w3,&w3_array);
    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:       VecRestoreArray(w3,&w3_array);

    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:       PetscLogEventBegin(MAT_FDColoringFunction,0,0,0,0);
    328:       (*f)(sctx,w3,w2,fctx);
    329:       PetscLogEventEnd(MAT_FDColoringFunction,0,0,0,0);
    330:       VecAXPY(w2,-1.0,w1);

    332:       /*
    333:        (3-3) Loop over rows of vector, putting results into Jacobian matrix
    334:        */
    335:       nrows_k = nrows[k];
    336:       VecGetArray(w2,&y);
    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:       VecRestoreArray(w2,&y);
    350:     }
    351:   }

    353:   MatAssemblyBegin(J,MAT_FINAL_ASSEMBLY);
    354:   MatAssemblyEnd(J,MAT_FINAL_ASSEMBLY);
    355:   if (vscale) {
    356:     VecRestoreArray(vscale,&vscale_array);
    357:   }
    358:   coloring->currentcolor = -1;
    359:   return(0);
    360: }

    364: PetscErrorCode MatFDColoringSetUp_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
    365: {
    366:   PetscErrorCode         ierr;
    367:   PetscMPIInt            size,*ncolsonproc,*disp,nn;
    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;
    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: #if defined(PETSC_USE_CTABLE)
    381:   PetscTable             colmap=NULL;
    382: #else
    383:   PetscInt               *colmap=NULL;     /* local col number of off-diag col */
    384: #endif

    387:   if (ctype == IS_COLORING_GHOSTED) {
    388:     if (!map) SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_ARG_INCOMP,"When using ghosted differencing matrix must have local to global mapping provided with MatSetLocalToGlobalMapping");
    389:     ISLocalToGlobalMappingGetIndices(map,&ltog);
    390:   }

    392:   MatGetBlockSize(mat,&bs);
    393:   PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);
    394:   if (isBAIJ) {
    395:     Mat_MPIBAIJ *baij=(Mat_MPIBAIJ*)mat->data;
    396:     Mat_SeqBAIJ *spA,*spB;
    397:     A = baij->A;  spA = (Mat_SeqBAIJ*)A->data; A_val = spA->a;
    398:     B = baij->B;  spB = (Mat_SeqBAIJ*)B->data; B_val = spB->a;
    399:     nz = spA->nz + spB->nz; /* total nonzero entries of mat */
    400:     if (!baij->colmap) {
    401:       MatCreateColmap_MPIBAIJ_Private(mat);
    402:     }
    403:     colmap = baij->colmap;
    404:     MatGetColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);
    405:     MatGetColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);

    407:     if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') {  /* create vscale for storing dx */
    408:       PetscInt    *garray;
    409:       PetscMalloc1(B->cmap->n,&garray);
    410:       for (i=0; i<baij->B->cmap->n/bs; i++) {
    411:         for (j=0; j<bs; j++) {
    412:           garray[i*bs+j] = bs*baij->garray[i]+j;
    413:         }
    414:       }
    415:       VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,garray,&c->vscale);
    416:       PetscFree(garray);
    417:     }
    418:   } else {
    419:     Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data;
    420:     Mat_SeqAIJ *spA,*spB;
    421:     A = aij->A;  spA = (Mat_SeqAIJ*)A->data; A_val = spA->a;
    422:     B = aij->B;  spB = (Mat_SeqAIJ*)B->data; B_val = spB->a;
    423:     nz = spA->nz + spB->nz; /* total nonzero entries of mat */
    424:     if (!aij->colmap) {
    425:       /* Allow access to data structures of local part of matrix
    426:        - creates aij->colmap which maps global column number to local number in part B */
    427:       MatCreateColmap_MPIAIJ_Private(mat);
    428:     }
    429:     colmap = aij->colmap;
    430:     MatGetColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);
    431:     MatGetColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);

    433:     bs = 1; /* only bs=1 is supported for non MPIBAIJ matrix */

    435:     if (ctype == IS_COLORING_GLOBAL && c->htype[0] == 'd') { /* create vscale for storing dx */
    436:       VecCreateGhost(PetscObjectComm((PetscObject)mat),mat->cmap->n,PETSC_DETERMINE,B->cmap->n,aij->garray,&c->vscale);
    437:     }
    438:   }

    440:   m         = mat->rmap->n/bs;
    441:   cstart    = mat->cmap->rstart/bs;
    442:   cend      = mat->cmap->rend/bs;

    444:   PetscMalloc1(nis,&c->ncolumns);
    445:   PetscMalloc1(nis,&c->columns);
    446:   PetscMalloc1(nis,&c->nrows);
    447:   PetscLogObjectMemory((PetscObject)c,3*nis*sizeof(PetscInt));

    449:   if (c->htype[0] == 'd') {
    450:     PetscMalloc1(nz,&Jentry);
    451:     PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry));
    452:     c->matentry = Jentry;
    453:   } else if (c->htype[0] == 'w') {
    454:     PetscMalloc1(nz,&Jentry2);
    455:     PetscLogObjectMemory((PetscObject)c,nz*sizeof(MatEntry2));
    456:     c->matentry2 = Jentry2;
    457:   } else SETERRQ(PetscObjectComm((PetscObject)mat),PETSC_ERR_SUP,"htype is not supported");

    459:   PetscMalloc2(m+1,&rowhit,m+1,&valaddrhit);
    460:   nz = 0;
    461:   ISColoringGetIS(iscoloring,PETSC_IGNORE,&isa);
    462:   for (i=0; i<nis; i++) { /* for each local color */
    463:     ISGetLocalSize(isa[i],&n);
    464:     ISGetIndices(isa[i],&is);

    466:     c->ncolumns[i] = n; /* local number of columns of this color on this process */
    467:     if (n) {
    468:       PetscMalloc1(n,&c->columns[i]);
    469:       PetscLogObjectMemory((PetscObject)c,n*sizeof(PetscInt));
    470:       PetscMemcpy(c->columns[i],is,n*sizeof(PetscInt));
    471:     } else {
    472:       c->columns[i] = 0;
    473:     }

    475:     if (ctype == IS_COLORING_GLOBAL) {
    476:       /* Determine nctot, the total (parallel) number of columns of this color */
    477:       MPI_Comm_size(PetscObjectComm((PetscObject)mat),&size);
    478:       PetscMalloc2(size,&ncolsonproc,size,&disp);

    480:       /* ncolsonproc[j]: local ncolumns on proc[j] of this color */
    481:       PetscMPIIntCast(n,&nn);
    482:       MPI_Allgather(&nn,1,MPI_INT,ncolsonproc,1,MPI_INT,PetscObjectComm((PetscObject)mat));
    483:       nctot = 0; for (j=0; j<size; j++) nctot += ncolsonproc[j];
    484:       if (!nctot) {
    485:         PetscInfo(mat,"Coloring of matrix has some unneeded colors with no corresponding rows\n");
    486:       }

    488:       disp[0] = 0;
    489:       for (j=1; j<size; j++) {
    490:         disp[j] = disp[j-1] + ncolsonproc[j-1];
    491:       }

    493:       /* Get cols, the complete list of columns for this color on each process */
    494:       PetscMalloc1(nctot+1,&cols);
    495:       MPI_Allgatherv((void*)is,n,MPIU_INT,cols,ncolsonproc,disp,MPIU_INT,PetscObjectComm((PetscObject)mat));
    496:       PetscFree2(ncolsonproc,disp);
    497:     } else if (ctype == IS_COLORING_GHOSTED) {
    498:       /* Determine local number of columns of this color on this process, including ghost points */
    499:       nctot = n;
    500:       PetscMalloc1(nctot+1,&cols);
    501:       PetscMemcpy(cols,is,n*sizeof(PetscInt));
    502:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Not provided for this MatFDColoring type");

    504:     /* Mark all rows affect by these columns */
    505:     PetscMemzero(rowhit,m*sizeof(PetscInt));
    506:     bs2     = bs*bs;
    507:     nrows_i = 0;
    508:     for (j=0; j<nctot; j++) { /* loop over columns*/
    509:       if (ctype == IS_COLORING_GHOSTED) {
    510:         col = ltog[cols[j]];
    511:       } else {
    512:         col = cols[j];
    513:       }
    514:       if (col >= cstart && col < cend) { /* column is in A, diagonal block of mat */
    515:         row      = A_cj + A_ci[col-cstart];
    516:         nrows    = A_ci[col-cstart+1] - A_ci[col-cstart];
    517:         nrows_i += nrows;
    518:         /* loop over columns of A marking them in rowhit */
    519:         for (k=0; k<nrows; k++) {
    520:           /* set valaddrhit for part A */
    521:           spidx            = bs2*spidxA[A_ci[col-cstart] + k];
    522:           valaddrhit[*row] = &A_val[spidx];
    523:           rowhit[*row++]   = col - cstart + 1; /* local column index */
    524:         }
    525:       } else { /* column is in B, off-diagonal block of mat */
    526: #if defined(PETSC_USE_CTABLE)
    527:         PetscTableFind(colmap,col+1,&colb);
    528:         colb--;
    529: #else
    530:         colb = colmap[col] - 1; /* local column index */
    531: #endif
    532:         if (colb == -1) {
    533:           nrows = 0;
    534:         } else {
    535:           colb  = colb/bs;
    536:           row   = B_cj + B_ci[colb];
    537:           nrows = B_ci[colb+1] - B_ci[colb];
    538:         }
    539:         nrows_i += nrows;
    540:         /* loop over columns of B marking them in rowhit */
    541:         for (k=0; k<nrows; k++) {
    542:           /* set valaddrhit for part B */
    543:           spidx            = bs2*spidxB[B_ci[colb] + k];
    544:           valaddrhit[*row] = &B_val[spidx];
    545:           rowhit[*row++]   = colb + 1 + cend - cstart; /* local column index */
    546:         }
    547:       }
    548:     }
    549:     c->nrows[i] = nrows_i;

    551:     if (c->htype[0] == 'd') {
    552:       for (j=0; j<m; j++) {
    553:         if (rowhit[j]) {
    554:           Jentry[nz].row     = j;              /* local row index */
    555:           Jentry[nz].col     = rowhit[j] - 1;  /* local column index */
    556:           Jentry[nz].valaddr = valaddrhit[j];  /* address of mat value for this entry */
    557:           nz++;
    558:         }
    559:       }
    560:     } else { /* c->htype == 'wp' */
    561:       for (j=0; j<m; j++) {
    562:         if (rowhit[j]) {
    563:           Jentry2[nz].row     = j;              /* local row index */
    564:           Jentry2[nz].valaddr = valaddrhit[j];  /* address of mat value for this entry */
    565:           nz++;
    566:         }
    567:       }
    568:     }
    569:     PetscFree(cols);
    570:   }

    572:   if (bcols > 1) { /* reorder Jentry for faster MatFDColoringApply() */
    573:     MatFDColoringSetUpBlocked_AIJ_Private(mat,c,nz);
    574:   }

    576:   if (isBAIJ) {
    577:     MatRestoreColumnIJ_SeqBAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);
    578:     MatRestoreColumnIJ_SeqBAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);
    579:     PetscMalloc1(bs*mat->rmap->n,&c->dy);
    580:   } else {
    581:     MatRestoreColumnIJ_SeqAIJ_Color(A,0,PETSC_FALSE,PETSC_FALSE,&ncols,&A_ci,&A_cj,&spidxA,NULL);
    582:     MatRestoreColumnIJ_SeqAIJ_Color(B,0,PETSC_FALSE,PETSC_FALSE,&ncols,&B_ci,&B_cj,&spidxB,NULL);
    583:   }

    585:   ISColoringRestoreIS(iscoloring,&isa);
    586:   PetscFree2(rowhit,valaddrhit);

    588:   if (ctype == IS_COLORING_GHOSTED) {
    589:     ISLocalToGlobalMappingRestoreIndices(map,&ltog);
    590:   }
    591:   PetscInfo3(c,"ncolors %D, brows %D and bcols %D are used.\n",c->ncolors,c->brows,c->bcols);
    592:   return(0);
    593: }

    597: PetscErrorCode MatFDColoringCreate_MPIXAIJ(Mat mat,ISColoring iscoloring,MatFDColoring c)
    598: {
    600:   PetscInt       bs,nis=iscoloring->n,m=mat->rmap->n;
    601:   PetscBool      isBAIJ;

    604:   /* set default brows and bcols for speedup inserting the dense matrix into sparse Jacobian;
    605:    bcols is chosen s.t. dy-array takes 50% of memory space as mat */
    606:   MatGetBlockSize(mat,&bs);
    607:   PetscObjectTypeCompare((PetscObject)mat,MATMPIBAIJ,&isBAIJ);
    608:   if (isBAIJ || m == 0) {
    609:     c->brows = m;
    610:     c->bcols = 1;
    611:   } else { /* mpiaij matrix */
    612:     /* bcols is chosen s.t. dy-array takes 50% of local memory space as mat */
    613:     Mat_MPIAIJ *aij=(Mat_MPIAIJ*)mat->data;
    614:     Mat_SeqAIJ *spA,*spB;
    615:     Mat        A,B;
    616:     PetscInt   nz,brows,bcols;
    617:     PetscReal  mem;

    619:     bs    = 1; /* only bs=1 is supported for MPIAIJ matrix */

    621:     A = aij->A;  spA = (Mat_SeqAIJ*)A->data;
    622:     B = aij->B;  spB = (Mat_SeqAIJ*)B->data;
    623:     nz = spA->nz + spB->nz; /* total local nonzero entries of mat */
    624:     mem = nz*(sizeof(PetscScalar) + sizeof(PetscInt)) + 3*m*sizeof(PetscInt);
    625:     bcols = (PetscInt)(0.5*mem /(m*sizeof(PetscScalar)));
    626:     brows = 1000/bcols;
    627:     if (bcols > nis) bcols = nis;
    628:     if (brows == 0 || brows > m) brows = m;
    629:     c->brows = brows;
    630:     c->bcols = bcols;
    631:   }

    633:   c->M       = mat->rmap->N/bs;         /* set the global rows and columns and local rows */
    634:   c->N       = mat->cmap->N/bs;
    635:   c->m       = mat->rmap->n/bs;
    636:   c->rstart  = mat->rmap->rstart/bs;
    637:   c->ncolors = nis;
    638:   return(0);
    639: }