Date: 2016-07-24T16:53:47+00:00

Actual source code: mmaij.c
petsc-3.7.3 2016-07-24
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      2: /*
      3:    Support for the parallel AIJ matrix vector multiply
      4: */
      5: #include <../src/mat/impls/aij/mpi/mpiaij.h>
      6: #include <petsc/private/isimpl.h>    /* needed because accesses data structure of ISLocalToGlobalMapping directly */

     10: PetscErrorCode MatSetUpMultiply_MPIAIJ(Mat mat)
     11: {
     12:   Mat_MPIAIJ     *aij = (Mat_MPIAIJ*)mat->data;
     13:   Mat_SeqAIJ     *B   = (Mat_SeqAIJ*)(aij->B->data);
     15:   PetscInt       i,j,*aj = B->j,ec = 0,*garray;
     16:   IS             from,to;
     17:   Vec            gvec;
     18: #if defined(PETSC_USE_CTABLE)
     19:   PetscTable         gid1_lid1;
     20:   PetscTablePosition tpos;
     21:   PetscInt           gid,lid;
     22: #else
     23:   PetscInt N = mat->cmap->N,*indices;
     24: #endif

     27: #if defined(PETSC_USE_CTABLE)
     28:   /* use a table */
     29:   PetscTableCreate(aij->B->rmap->n,mat->cmap->N+1,&gid1_lid1);
     30:   for (i=0; i<aij->B->rmap->n; i++) {
     31:     for (j=0; j<B->ilen[i]; j++) {
     32:       PetscInt data,gid1 = aj[B->i[i] + j] + 1;
     33:       PetscTableFind(gid1_lid1,gid1,&data);
     34:       if (!data) {
     35:         /* one based table */
     36:         PetscTableAdd(gid1_lid1,gid1,++ec,INSERT_VALUES);
     37:       }
     38:     }
     39:   }
     40:   /* form array of columns we need */
     41:   PetscMalloc1(ec+1,&garray);
     42:   PetscTableGetHeadPosition(gid1_lid1,&tpos);
     43:   while (tpos) {
     44:     PetscTableGetNext(gid1_lid1,&tpos,&gid,&lid);
     45:     gid--;
     46:     lid--;
     47:     garray[lid] = gid;
     48:   }
     49:   PetscSortInt(ec,garray); /* sort, and rebuild */
     50:   PetscTableRemoveAll(gid1_lid1);
     51:   for (i=0; i<ec; i++) {
     52:     PetscTableAdd(gid1_lid1,garray[i]+1,i+1,INSERT_VALUES);
     53:   }
     54:   /* compact out the extra columns in B */
     55:   for (i=0; i<aij->B->rmap->n; i++) {
     56:     for (j=0; j<B->ilen[i]; j++) {
     57:       PetscInt gid1 = aj[B->i[i] + j] + 1;
     58:       PetscTableFind(gid1_lid1,gid1,&lid);
     59:       lid--;
     60:       aj[B->i[i] + j] = lid;
     61:     }
     62:   }
     63:   aij->B->cmap->n = aij->B->cmap->N = ec;
     64:   aij->B->cmap->bs = 1;

     66:   PetscLayoutSetUp((aij->B->cmap));
     67:   PetscTableDestroy(&gid1_lid1);
     68: #else
     69:   /* Make an array as long as the number of columns */
     70:   /* mark those columns that are in aij->B */
     71:   PetscCalloc1(N+1,&indices);
     72:   for (i=0; i<aij->B->rmap->n; i++) {
     73:     for (j=0; j<B->ilen[i]; j++) {
     74:       if (!indices[aj[B->i[i] + j]]) ec++;
     75:       indices[aj[B->i[i] + j]] = 1;
     76:     }
     77:   }

     79:   /* form array of columns we need */
     80:   PetscMalloc1(ec+1,&garray);
     81:   ec   = 0;
     82:   for (i=0; i<N; i++) {
     83:     if (indices[i]) garray[ec++] = i;
     84:   }

     86:   /* make indices now point into garray */
     87:   for (i=0; i<ec; i++) {
     88:     indices[garray[i]] = i;
     89:   }

     91:   /* compact out the extra columns in B */
     92:   for (i=0; i<aij->B->rmap->n; i++) {
     93:     for (j=0; j<B->ilen[i]; j++) {
     94:       aj[B->i[i] + j] = indices[aj[B->i[i] + j]];
     95:     }
     96:   }
     97:   aij->B->cmap->n = aij->B->cmap->N = ec;
     98:   aij->B->cmap->bs = 1;

    100:   PetscLayoutSetUp((aij->B->cmap));
    101:   PetscFree(indices);
    102: #endif
    103:   /* create local vector that is used to scatter into */
    104:   VecCreateSeq(PETSC_COMM_SELF,ec,&aij->lvec);

    106:   /* create two temporary Index sets for build scatter gather */
    107:   ISCreateGeneral(((PetscObject)mat)->comm,ec,garray,PETSC_COPY_VALUES,&from);

    109:   ISCreateStride(PETSC_COMM_SELF,ec,0,1,&to);

    111:   /* create temporary global vector to generate scatter context */
    112:   /* This does not allocate the array's memory so is efficient */
    113:   VecCreateMPIWithArray(PetscObjectComm((PetscObject)mat),1,mat->cmap->n,mat->cmap->N,NULL,&gvec);

    115:   /* generate the scatter context */
    116:   VecScatterCreate(gvec,from,aij->lvec,to,&aij->Mvctx);
    117:   PetscLogObjectParent((PetscObject)mat,(PetscObject)aij->Mvctx);
    118:   PetscLogObjectParent((PetscObject)mat,(PetscObject)aij->lvec);
    119:   PetscLogObjectParent((PetscObject)mat,(PetscObject)from);
    120:   PetscLogObjectParent((PetscObject)mat,(PetscObject)to);

    122:   aij->garray = garray;

    124:   PetscLogObjectMemory((PetscObject)mat,(ec+1)*sizeof(PetscInt));
    125:   ISDestroy(&from);
    126:   ISDestroy(&to);
    127:   VecDestroy(&gvec);
    128:   return(0);
    129: }

    134: /*
    135:      Takes the local part of an already assembled MPIAIJ matrix
    136:    and disassembles it. This is to allow new nonzeros into the matrix
    137:    that require more communication in the matrix vector multiply.
    138:    Thus certain data-structures must be rebuilt.

    140:    Kind of slow! But that's what application programmers get when
    141:    they are sloppy.
    142: */
    143: PetscErrorCode MatDisAssemble_MPIAIJ(Mat A)
    144: {
    145:   Mat_MPIAIJ     *aij  = (Mat_MPIAIJ*)A->data;
    146:   Mat            B     = aij->B,Bnew;
    147:   Mat_SeqAIJ     *Baij = (Mat_SeqAIJ*)B->data;
    149:   PetscInt       i,j,m = B->rmap->n,n = A->cmap->N,col,ct = 0,*garray = aij->garray,*nz,ec;
    150:   PetscScalar    v;

    153:   /* free stuff related to matrix-vec multiply */
    154:   VecGetSize(aij->lvec,&ec); /* needed for PetscLogObjectMemory below */
    155:   VecDestroy(&aij->lvec);
    156:   VecScatterDestroy(&aij->Mvctx);
    157:   if (aij->colmap) {
    158: #if defined(PETSC_USE_CTABLE)
    159:     PetscTableDestroy(&aij->colmap);
    160: #else
    161:     PetscFree(aij->colmap);
    162:     PetscLogObjectMemory((PetscObject)A,-aij->B->cmap->n*sizeof(PetscInt));
    163: #endif
    164:   }

    166:   /* make sure that B is assembled so we can access its values */
    167:   MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    168:   MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);

    170:   /* invent new B and copy stuff over */
    171:   PetscMalloc1(m+1,&nz);
    172:   for (i=0; i<m; i++) {
    173:     nz[i] = Baij->i[i+1] - Baij->i[i];
    174:   }
    175:   MatCreate(PETSC_COMM_SELF,&Bnew);
    176:   MatSetSizes(Bnew,m,n,m,n);
    177:   MatSetBlockSizesFromMats(Bnew,A,A);
    178:   MatSetType(Bnew,((PetscObject)B)->type_name);
    179:   MatSeqAIJSetPreallocation(Bnew,0,nz);

    181:   ((Mat_SeqAIJ*)Bnew->data)->nonew = Baij->nonew; /* Inherit insertion error options. */
    182:   /*
    183:    Ensure that B's nonzerostate is monotonically increasing.
    184:    Or should this follow the MatSetValues() loop to preserve B's nonzerstate across a MatDisAssemble() call?
    185:    */
    186:   Bnew->nonzerostate = B->nonzerostate;

    188:   PetscFree(nz);
    189:   for (i=0; i<m; i++) {
    190:     for (j=Baij->i[i]; j<Baij->i[i+1]; j++) {
    191:       col  = garray[Baij->j[ct]];
    192:       v    = Baij->a[ct++];
    193:       MatSetValues(Bnew,1,&i,1,&col,&v,B->insertmode);
    194:     }
    195:   }
    196:   PetscFree(aij->garray);
    197:   PetscLogObjectMemory((PetscObject)A,-ec*sizeof(PetscInt));
    198:   MatDestroy(&B);
    199:   PetscLogObjectParent((PetscObject)A,(PetscObject)Bnew);

    201:   aij->B           = Bnew;
    202:   A->was_assembled = PETSC_FALSE;
    203:   return(0);
    204: }

    206: /*      ugly stuff added for Glenn someday we should fix this up */

    208: static PetscInt *auglyrmapd = 0,*auglyrmapo = 0; /* mapping from the local ordering to the "diagonal" and "off-diagonal" parts of the local matrix */
    209: static Vec auglydd          = 0,auglyoo     = 0; /* work vectors used to scale the two parts of the local matrix */

    214: PetscErrorCode MatMPIAIJDiagonalScaleLocalSetUp(Mat inA,Vec scale)
    215: {
    216:   Mat_MPIAIJ     *ina = (Mat_MPIAIJ*) inA->data; /*access private part of matrix */
    218:   PetscInt       i,n,nt,cstart,cend,no,*garray = ina->garray,*lindices;
    219:   PetscInt       *r_rmapd,*r_rmapo;

    222:   MatGetOwnershipRange(inA,&cstart,&cend);
    223:   MatGetSize(ina->A,NULL,&n);
    224:   PetscCalloc1(inA->rmap->mapping->n+1,&r_rmapd);
    225:   nt   = 0;
    226:   for (i=0; i<inA->rmap->mapping->n; i++) {
    227:     if (inA->rmap->mapping->indices[i] >= cstart && inA->rmap->mapping->indices[i] < cend) {
    228:       nt++;
    229:       r_rmapd[i] = inA->rmap->mapping->indices[i] + 1;
    230:     }
    231:   }
    232:   if (nt != n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Hmm nt %D n %D",nt,n);
    233:   PetscMalloc1(n+1,&auglyrmapd);
    234:   for (i=0; i<inA->rmap->mapping->n; i++) {
    235:     if (r_rmapd[i]) {
    236:       auglyrmapd[(r_rmapd[i]-1)-cstart] = i;
    237:     }
    238:   }
    239:   PetscFree(r_rmapd);
    240:   VecCreateSeq(PETSC_COMM_SELF,n,&auglydd);

    242:   PetscCalloc1(inA->cmap->N+1,&lindices);
    243:   for (i=0; i<ina->B->cmap->n; i++) {
    244:     lindices[garray[i]] = i+1;
    245:   }
    246:   no   = inA->rmap->mapping->n - nt;
    247:   PetscCalloc1(inA->rmap->mapping->n+1,&r_rmapo);
    248:   nt   = 0;
    249:   for (i=0; i<inA->rmap->mapping->n; i++) {
    250:     if (lindices[inA->rmap->mapping->indices[i]]) {
    251:       nt++;
    252:       r_rmapo[i] = lindices[inA->rmap->mapping->indices[i]];
    253:     }
    254:   }
    255:   if (nt > no) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_PLIB,"Hmm nt %D no %D",nt,n);
    256:   PetscFree(lindices);
    257:   PetscMalloc1(nt+1,&auglyrmapo);
    258:   for (i=0; i<inA->rmap->mapping->n; i++) {
    259:     if (r_rmapo[i]) {
    260:       auglyrmapo[(r_rmapo[i]-1)] = i;
    261:     }
    262:   }
    263:   PetscFree(r_rmapo);
    264:   VecCreateSeq(PETSC_COMM_SELF,nt,&auglyoo);
    265:   return(0);
    266: }

    270: PetscErrorCode MatMPIAIJDiagonalScaleLocal(Mat A,Vec scale)
    271: {
    272:   /* This routine should really be abandoned as it duplicates MatDiagonalScaleLocal */

    276:   PetscTryMethod(A,"MatDiagonalScaleLocal_C",(Mat,Vec),(A,scale));
    277:   return(0);
    278: }

    282: PetscErrorCode  MatDiagonalScaleLocal_MPIAIJ(Mat A,Vec scale)
    283: {
    284:   Mat_MPIAIJ     *a = (Mat_MPIAIJ*) A->data; /*access private part of matrix */
    286:   PetscInt       n,i;
    287:   PetscScalar    *d,*o,*s;

    290:   if (!auglyrmapd) {
    291:     MatMPIAIJDiagonalScaleLocalSetUp(A,scale);
    292:   }

    294:   VecGetArray(scale,&s);

    296:   VecGetLocalSize(auglydd,&n);
    297:   VecGetArray(auglydd,&d);
    298:   for (i=0; i<n; i++) {
    299:     d[i] = s[auglyrmapd[i]]; /* copy "diagonal" (true local) portion of scale into dd vector */
    300:   }
    301:   VecRestoreArray(auglydd,&d);
    302:   /* column scale "diagonal" portion of local matrix */
    303:   MatDiagonalScale(a->A,NULL,auglydd);

    305:   VecGetLocalSize(auglyoo,&n);
    306:   VecGetArray(auglyoo,&o);
    307:   for (i=0; i<n; i++) {
    308:     o[i] = s[auglyrmapo[i]]; /* copy "off-diagonal" portion of scale into oo vector */
    309:   }
    310:   VecRestoreArray(scale,&s);
    311:   VecRestoreArray(auglyoo,&o);
    312:   /* column scale "off-diagonal" portion of local matrix */
    313:   MatDiagonalScale(a->B,NULL,auglyoo);
    314:   return(0);
    315: }