Actual source code: mpisell.c
petsc-3.10.5 2019-03-28
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      1:  #include <../src/mat/impls/aij/mpi/mpiaij.h>
      2:  #include <../src/mat/impls/sell/mpi/mpisell.h>
      3:  #include <petsc/private/vecimpl.h>
      4:  #include <petsc/private/isimpl.h>
      5:  #include <petscblaslapack.h>
      6:  #include <petscsf.h>

      8: /*MC
      9:    MATSELL - MATSELL = "sell" - A matrix type to be used for sparse matrices.

     11:    This matrix type is identical to MATSEQSELL when constructed with a single process communicator,
     12:    and MATMPISELL otherwise.  As a result, for single process communicators,
     13:   MatSeqSELLSetPreallocation is supported, and similarly MatMPISELLSetPreallocation is supported
     14:   for communicators controlling multiple processes.  It is recommended that you call both of
     15:   the above preallocation routines for simplicity.

     17:    Options Database Keys:
     18: . -mat_type sell - sets the matrix type to "sell" during a call to MatSetFromOptions()

     20:   Developer Notes:
     21:     Subclasses include MATSELLCUSP, MATSELLCUSPARSE, MATSELLPERM, MATSELLCRL, and also automatically switches over to use inodes when
     22:    enough exist.

     24:   Level: beginner

     26: .seealso: MatCreateSELL(), MatCreateSeqSELL(), MATSEQSELL, MATMPISELL
     27: M*/

     29: PetscErrorCode MatDiagonalSet_MPISELL(Mat Y,Vec D,InsertMode is)
     30: {
     32:   Mat_MPISELL    *sell=(Mat_MPISELL*)Y->data;

     35:   if (Y->assembled && Y->rmap->rstart == Y->cmap->rstart && Y->rmap->rend == Y->cmap->rend) {
     36:     MatDiagonalSet(sell->A,D,is);
     37:   } else {
     38:     MatDiagonalSet_Default(Y,D,is);
     39:   }
     40:   return(0);
     41: }

     43: /*
     44:   Local utility routine that creates a mapping from the global column
     45: number to the local number in the off-diagonal part of the local
     46: storage of the matrix.  When PETSC_USE_CTABLE is used this is scalable at
     47: a slightly higher hash table cost; without it it is not scalable (each processor
     48: has an order N integer array but is fast to acess.
     49: */
     50: PetscErrorCode MatCreateColmap_MPISELL_Private(Mat mat)
     51: {
     52:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
     54:   PetscInt       n=sell->B->cmap->n,i;

     57:   if (!sell->garray) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_PLIB,"MPISELL Matrix was assembled but is missing garray");
     58: #if defined(PETSC_USE_CTABLE)
     59:   PetscTableCreate(n,mat->cmap->N+1,&sell->colmap);
     60:   for (i=0; i<n; i++) {
     61:     PetscTableAdd(sell->colmap,sell->garray[i]+1,i+1,INSERT_VALUES);
     62:   }
     63: #else
     64:   PetscCalloc1(mat->cmap->N+1,&sell->colmap);
     65:   PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N+1)*sizeof(PetscInt));
     66:   for (i=0; i<n; i++) sell->colmap[sell->garray[i]] = i+1;
     67: #endif
     68:   return(0);
     69: }

     71: #define MatSetValues_SeqSELL_A_Private(row,col,value,addv,orow,ocol) \
     72:   { \
     73:     if (col <= lastcol1) low1 = 0; \
     74:     else                high1 = nrow1; \
     75:     lastcol1 = col; \
     76:     while (high1-low1 > 5) { \
     77:       t = (low1+high1)/2; \
     78:       if (*(cp1+8*t) > col) high1 = t; \
     79:       else                   low1 = t; \
     80:     } \
     81:     for (_i=low1; _i<high1; _i++) { \
     82:       if (*(cp1+8*_i) > col) break; \
     83:       if (*(cp1+8*_i) == col) { \
     84:         if (addv == ADD_VALUES) *(vp1+8*_i) += value;   \
     85:         else                     *(vp1+8*_i) = value; \
     86:         goto a_noinsert; \
     87:       } \
     88:     }  \
     89:     if (value == 0.0 && ignorezeroentries) {low1 = 0; high1 = nrow1;goto a_noinsert;} \
     90:     if (nonew == 1) {low1 = 0; high1 = nrow1; goto a_noinsert;} \
     91:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
     92:     MatSeqXSELLReallocateSELL(A,am,1,nrow1,a->sliidx,row/8,row,col,a->colidx,a->val,cp1,vp1,nonew,MatScalar); \
     93:     /* shift up all the later entries in this row */ \
     94:     for (ii=nrow1-1; ii>=_i; ii--) { \
     95:       *(cp1+8*(ii+1)) = *(cp1+8*ii); \
     96:       *(vp1+8*(ii+1)) = *(vp1+8*ii); \
     97:     } \
     98:     *(cp1+8*_i) = col; \
     99:     *(vp1+8*_i) = value; \
    100:     a->nz++; nrow1++; A->nonzerostate++; \
    101:     a_noinsert: ; \
    102:     a->rlen[row] = nrow1; \
    103:   }

    105: #define MatSetValues_SeqSELL_B_Private(row,col,value,addv,orow,ocol) \
    106:   { \
    107:     if (col <= lastcol2) low2 = 0; \
    108:     else                high2 = nrow2; \
    109:     lastcol2 = col; \
    110:     while (high2-low2 > 5) { \
    111:       t = (low2+high2)/2; \
    112:       if (*(cp2+8*t) > col) high2 = t; \
    113:       else low2  = t; \
    114:     } \
    115:     for (_i=low2; _i<high2; _i++) { \
    116:       if (*(cp2+8*_i) > col) break; \
    117:       if (*(cp2+8*_i) == col) { \
    118:         if (addv == ADD_VALUES) *(vp2+8*_i) += value; \
    119:         else                     *(vp2+8*_i) = value; \
    120:         goto b_noinsert; \
    121:       } \
    122:     } \
    123:     if (value == 0.0 && ignorezeroentries) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
    124:     if (nonew == 1) {low2 = 0; high2 = nrow2; goto b_noinsert;} \
    125:     if (nonew == -1) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", orow, ocol); \
    126:     MatSeqXSELLReallocateSELL(B,bm,1,nrow2,b->sliidx,row/8,row,col,b->colidx,b->val,cp2,vp2,nonew,MatScalar); \
    127:     /* shift up all the later entries in this row */ \
    128:     for (ii=nrow2-1; ii>=_i; ii--) { \
    129:       *(cp2+8*(ii+1)) = *(cp2+8*ii); \
    130:       *(vp2+8*(ii+1)) = *(vp2+8*ii); \
    131:     } \
    132:     *(cp2+8*_i) = col; \
    133:     *(vp2+8*_i) = value; \
    134:     b->nz++; nrow2++; B->nonzerostate++; \
    135:     b_noinsert: ; \
    136:     b->rlen[row] = nrow2; \
    137:   }

    139: PetscErrorCode MatSetValues_MPISELL(Mat mat,PetscInt m,const PetscInt im[],PetscInt n,const PetscInt in[],const PetscScalar v[],InsertMode addv)
    140: {
    141:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
    142:   PetscScalar    value;
    144:   PetscInt       i,j,rstart=mat->rmap->rstart,rend=mat->rmap->rend,shift1,shift2;
    145:   PetscInt       cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,col;
    146:   PetscBool      roworiented=sell->roworiented;

    148:   /* Some Variables required in the macro */
    149:   Mat            A=sell->A;
    150:   Mat_SeqSELL    *a=(Mat_SeqSELL*)A->data;
    151:   PetscBool      ignorezeroentries=a->ignorezeroentries,found;
    152:   Mat            B=sell->B;
    153:   Mat_SeqSELL    *b=(Mat_SeqSELL*)B->data;
    154:   PetscInt       *cp1,*cp2,ii,_i,nrow1,nrow2,low1,high1,low2,high2,t,lastcol1,lastcol2;
    155:   MatScalar      *vp1,*vp2;

    158:   for (i=0; i<m; i++) {
    159:     if (im[i] < 0) continue;
    160: #if defined(PETSC_USE_DEBUG)
    161:     if (im[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",im[i],mat->rmap->N-1);
    162: #endif
    163:     if (im[i] >= rstart && im[i] < rend) {
    164:       row      = im[i] - rstart;
    165:       lastcol1 = -1;
    166:       shift1   = a->sliidx[row>>3]+(row&0x07); /* starting index of the row */
    167:       cp1      = a->colidx+shift1;
    168:       vp1      = a->val+shift1;
    169:       nrow1    = a->rlen[row];
    170:       low1     = 0;
    171:       high1    = nrow1;
    172:       lastcol2 = -1;
    173:       shift2   = b->sliidx[row>>3]+(row&0x07); /* starting index of the row */
    174:       cp2      = b->colidx+shift2;
    175:       vp2      = b->val+shift2;
    176:       nrow2    = b->rlen[row];
    177:       low2     = 0;
    178:       high2    = nrow2;

    180:       for (j=0; j<n; j++) {
    181:         if (roworiented) value = v[i*n+j];
    182:         else             value = v[i+j*m];
    183:         if (ignorezeroentries && value == 0.0 && (addv == ADD_VALUES)) continue;
    184:         if (in[j] >= cstart && in[j] < cend) {
    185:           col   = in[j] - cstart;
    186:           MatSetValue_SeqSELL_Private(A,row,col,value,addv,im[i],in[j],cp1,vp1,lastcol1,low1,high1); /* set one value */
    187:         } else if (in[j] < 0) continue;
    188: #if defined(PETSC_USE_DEBUG)
    189:         else if (in[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",in[j],mat->cmap->N-1);
    190: #endif
    191:         else {
    192:           if (mat->was_assembled) {
    193:             if (!sell->colmap) {
    194:               MatCreateColmap_MPISELL_Private(mat);
    195:             }
    196: #if defined(PETSC_USE_CTABLE)
    197:             PetscTableFind(sell->colmap,in[j]+1,&col);
    198:             col--;
    199: #else
    200:             col = sell->colmap[in[j]] - 1;
    201: #endif
    202:             if (col < 0 && !((Mat_SeqSELL*)(sell->B->data))->nonew) {
    203:               MatDisAssemble_MPISELL(mat);
    204:               col    = in[j];
    205:               /* Reinitialize the variables required by MatSetValues_SeqSELL_B_Private() */
    206:               B      = sell->B;
    207:               b      = (Mat_SeqSELL*)B->data;
    208:               shift2 = b->sliidx[row>>3]+(row&0x07); /* starting index of the row */
    209:               cp2    = b->colidx+shift2;
    210:               vp2    = b->val+shift2;
    211:               nrow2  = b->rlen[row];
    212:               low2   = 0;
    213:               high2  = nrow2;
    214:             } else if (col < 0) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Inserting a new nonzero at global row/column (%D, %D) into matrix", im[i], in[j]);
    215:           } else col = in[j];
    216:           MatSetValue_SeqSELL_Private(B,row,col,value,addv,im[i],in[j],cp2,vp2,lastcol2,low2,high2); /* set one value */
    217:         }
    218:       }
    219:     } else {
    220:       if (mat->nooffprocentries) SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_WRONG,"Setting off process row %D even though MatSetOption(,MAT_NO_OFF_PROC_ENTRIES,PETSC_TRUE) was set",im[i]);
    221:       if (!sell->donotstash) {
    222:         mat->assembled = PETSC_FALSE;
    223:         if (roworiented) {
    224:           MatStashValuesRow_Private(&mat->stash,im[i],n,in,v+i*n,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
    225:         } else {
    226:           MatStashValuesCol_Private(&mat->stash,im[i],n,in,v+i,m,(PetscBool)(ignorezeroentries && (addv == ADD_VALUES)));
    227:         }
    228:       }
    229:     }
    230:   }
    231:   return(0);
    232: }

    234: PetscErrorCode MatGetValues_MPISELL(Mat mat,PetscInt m,const PetscInt idxm[],PetscInt n,const PetscInt idxn[],PetscScalar v[])
    235: {
    236:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
    238:   PetscInt       i,j,rstart=mat->rmap->rstart,rend=mat->rmap->rend;
    239:   PetscInt       cstart=mat->cmap->rstart,cend=mat->cmap->rend,row,col;

    242:   for (i=0; i<m; i++) {
    243:     if (idxm[i] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative row: %D",idxm[i]);*/
    244:     if (idxm[i] >= mat->rmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Row too large: row %D max %D",idxm[i],mat->rmap->N-1);
    245:     if (idxm[i] >= rstart && idxm[i] < rend) {
    246:       row = idxm[i] - rstart;
    247:       for (j=0; j<n; j++) {
    248:         if (idxn[j] < 0) continue; /* SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Negative column: %D",idxn[j]); */
    249:         if (idxn[j] >= mat->cmap->N) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_OUTOFRANGE,"Column too large: col %D max %D",idxn[j],mat->cmap->N-1);
    250:         if (idxn[j] >= cstart && idxn[j] < cend) {
    251:           col  = idxn[j] - cstart;
    252:           MatGetValues(sell->A,1,&row,1,&col,v+i*n+j);
    253:         } else {
    254:           if (!sell->colmap) {
    255:             MatCreateColmap_MPISELL_Private(mat);
    256:           }
    257: #if defined(PETSC_USE_CTABLE)
    258:           PetscTableFind(sell->colmap,idxn[j]+1,&col);
    259:           col--;
    260: #else
    261:           col = sell->colmap[idxn[j]] - 1;
    262: #endif
    263:           if ((col < 0) || (sell->garray[col] != idxn[j])) *(v+i*n+j) = 0.0;
    264:           else {
    265:             MatGetValues(sell->B,1,&row,1,&col,v+i*n+j);
    266:           }
    267:         }
    268:       }
    269:     } else SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only local values currently supported");
    270:   }
    271:   return(0);
    272: }

    274: extern PetscErrorCode MatMultDiagonalBlock_MPISELL(Mat,Vec,Vec);

    276: PetscErrorCode MatAssemblyBegin_MPISELL(Mat mat,MatAssemblyType mode)
    277: {
    278:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
    280:   PetscInt       nstash,reallocs;

    283:   if (sell->donotstash || mat->nooffprocentries) return(0);

    285:   MatStashScatterBegin_Private(mat,&mat->stash,mat->rmap->range);
    286:   MatStashGetInfo_Private(&mat->stash,&nstash,&reallocs);
    287:   PetscInfo2(sell->A,"Stash has %D entries, uses %D mallocs.\n",nstash,reallocs);
    288:   return(0);
    289: }

    291: PetscErrorCode MatAssemblyEnd_MPISELL(Mat mat,MatAssemblyType mode)
    292: {
    293:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
    295:   PetscMPIInt    n;
    296:   PetscInt       i,flg;
    297:   PetscInt       *row,*col;
    298:   PetscScalar    *val;
    299:   PetscBool      other_disassembled;
    300:   /* do not use 'b = (Mat_SeqSELL*)sell->B->data' as B can be reset in disassembly */
    302:   if (!sell->donotstash && !mat->nooffprocentries) {
    303:     while (1) {
    304:       MatStashScatterGetMesg_Private(&mat->stash,&n,&row,&col,&val,&flg);
    305:       if (!flg) break;

    307:       for (i=0; i<n; i++) { /* assemble one by one */
    308:         MatSetValues_MPISELL(mat,1,row+i,1,col+i,val+i,mat->insertmode);
    309:       }
    310:     }
    311:     MatStashScatterEnd_Private(&mat->stash);
    312:   }
    313:   MatAssemblyBegin(sell->A,mode);
    314:   MatAssemblyEnd(sell->A,mode);

    316:   /*
    317:      determine if any processor has disassembled, if so we must
    318:      also disassemble ourselfs, in order that we may reassemble.
    319:   */
    320:   /*
    321:      if nonzero structure of submatrix B cannot change then we know that
    322:      no processor disassembled thus we can skip this stuff
    323:   */
    324:   if (!((Mat_SeqSELL*)sell->B->data)->nonew) {
    325:     MPIU_Allreduce(&mat->was_assembled,&other_disassembled,1,MPIU_BOOL,MPI_PROD,PetscObjectComm((PetscObject)mat));
    326:     if (mat->was_assembled && !other_disassembled) {
    327:       SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"MatDisAssemble not implemented yet\n");
    328:       MatDisAssemble_MPISELL(mat);
    329:     }
    330:   }
    331:   if (!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) {
    332:     MatSetUpMultiply_MPISELL(mat);
    333:   }
    334:   /*
    335:   MatSetOption(sell->B,MAT_USE_INODES,PETSC_FALSE);
    336:   */
    337:   MatAssemblyBegin(sell->B,mode);
    338:   MatAssemblyEnd(sell->B,mode);
    339:   PetscFree2(sell->rowvalues,sell->rowindices);
    340:   sell->rowvalues = 0;
    341:   VecDestroy(&sell->diag);

    343:   /* if no new nonzero locations are allowed in matrix then only set the matrix state the first time through */
    344:   if ((!mat->was_assembled && mode == MAT_FINAL_ASSEMBLY) || !((Mat_SeqSELL*)(sell->A->data))->nonew) {
    345:     PetscObjectState state = sell->A->nonzerostate + sell->B->nonzerostate;
    346:     MPIU_Allreduce(&state,&mat->nonzerostate,1,MPIU_INT64,MPI_SUM,PetscObjectComm((PetscObject)mat));
    347:   }
    348:   return(0);
    349: }

    351: PetscErrorCode MatZeroEntries_MPISELL(Mat A)
    352: {
    353:   Mat_MPISELL    *l=(Mat_MPISELL*)A->data;

    357:   MatZeroEntries(l->A);
    358:   MatZeroEntries(l->B);
    359:   return(0);
    360: }

    362: PetscErrorCode MatMult_MPISELL(Mat A,Vec xx,Vec yy)
    363: {
    364:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
    366:   PetscInt       nt;

    369:   VecGetLocalSize(xx,&nt);
    370:   if (nt != A->cmap->n) SETERRQ2(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"Incompatible partition of A (%D) and xx (%D)",A->cmap->n,nt);
    371:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    372:   (*a->A->ops->mult)(a->A,xx,yy);
    373:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    374:   (*a->B->ops->multadd)(a->B,a->lvec,yy,yy);
    375:   return(0);
    376: }

    378: PetscErrorCode MatMultDiagonalBlock_MPISELL(Mat A,Vec bb,Vec xx)
    379: {
    380:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    384:   MatMultDiagonalBlock(a->A,bb,xx);
    385:   return(0);
    386: }

    388: PetscErrorCode MatMultAdd_MPISELL(Mat A,Vec xx,Vec yy,Vec zz)
    389: {
    390:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    394:   VecScatterBegin(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    395:   (*a->A->ops->multadd)(a->A,xx,yy,zz);
    396:   VecScatterEnd(a->Mvctx,xx,a->lvec,INSERT_VALUES,SCATTER_FORWARD);
    397:   (*a->B->ops->multadd)(a->B,a->lvec,zz,zz);
    398:   return(0);
    399: }

    401: PetscErrorCode MatMultTranspose_MPISELL(Mat A,Vec xx,Vec yy)
    402: {
    403:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
    405:   PetscBool      merged;

    408:   VecScatterGetMerged(a->Mvctx,&merged);
    409:   /* do nondiagonal part */
    410:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    411:   if (!merged) {
    412:     /* send it on its way */
    413:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    414:     /* do local part */
    415:     (*a->A->ops->multtranspose)(a->A,xx,yy);
    416:     /* receive remote parts: note this assumes the values are not actually */
    417:     /* added in yy until the next line, */
    418:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    419:   } else {
    420:     /* do local part */
    421:     (*a->A->ops->multtranspose)(a->A,xx,yy);
    422:     /* send it on its way */
    423:     VecScatterBegin(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    424:     /* values actually were received in the Begin() but we need to call this nop */
    425:     VecScatterEnd(a->Mvctx,a->lvec,yy,ADD_VALUES,SCATTER_REVERSE);
    426:   }
    427:   return(0);
    428: }

    430: PetscErrorCode MatIsTranspose_MPISELL(Mat Amat,Mat Bmat,PetscReal tol,PetscBool *f)
    431: {
    432:   MPI_Comm       comm;
    433:   Mat_MPISELL    *Asell=(Mat_MPISELL*)Amat->data,*Bsell;
    434:   Mat            Adia=Asell->A,Bdia,Aoff,Boff,*Aoffs,*Boffs;
    435:   IS             Me,Notme;
    437:   PetscInt       M,N,first,last,*notme,i;
    438:   PetscMPIInt    size;

    441:   /* Easy test: symmetric diagonal block */
    442:   Bsell = (Mat_MPISELL*)Bmat->data; Bdia = Bsell->A;
    443:   MatIsTranspose(Adia,Bdia,tol,f);
    444:   if (!*f) return(0);
    445:   PetscObjectGetComm((PetscObject)Amat,&comm);
    446:   MPI_Comm_size(comm,&size);
    447:   if (size == 1) return(0);

    449:   /* Hard test: off-diagonal block. This takes a MatCreateSubMatrix. */
    450:   MatGetSize(Amat,&M,&N);
    451:   MatGetOwnershipRange(Amat,&first,&last);
    452:   PetscMalloc1(N-last+first,&notme);
    453:   for (i=0; i<first; i++) notme[i] = i;
    454:   for (i=last; i<M; i++) notme[i-last+first] = i;
    455:   ISCreateGeneral(MPI_COMM_SELF,N-last+first,notme,PETSC_COPY_VALUES,&Notme);
    456:   ISCreateStride(MPI_COMM_SELF,last-first,first,1,&Me);
    457:   MatCreateSubMatrices(Amat,1,&Me,&Notme,MAT_INITIAL_MATRIX,&Aoffs);
    458:   Aoff = Aoffs[0];
    459:   MatCreateSubMatrices(Bmat,1,&Notme,&Me,MAT_INITIAL_MATRIX,&Boffs);
    460:   Boff = Boffs[0];
    461:   MatIsTranspose(Aoff,Boff,tol,f);
    462:   MatDestroyMatrices(1,&Aoffs);
    463:   MatDestroyMatrices(1,&Boffs);
    464:   ISDestroy(&Me);
    465:   ISDestroy(&Notme);
    466:   PetscFree(notme);
    467:   return(0);
    468: }

    470: PetscErrorCode MatMultTransposeAdd_MPISELL(Mat A,Vec xx,Vec yy,Vec zz)
    471: {
    472:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    476:   /* do nondiagonal part */
    477:   (*a->B->ops->multtranspose)(a->B,xx,a->lvec);
    478:   /* send it on its way */
    479:   VecScatterBegin(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    480:   /* do local part */
    481:   (*a->A->ops->multtransposeadd)(a->A,xx,yy,zz);
    482:   /* receive remote parts */
    483:   VecScatterEnd(a->Mvctx,a->lvec,zz,ADD_VALUES,SCATTER_REVERSE);
    484:   return(0);
    485: }

    487: /*
    488:   This only works correctly for square matrices where the subblock A->A is the
    489:    diagonal block
    490: */
    491: PetscErrorCode MatGetDiagonal_MPISELL(Mat A,Vec v)
    492: {
    494:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    497:   if (A->rmap->N != A->cmap->N) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Supports only square matrix where A->A is diag block");
    498:   if (A->rmap->rstart != A->cmap->rstart || A->rmap->rend != A->cmap->rend) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"row partition must equal col partition");
    499:   MatGetDiagonal(a->A,v);
    500:   return(0);
    501: }

    503: PetscErrorCode MatScale_MPISELL(Mat A,PetscScalar aa)
    504: {
    505:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    509:   MatScale(a->A,aa);
    510:   MatScale(a->B,aa);
    511:   return(0);
    512: }

    514: PetscErrorCode MatDestroy_MPISELL(Mat mat)
    515: {
    516:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

    520: #if defined(PETSC_USE_LOG)
    521:   PetscLogObjectState((PetscObject)mat,"Rows=%D, Cols=%D",mat->rmap->N,mat->cmap->N);
    522: #endif
    523:   MatStashDestroy_Private(&mat->stash);
    524:   VecDestroy(&sell->diag);
    525:   MatDestroy(&sell->A);
    526:   MatDestroy(&sell->B);
    527: #if defined(PETSC_USE_CTABLE)
    528:   PetscTableDestroy(&sell->colmap);
    529: #else
    530:   PetscFree(sell->colmap);
    531: #endif
    532:   PetscFree(sell->garray);
    533:   VecDestroy(&sell->lvec);
    534:   VecScatterDestroy(&sell->Mvctx);
    535:   PetscFree2(sell->rowvalues,sell->rowindices);
    536:   PetscFree(sell->ld);
    537:   PetscFree(mat->data);

    539:   PetscObjectChangeTypeName((PetscObject)mat,0);
    540:   PetscObjectComposeFunction((PetscObject)mat,"MatStoreValues_C",NULL);
    541:   PetscObjectComposeFunction((PetscObject)mat,"MatRetrieveValues_C",NULL);
    542:   PetscObjectComposeFunction((PetscObject)mat,"MatIsTranspose_C",NULL);
    543:   PetscObjectComposeFunction((PetscObject)mat,"MatMPISELLSetPreallocation_C",NULL);
    544:   PetscObjectComposeFunction((PetscObject)mat,"MatConvert_mpisell_mpiaij_C",NULL);
    545:   PetscObjectComposeFunction((PetscObject)mat,"MatDiagonalScaleLocal_C",NULL);
    546:   return(0);
    547: }

    549:  #include <petscdraw.h>
    550: PetscErrorCode MatView_MPISELL_ASCIIorDraworSocket(Mat mat,PetscViewer viewer)
    551: {
    552:   Mat_MPISELL       *sell=(Mat_MPISELL*)mat->data;
    553:   PetscErrorCode    ierr;
    554:   PetscMPIInt       rank=sell->rank,size=sell->size;
    555:   PetscBool         isdraw,iascii,isbinary;
    556:   PetscViewer       sviewer;
    557:   PetscViewerFormat format;

    560:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    561:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    562:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    563:   if (iascii) {
    564:     PetscViewerGetFormat(viewer,&format);
    565:     if (format == PETSC_VIEWER_ASCII_INFO_DETAIL) {
    566:       MatInfo   info;
    567:       PetscBool inodes;

    569:       MPI_Comm_rank(PetscObjectComm((PetscObject)mat),&rank);
    570:       MatGetInfo(mat,MAT_LOCAL,&info);
    571:       MatInodeGetInodeSizes(sell->A,NULL,(PetscInt**)&inodes,NULL);
    572:       PetscViewerASCIIPushSynchronized(viewer);
    573:       if (!inodes) {
    574:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, not using I-node routines\n",
    575:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
    576:       } else {
    577:         PetscViewerASCIISynchronizedPrintf(viewer,"[%d] Local rows %D nz %D nz alloced %D mem %D, using I-node routines\n",
    578:                                                   rank,mat->rmap->n,(PetscInt)info.nz_used,(PetscInt)info.nz_allocated,(PetscInt)info.memory);
    579:       }
    580:       MatGetInfo(sell->A,MAT_LOCAL,&info);
    581:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] on-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    582:       MatGetInfo(sell->B,MAT_LOCAL,&info);
    583:       PetscViewerASCIISynchronizedPrintf(viewer,"[%d] off-diagonal part: nz %D \n",rank,(PetscInt)info.nz_used);
    584:       PetscViewerFlush(viewer);
    585:       PetscViewerASCIIPopSynchronized(viewer);
    586:       PetscViewerASCIIPrintf(viewer,"Information on VecScatter used in matrix-vector product: \n");
    587:       VecScatterView(sell->Mvctx,viewer);
    588:       return(0);
    589:     } else if (format == PETSC_VIEWER_ASCII_INFO) {
    590:       PetscInt inodecount,inodelimit,*inodes;
    591:       MatInodeGetInodeSizes(sell->A,&inodecount,&inodes,&inodelimit);
    592:       if (inodes) {
    593:         PetscViewerASCIIPrintf(viewer,"using I-node (on process 0) routines: found %D nodes, limit used is %D\n",inodecount,inodelimit);
    594:       } else {
    595:         PetscViewerASCIIPrintf(viewer,"not using I-node (on process 0) routines\n");
    596:       }
    597:       return(0);
    598:     } else if (format == PETSC_VIEWER_ASCII_FACTOR_INFO) {
    599:       return(0);
    600:     }
    601:   } else if (isbinary) {
    602:     if (size == 1) {
    603:       PetscObjectSetName((PetscObject)sell->A,((PetscObject)mat)->name);
    604:       MatView(sell->A,viewer);
    605:     } else {
    606:       /* MatView_MPISELL_Binary(mat,viewer); */
    607:     }
    608:     return(0);
    609:   } else if (isdraw) {
    610:     PetscDraw draw;
    611:     PetscBool isnull;
    612:     PetscViewerDrawGetDraw(viewer,0,&draw);
    613:     PetscDrawIsNull(draw,&isnull);
    614:     if (isnull) return(0);
    615:   }

    617:   {
    618:     /* assemble the entire matrix onto first processor. */
    619:     Mat         A;
    620:     Mat_SeqSELL *Aloc;
    621:     PetscInt    M=mat->rmap->N,N=mat->cmap->N,*acolidx,row,col,i,j;
    622:     MatScalar   *aval;
    623:     PetscBool   isnonzero;

    625:     MatCreate(PetscObjectComm((PetscObject)mat),&A);
    626:     if (!rank) {
    627:       MatSetSizes(A,M,N,M,N);
    628:     } else {
    629:       MatSetSizes(A,0,0,M,N);
    630:     }
    631:     /* This is just a temporary matrix, so explicitly using MATMPISELL is probably best */
    632:     MatSetType(A,MATMPISELL);
    633:     MatMPISELLSetPreallocation(A,0,NULL,0,NULL);
    634:     MatSetOption(A,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_FALSE);
    635:     PetscLogObjectParent((PetscObject)mat,(PetscObject)A);

    637:     /* copy over the A part */
    638:     Aloc = (Mat_SeqSELL*)sell->A->data;
    639:     acolidx = Aloc->colidx; aval = Aloc->val;
    640:     for (i=0; i<Aloc->totalslices; i++) { /* loop over slices */
    641:       for (j=Aloc->sliidx[i]; j<Aloc->sliidx[i+1]; j++) {
    642:         isnonzero = (PetscBool)((j-Aloc->sliidx[i])/8 < Aloc->rlen[(i<<3)+(j&0x07)]);
    643:         if (isnonzero) { /* check the mask bit */
    644:           row  = (i<<3)+(j&0x07) + mat->rmap->rstart; /* i<<3 is the starting row of this slice */
    645:           col  = *acolidx + mat->rmap->rstart;
    646:           MatSetValues(A,1,&row,1,&col,aval,INSERT_VALUES);
    647:         }
    648:         aval++; acolidx++;
    649:       }
    650:     }

    652:     /* copy over the B part */
    653:     Aloc = (Mat_SeqSELL*)sell->B->data;
    654:     acolidx = Aloc->colidx; aval = Aloc->val;
    655:     for (i=0; i<Aloc->totalslices; i++) {
    656:       for (j=Aloc->sliidx[i]; j<Aloc->sliidx[i+1]; j++) {
    657:         isnonzero = (PetscBool)((j-Aloc->sliidx[i])/8 < Aloc->rlen[(i<<3)+(j&0x07)]);
    658:         if (isnonzero) {
    659:           row  = (i<<3)+(j&0x07) + mat->rmap->rstart;
    660:           col  = sell->garray[*acolidx];
    661:           MatSetValues(A,1,&row,1,&col,aval,INSERT_VALUES);
    662:         }
    663:         aval++; acolidx++;
    664:       }
    665:     }

    667:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    668:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    669:     /*
    670:        Everyone has to call to draw the matrix since the graphics waits are
    671:        synchronized across all processors that share the PetscDraw object
    672:     */
    673:     PetscViewerGetSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    674:     if (!rank) {
    675:       PetscObjectSetName((PetscObject)((Mat_MPISELL*)(A->data))->A,((PetscObject)mat)->name);
    676:       MatView_SeqSELL(((Mat_MPISELL*)(A->data))->A,sviewer);
    677:     }
    678:     PetscViewerRestoreSubViewer(viewer,PETSC_COMM_SELF,&sviewer);
    679:     PetscViewerFlush(viewer);
    680:     MatDestroy(&A);
    681:   }
    682:   return(0);
    683: }

    685: PetscErrorCode MatView_MPISELL(Mat mat,PetscViewer viewer)
    686: {
    688:   PetscBool      iascii,isdraw,issocket,isbinary;

    691:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
    692:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERDRAW,&isdraw);
    693:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERBINARY,&isbinary);
    694:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERSOCKET,&issocket);
    695:   if (iascii || isdraw || isbinary || issocket) {
    696:     MatView_MPISELL_ASCIIorDraworSocket(mat,viewer);
    697:   }
    698:   return(0);
    699: }

    701: PetscErrorCode MatGetGhosts_MPISELL(Mat mat,PetscInt *nghosts,const PetscInt *ghosts[])
    702: {
    703:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

    707:   MatGetSize(sell->B,NULL,nghosts);
    708:   if (ghosts) *ghosts = sell->garray;
    709:   return(0);
    710: }

    712: PetscErrorCode MatGetInfo_MPISELL(Mat matin,MatInfoType flag,MatInfo *info)
    713: {
    714:   Mat_MPISELL    *mat=(Mat_MPISELL*)matin->data;
    715:   Mat            A=mat->A,B=mat->B;
    717:   PetscReal      isend[5],irecv[5];

    720:   info->block_size = 1.0;
    721:   MatGetInfo(A,MAT_LOCAL,info);

    723:   isend[0] = info->nz_used; isend[1] = info->nz_allocated; isend[2] = info->nz_unneeded;
    724:   isend[3] = info->memory;  isend[4] = info->mallocs;

    726:   MatGetInfo(B,MAT_LOCAL,info);

    728:   isend[0] += info->nz_used; isend[1] += info->nz_allocated; isend[2] += info->nz_unneeded;
    729:   isend[3] += info->memory;  isend[4] += info->mallocs;
    730:   if (flag == MAT_LOCAL) {
    731:     info->nz_used      = isend[0];
    732:     info->nz_allocated = isend[1];
    733:     info->nz_unneeded  = isend[2];
    734:     info->memory       = isend[3];
    735:     info->mallocs      = isend[4];
    736:   } else if (flag == MAT_GLOBAL_MAX) {
    737:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_MAX,PetscObjectComm((PetscObject)matin));

    739:     info->nz_used      = irecv[0];
    740:     info->nz_allocated = irecv[1];
    741:     info->nz_unneeded  = irecv[2];
    742:     info->memory       = irecv[3];
    743:     info->mallocs      = irecv[4];
    744:   } else if (flag == MAT_GLOBAL_SUM) {
    745:     MPIU_Allreduce(isend,irecv,5,MPIU_REAL,MPIU_SUM,PetscObjectComm((PetscObject)matin));

    747:     info->nz_used      = irecv[0];
    748:     info->nz_allocated = irecv[1];
    749:     info->nz_unneeded  = irecv[2];
    750:     info->memory       = irecv[3];
    751:     info->mallocs      = irecv[4];
    752:   }
    753:   info->fill_ratio_given  = 0; /* no parallel LU/ILU/Cholesky */
    754:   info->fill_ratio_needed = 0;
    755:   info->factor_mallocs    = 0;
    756:   return(0);
    757: }

    759: PetscErrorCode MatSetOption_MPISELL(Mat A,MatOption op,PetscBool flg)
    760: {
    761:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    765:   switch (op) {
    766:   case MAT_NEW_NONZERO_LOCATIONS:
    767:   case MAT_NEW_NONZERO_ALLOCATION_ERR:
    768:   case MAT_UNUSED_NONZERO_LOCATION_ERR:
    769:   case MAT_KEEP_NONZERO_PATTERN:
    770:   case MAT_NEW_NONZERO_LOCATION_ERR:
    771:   case MAT_USE_INODES:
    772:   case MAT_IGNORE_ZERO_ENTRIES:
    773:     MatCheckPreallocated(A,1);
    774:     MatSetOption(a->A,op,flg);
    775:     MatSetOption(a->B,op,flg);
    776:     break;
    777:   case MAT_ROW_ORIENTED:
    778:     MatCheckPreallocated(A,1);
    779:     a->roworiented = flg;

    781:     MatSetOption(a->A,op,flg);
    782:     MatSetOption(a->B,op,flg);
    783:     break;
    784:   case MAT_NEW_DIAGONALS:
    785:     PetscInfo1(A,"Option %s ignored\n",MatOptions[op]);
    786:     break;
    787:   case MAT_IGNORE_OFF_PROC_ENTRIES:
    788:     a->donotstash = flg;
    789:     break;
    790:   case MAT_SPD:
    791:     A->spd_set = PETSC_TRUE;
    792:     A->spd     = flg;
    793:     if (flg) {
    794:       A->symmetric                  = PETSC_TRUE;
    795:       A->structurally_symmetric     = PETSC_TRUE;
    796:       A->symmetric_set              = PETSC_TRUE;
    797:       A->structurally_symmetric_set = PETSC_TRUE;
    798:     }
    799:     break;
    800:   case MAT_SYMMETRIC:
    801:     MatCheckPreallocated(A,1);
    802:     MatSetOption(a->A,op,flg);
    803:     break;
    804:   case MAT_STRUCTURALLY_SYMMETRIC:
    805:     MatCheckPreallocated(A,1);
    806:     MatSetOption(a->A,op,flg);
    807:     break;
    808:   case MAT_HERMITIAN:
    809:     MatCheckPreallocated(A,1);
    810:     MatSetOption(a->A,op,flg);
    811:     break;
    812:   case MAT_SYMMETRY_ETERNAL:
    813:     MatCheckPreallocated(A,1);
    814:     MatSetOption(a->A,op,flg);
    815:     break;
    816:   default:
    817:     SETERRQ1(PETSC_COMM_SELF,PETSC_ERR_SUP,"unknown option %d",op);
    818:   }
    819:   return(0);
    820: }

    823: PetscErrorCode MatDiagonalScale_MPISELL(Mat mat,Vec ll,Vec rr)
    824: {
    825:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;
    826:   Mat            a=sell->A,b=sell->B;
    828:   PetscInt       s1,s2,s3;

    831:   MatGetLocalSize(mat,&s2,&s3);
    832:   if (rr) {
    833:     VecGetLocalSize(rr,&s1);
    834:     if (s1!=s3) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"right vector non-conforming local size");
    835:     /* Overlap communication with computation. */
    836:     VecScatterBegin(sell->Mvctx,rr,sell->lvec,INSERT_VALUES,SCATTER_FORWARD);
    837:   }
    838:   if (ll) {
    839:     VecGetLocalSize(ll,&s1);
    840:     if (s1!=s2) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ARG_SIZ,"left vector non-conforming local size");
    841:     (*b->ops->diagonalscale)(b,ll,0);
    842:   }
    843:   /* scale  the diagonal block */
    844:   (*a->ops->diagonalscale)(a,ll,rr);

    846:   if (rr) {
    847:     /* Do a scatter end and then right scale the off-diagonal block */
    848:     VecScatterEnd(sell->Mvctx,rr,sell->lvec,INSERT_VALUES,SCATTER_FORWARD);
    849:     (*b->ops->diagonalscale)(b,0,sell->lvec);
    850:   }
    851:   return(0);
    852: }

    854: PetscErrorCode MatSetUnfactored_MPISELL(Mat A)
    855: {
    856:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    860:   MatSetUnfactored(a->A);
    861:   return(0);
    862: }

    864: PetscErrorCode MatEqual_MPISELL(Mat A,Mat B,PetscBool  *flag)
    865: {
    866:   Mat_MPISELL    *matB=(Mat_MPISELL*)B->data,*matA=(Mat_MPISELL*)A->data;
    867:   Mat            a,b,c,d;
    868:   PetscBool      flg;

    872:   a = matA->A; b = matA->B;
    873:   c = matB->A; d = matB->B;

    875:   MatEqual(a,c,&flg);
    876:   if (flg) {
    877:     MatEqual(b,d,&flg);
    878:   }
    879:   MPIU_Allreduce(&flg,flag,1,MPIU_BOOL,MPI_LAND,PetscObjectComm((PetscObject)A));
    880:   return(0);
    881: }

    883: PetscErrorCode MatCopy_MPISELL(Mat A,Mat B,MatStructure str)
    884: {
    886:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
    887:   Mat_MPISELL    *b=(Mat_MPISELL*)B->data;

    890:   /* If the two matrices don't have the same copy implementation, they aren't compatible for fast copy. */
    891:   if ((str != SAME_NONZERO_PATTERN) || (A->ops->copy != B->ops->copy)) {
    892:     /* because of the column compression in the off-processor part of the matrix a->B,
    893:        the number of columns in a->B and b->B may be different, hence we cannot call
    894:        the MatCopy() directly on the two parts. If need be, we can provide a more
    895:        efficient copy than the MatCopy_Basic() by first uncompressing the a->B matrices
    896:        then copying the submatrices */
    897:     MatCopy_Basic(A,B,str);
    898:   } else {
    899:     MatCopy(a->A,b->A,str);
    900:     MatCopy(a->B,b->B,str);
    901:   }
    902:   return(0);
    903: }

    905: PetscErrorCode MatSetUp_MPISELL(Mat A)
    906: {

    910:    MatMPISELLSetPreallocation(A,PETSC_DEFAULT,0,PETSC_DEFAULT,0);
    911:   return(0);
    912: }

    915: extern PetscErrorCode MatConjugate_SeqSELL(Mat);

    917: PetscErrorCode MatConjugate_MPISELL(Mat mat)
    918: {
    919: #if defined(PETSC_USE_COMPLEX)
    921:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

    924:   MatConjugate_SeqSELL(sell->A);
    925:   MatConjugate_SeqSELL(sell->B);
    926: #else
    928: #endif
    929:   return(0);
    930: }

    932: PetscErrorCode MatRealPart_MPISELL(Mat A)
    933: {
    934:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    938:   MatRealPart(a->A);
    939:   MatRealPart(a->B);
    940:   return(0);
    941: }

    943: PetscErrorCode MatImaginaryPart_MPISELL(Mat A)
    944: {
    945:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    949:   MatImaginaryPart(a->A);
    950:   MatImaginaryPart(a->B);
    951:   return(0);
    952: }

    954: PetscErrorCode MatInvertBlockDiagonal_MPISELL(Mat A,const PetscScalar **values)
    955: {
    956:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    960:   MatInvertBlockDiagonal(a->A,values);
    961:   A->factorerrortype = a->A->factorerrortype;
    962:   return(0);
    963: }

    965: static PetscErrorCode MatSetRandom_MPISELL(Mat x,PetscRandom rctx)
    966: {
    968:   Mat_MPISELL    *sell=(Mat_MPISELL*)x->data;

    971:   MatSetRandom(sell->A,rctx);
    972:   MatSetRandom(sell->B,rctx);
    973:   MatAssemblyBegin(x,MAT_FINAL_ASSEMBLY);
    974:   MatAssemblyEnd(x,MAT_FINAL_ASSEMBLY);
    975:   return(0);
    976: }

    978: PetscErrorCode MatSetFromOptions_MPISELL(PetscOptionItems *PetscOptionsObject,Mat A)
    979: {

    983:   PetscOptionsHead(PetscOptionsObject,"MPISELL options");
    984:   PetscOptionsTail();
    985:   return(0);
    986: }

    988: PetscErrorCode MatShift_MPISELL(Mat Y,PetscScalar a)
    989: {
    991:   Mat_MPISELL    *msell=(Mat_MPISELL*)Y->data;
    992:   Mat_SeqSELL    *sell=(Mat_SeqSELL*)msell->A->data;

    995:   if (!Y->preallocated) {
    996:     MatMPISELLSetPreallocation(Y,1,NULL,0,NULL);
    997:   } else if (!sell->nz) {
    998:     PetscInt nonew = sell->nonew;
    999:     MatSeqSELLSetPreallocation(msell->A,1,NULL);
    1000:     sell->nonew = nonew;
    1001:   }
    1002:   MatShift_Basic(Y,a);
    1003:   return(0);
    1004: }

    1006: PetscErrorCode MatMissingDiagonal_MPISELL(Mat A,PetscBool  *missing,PetscInt *d)
    1007: {
    1008:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;

    1012:   if (A->rmap->n != A->cmap->n) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_SUP,"Only works for square matrices");
    1013:   MatMissingDiagonal(a->A,missing,d);
    1014:   if (d) {
    1015:     PetscInt rstart;
    1016:     MatGetOwnershipRange(A,&rstart,NULL);
    1017:     *d += rstart;

    1019:   }
    1020:   return(0);
    1021: }

    1023: PetscErrorCode MatGetDiagonalBlock_MPISELL(Mat A,Mat *a)
    1024: {
    1026:   *a = ((Mat_MPISELL*)A->data)->A;
    1027:   return(0);
    1028: }

    1030: /* -------------------------------------------------------------------*/
    1031: static struct _MatOps MatOps_Values = {MatSetValues_MPISELL,
    1032:                                        0,
    1033:                                        0,
    1034:                                        MatMult_MPISELL,
    1035:                                 /* 4*/ MatMultAdd_MPISELL,
    1036:                                        MatMultTranspose_MPISELL,
    1037:                                        MatMultTransposeAdd_MPISELL,
    1038:                                        0,
    1039:                                        0,
    1040:                                        0,
    1041:                                 /*10*/ 0,
    1042:                                        0,
    1043:                                        0,
    1044:                                        MatSOR_MPISELL,
    1045:                                        0,
    1046:                                 /*15*/ MatGetInfo_MPISELL,
    1047:                                        MatEqual_MPISELL,
    1048:                                        MatGetDiagonal_MPISELL,
    1049:                                        MatDiagonalScale_MPISELL,
    1050:                                        0,
    1051:                                 /*20*/ MatAssemblyBegin_MPISELL,
    1052:                                        MatAssemblyEnd_MPISELL,
    1053:                                        MatSetOption_MPISELL,
    1054:                                        MatZeroEntries_MPISELL,
    1055:                                 /*24*/ 0,
    1056:                                        0,
    1057:                                        0,
    1058:                                        0,
    1059:                                        0,
    1060:                                 /*29*/ MatSetUp_MPISELL,
    1061:                                        0,
    1062:                                        0,
    1063:                                        MatGetDiagonalBlock_MPISELL,
    1064:                                        0,
    1065:                                 /*34*/ MatDuplicate_MPISELL,
    1066:                                        0,
    1067:                                        0,
    1068:                                        0,
    1069:                                        0,
    1070:                                 /*39*/ 0,
    1071:                                        0,
    1072:                                        0,
    1073:                                        MatGetValues_MPISELL,
    1074:                                        MatCopy_MPISELL,
    1075:                                 /*44*/ 0,
    1076:                                        MatScale_MPISELL,
    1077:                                        MatShift_MPISELL,
    1078:                                        MatDiagonalSet_MPISELL,
    1079:                                        0,
    1080:                                 /*49*/ MatSetRandom_MPISELL,
    1081:                                        0,
    1082:                                        0,
    1083:                                        0,
    1084:                                        0,
    1085:                                 /*54*/ MatFDColoringCreate_MPIXAIJ,
    1086:                                        0,
    1087:                                        MatSetUnfactored_MPISELL,
    1088:                                        0,
    1089:                                        0,
    1090:                                 /*59*/ 0,
    1091:                                        MatDestroy_MPISELL,
    1092:                                        MatView_MPISELL,
    1093:                                        0,
    1094:                                        0,
    1095:                                 /*64*/ 0,
    1096:                                        0,
    1097:                                        0,
    1098:                                        0,
    1099:                                        0,
    1100:                                 /*69*/ 0,
    1101:                                        0,
    1102:                                        0,
    1103:                                        0,
    1104:                                        0,
    1105:                                        0,
    1106:                                 /*75*/ MatFDColoringApply_AIJ, /* reuse AIJ function */
    1107:                                        MatSetFromOptions_MPISELL,
    1108:                                        0,
    1109:                                        0,
    1110:                                        0,
    1111:                                 /*80*/ 0,
    1112:                                        0,
    1113:                                        0,
    1114:                                 /*83*/ 0,
    1115:                                        0,
    1116:                                        0,
    1117:                                        0,
    1118:                                        0,
    1119:                                        0,
    1120:                                 /*89*/ 0,
    1121:                                        0,
    1122:                                        0,
    1123:                                        0,
    1124:                                        0,
    1125:                                 /*94*/ 0,
    1126:                                        0,
    1127:                                        0,
    1128:                                        0,
    1129:                                        0,
    1130:                                 /*99*/ 0,
    1131:                                        0,
    1132:                                        0,
    1133:                                        MatConjugate_MPISELL,
    1134:                                        0,
    1135:                                 /*104*/0,
    1136:                                        MatRealPart_MPISELL,
    1137:                                        MatImaginaryPart_MPISELL,
    1138:                                        0,
    1139:                                        0,
    1140:                                 /*109*/0,
    1141:                                        0,
    1142:                                        0,
    1143:                                        0,
    1144:                                        MatMissingDiagonal_MPISELL,
    1145:                                 /*114*/0,
    1146:                                        0,
    1147:                                        MatGetGhosts_MPISELL,
    1148:                                        0,
    1149:                                        0,
    1150:                                 /*119*/0,
    1151:                                        0,
    1152:                                        0,
    1153:                                        0,
    1154:                                        0,
    1155:                                 /*124*/0,
    1156:                                        0,
    1157:                                        MatInvertBlockDiagonal_MPISELL,
    1158:                                        0,
    1159:                                        0,
    1160:                                 /*129*/0,
    1161:                                        0,
    1162:                                        0,
    1163:                                        0,
    1164:                                        0,
    1165:                                 /*134*/0,
    1166:                                        0,
    1167:                                        0,
    1168:                                        0,
    1169:                                        0,
    1170:                                 /*139*/0,
    1171:                                        0,
    1172:                                        0,
    1173:                                        MatFDColoringSetUp_MPIXAIJ,
    1174:                                        0,
    1175:                                 /*144*/0
    1176: };

    1178: /* ----------------------------------------------------------------------------------------*/

    1180: PetscErrorCode MatStoreValues_MPISELL(Mat mat)
    1181: {
    1182:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

    1186:   MatStoreValues(sell->A);
    1187:   MatStoreValues(sell->B);
    1188:   return(0);
    1189: }

    1191: PetscErrorCode MatRetrieveValues_MPISELL(Mat mat)
    1192: {
    1193:   Mat_MPISELL    *sell=(Mat_MPISELL*)mat->data;

    1197:   MatRetrieveValues(sell->A);
    1198:   MatRetrieveValues(sell->B);
    1199:   return(0);
    1200: }

    1202: PetscErrorCode MatMPISELLSetPreallocation_MPISELL(Mat B,PetscInt d_rlenmax,const PetscInt d_rlen[],PetscInt o_rlenmax,const PetscInt o_rlen[])
    1203: {
    1204:   Mat_MPISELL    *b;

    1208:   PetscLayoutSetUp(B->rmap);
    1209:   PetscLayoutSetUp(B->cmap);
    1210:   b = (Mat_MPISELL*)B->data;

    1212:   if (!B->preallocated) {
    1213:     /* Explicitly create 2 MATSEQSELL matrices. */
    1214:     MatCreate(PETSC_COMM_SELF,&b->A);
    1215:     MatSetSizes(b->A,B->rmap->n,B->cmap->n,B->rmap->n,B->cmap->n);
    1216:     MatSetBlockSizesFromMats(b->A,B,B);
    1217:     MatSetType(b->A,MATSEQSELL);
    1218:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->A);
    1219:     MatCreate(PETSC_COMM_SELF,&b->B);
    1220:     MatSetSizes(b->B,B->rmap->n,B->cmap->N,B->rmap->n,B->cmap->N);
    1221:     MatSetBlockSizesFromMats(b->B,B,B);
    1222:     MatSetType(b->B,MATSEQSELL);
    1223:     PetscLogObjectParent((PetscObject)B,(PetscObject)b->B);
    1224:   }

    1226:   MatSeqSELLSetPreallocation(b->A,d_rlenmax,d_rlen);
    1227:   MatSeqSELLSetPreallocation(b->B,o_rlenmax,o_rlen);
    1228:   B->preallocated  = PETSC_TRUE;
    1229:   B->was_assembled = PETSC_FALSE;
    1230:   /*
    1231:     critical for MatAssemblyEnd to work.
    1232:     MatAssemblyBegin checks it to set up was_assembled
    1233:     and MatAssemblyEnd checks was_assembled to determine whether to build garray
    1234:   */
    1235:   B->assembled     = PETSC_FALSE;
    1236:   return(0);
    1237: }

    1239: PetscErrorCode MatDuplicate_MPISELL(Mat matin,MatDuplicateOption cpvalues,Mat *newmat)
    1240: {
    1241:   Mat            mat;
    1242:   Mat_MPISELL    *a,*oldmat=(Mat_MPISELL*)matin->data;

    1246:   *newmat = 0;
    1247:   MatCreate(PetscObjectComm((PetscObject)matin),&mat);
    1248:   MatSetSizes(mat,matin->rmap->n,matin->cmap->n,matin->rmap->N,matin->cmap->N);
    1249:   MatSetBlockSizesFromMats(mat,matin,matin);
    1250:   MatSetType(mat,((PetscObject)matin)->type_name);
    1251:   PetscMemcpy(mat->ops,matin->ops,sizeof(struct _MatOps));
    1252:   a       = (Mat_MPISELL*)mat->data;

    1254:   mat->factortype   = matin->factortype;
    1255:   mat->assembled    = PETSC_TRUE;
    1256:   mat->insertmode   = NOT_SET_VALUES;
    1257:   mat->preallocated = PETSC_TRUE;

    1259:   a->size         = oldmat->size;
    1260:   a->rank         = oldmat->rank;
    1261:   a->donotstash   = oldmat->donotstash;
    1262:   a->roworiented  = oldmat->roworiented;
    1263:   a->rowindices   = 0;
    1264:   a->rowvalues    = 0;
    1265:   a->getrowactive = PETSC_FALSE;

    1267:   PetscLayoutReference(matin->rmap,&mat->rmap);
    1268:   PetscLayoutReference(matin->cmap,&mat->cmap);

    1270:   if (oldmat->colmap) {
    1271: #if defined(PETSC_USE_CTABLE)
    1272:     PetscTableCreateCopy(oldmat->colmap,&a->colmap);
    1273: #else
    1274:     PetscMalloc1(mat->cmap->N,&a->colmap);
    1275:     PetscLogObjectMemory((PetscObject)mat,(mat->cmap->N)*sizeof(PetscInt));
    1276:     PetscMemcpy(a->colmap,oldmat->colmap,(mat->cmap->N)*sizeof(PetscInt));
    1277: #endif
    1278:   } else a->colmap = 0;
    1279:   if (oldmat->garray) {
    1280:     PetscInt len;
    1281:     len  = oldmat->B->cmap->n;
    1282:     PetscMalloc1(len+1,&a->garray);
    1283:     PetscLogObjectMemory((PetscObject)mat,len*sizeof(PetscInt));
    1284:     if (len) { PetscMemcpy(a->garray,oldmat->garray,len*sizeof(PetscInt)); }
    1285:   } else a->garray = 0;

    1287:   VecDuplicate(oldmat->lvec,&a->lvec);
    1288:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->lvec);
    1289:   VecScatterCopy(oldmat->Mvctx,&a->Mvctx);
    1290:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->Mvctx);
    1291:   MatDuplicate(oldmat->A,cpvalues,&a->A);
    1292:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->A);
    1293:   MatDuplicate(oldmat->B,cpvalues,&a->B);
    1294:   PetscLogObjectParent((PetscObject)mat,(PetscObject)a->B);
    1295:   PetscFunctionListDuplicate(((PetscObject)matin)->qlist,&((PetscObject)mat)->qlist);
    1296:   *newmat = mat;
    1297:   return(0);
    1298: }

    1300: /*@C
    1301:    MatMPISELLSetPreallocation - Preallocates memory for a sparse parallel matrix in sell format.
    1302:    For good matrix assembly performance the user should preallocate the matrix storage by
    1303:    setting the parameters d_nz (or d_nnz) and o_nz (or o_nnz).

    1305:    Collective on MPI_Comm

    1307:    Input Parameters:
    1308: +  B - the matrix
    1309: .  d_nz  - number of nonzeros per row in DIAGONAL portion of local submatrix
    1310:            (same value is used for all local rows)
    1311: .  d_nnz - array containing the number of nonzeros in the various rows of the
    1312:            DIAGONAL portion of the local submatrix (possibly different for each row)
    1313:            or NULL (PETSC_NULL_INTEGER in Fortran), if d_nz is used to specify the nonzero structure.
    1314:            The size of this array is equal to the number of local rows, i.e 'm'.
    1315:            For matrices that will be factored, you must leave room for (and set)
    1316:            the diagonal entry even if it is zero.
    1317: .  o_nz  - number of nonzeros per row in the OFF-DIAGONAL portion of local
    1318:            submatrix (same value is used for all local rows).
    1319: -  o_nnz - array containing the number of nonzeros in the various rows of the
    1320:            OFF-DIAGONAL portion of the local submatrix (possibly different for
    1321:            each row) or NULL (PETSC_NULL_INTEGER in Fortran), if o_nz is used to specify the nonzero
    1322:            structure. The size of this array is equal to the number
    1323:            of local rows, i.e 'm'.

    1325:    If the *_nnz parameter is given then the *_nz parameter is ignored

    1327:    The stored row and column indices begin with zero.

    1329:    The parallel matrix is partitioned such that the first m0 rows belong to
    1330:    process 0, the next m1 rows belong to process 1, the next m2 rows belong
    1331:    to process 2 etc.. where m0,m1,m2... are the input parameter 'm'.

    1333:    The DIAGONAL portion of the local submatrix of a processor can be defined
    1334:    as the submatrix which is obtained by extraction the part corresponding to
    1335:    the rows r1-r2 and columns c1-c2 of the global matrix, where r1 is the
    1336:    first row that belongs to the processor, r2 is the last row belonging to
    1337:    the this processor, and c1-c2 is range of indices of the local part of a
    1338:    vector suitable for applying the matrix to.  This is an mxn matrix.  In the
    1339:    common case of a square matrix, the row and column ranges are the same and
    1340:    the DIAGONAL part is also square. The remaining portion of the local
    1341:    submatrix (mxN) constitute the OFF-DIAGONAL portion.

    1343:    If o_nnz, d_nnz are specified, then o_nz, and d_nz are ignored.

    1345:    You can call MatGetInfo() to get information on how effective the preallocation was;
    1346:    for example the fields mallocs,nz_allocated,nz_used,nz_unneeded;
    1347:    You can also run with the option -info and look for messages with the string
    1348:    malloc in them to see if additional memory allocation was needed.

    1350:    Example usage:

    1352:    Consider the following 8x8 matrix with 34 non-zero values, that is
    1353:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
    1354:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
    1355:    as follows:

    1357: .vb
    1358:             1  2  0  |  0  3  0  |  0  4
    1359:     Proc0   0  5  6  |  7  0  0  |  8  0
    1360:             9  0 10  | 11  0  0  | 12  0
    1361:     -------------------------------------
    1362:            13  0 14  | 15 16 17  |  0  0
    1363:     Proc1   0 18  0  | 19 20 21  |  0  0
    1364:             0  0  0  | 22 23  0  | 24  0
    1365:     -------------------------------------
    1366:     Proc2  25 26 27  |  0  0 28  | 29  0
    1367:            30  0  0  | 31 32 33  |  0 34
    1368: .ve

    1370:    This can be represented as a collection of submatrices as:

    1372: .vb
    1373:       A B C
    1374:       D E F
    1375:       G H I
    1376: .ve

    1378:    Where the submatrices A,B,C are owned by proc0, D,E,F are
    1379:    owned by proc1, G,H,I are owned by proc2.

    1381:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    1382:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    1383:    The 'M','N' parameters are 8,8, and have the same values on all procs.

    1385:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
    1386:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
    1387:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
    1388:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
    1389:    part as SeqSELL matrices. for eg: proc1 will store [E] as a SeqSELL
    1390:    matrix, ans [DF] as another SeqSELL matrix.

    1392:    When d_nz, o_nz parameters are specified, d_nz storage elements are
    1393:    allocated for every row of the local diagonal submatrix, and o_nz
    1394:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
    1395:    One way to choose d_nz and o_nz is to use the max nonzerors per local
    1396:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
    1397:    In this case, the values of d_nz,o_nz are:
    1398: .vb
    1399:      proc0 : dnz = 2, o_nz = 2
    1400:      proc1 : dnz = 3, o_nz = 2
    1401:      proc2 : dnz = 1, o_nz = 4
    1402: .ve
    1403:    We are allocating m*(d_nz+o_nz) storage locations for every proc. This
    1404:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
    1405:    for proc3. i.e we are using 12+15+10=37 storage locations to store
    1406:    34 values.

    1408:    When d_nnz, o_nnz parameters are specified, the storage is specified
    1409:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
    1410:    In the above case the values for d_nnz,o_nnz are:
    1411: .vb
    1412:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
    1413:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
    1414:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
    1415: .ve
    1416:    Here the space allocated is according to nz (or maximum values in the nnz
    1417:    if nnz is provided) for DIAGONAL and OFF-DIAGONAL submatrices, i.e (2+2+3+2)*3+(1+4)*2=37

    1419:    Level: intermediate

    1421: .keywords: matrix, sell, sparse, parallel

    1423: .seealso: MatCreate(), MatCreateSeqSELL(), MatSetValues(), MatCreatesell(),
    1424:           MATMPISELL, MatGetInfo(), PetscSplitOwnership()
    1425: @*/
    1426: PetscErrorCode MatMPISELLSetPreallocation(Mat B,PetscInt d_nz,const PetscInt d_nnz[],PetscInt o_nz,const PetscInt o_nnz[])
    1427: {

    1433:   PetscTryMethod(B,"MatMPISELLSetPreallocation_C",(Mat,PetscInt,const PetscInt[],PetscInt,const PetscInt[]),(B,d_nz,d_nnz,o_nz,o_nnz));
    1434:   return(0);
    1435: }

    1437: /*@C
    1438:    MatCreateSELL - Creates a sparse parallel matrix in SELL format.

    1440:    Collective on MPI_Comm

    1442:    Input Parameters:
    1443: +  comm - MPI communicator
    1444: .  m - number of local rows (or PETSC_DECIDE to have calculated if M is given)
    1445:            This value should be the same as the local size used in creating the
    1446:            y vector for the matrix-vector product y = Ax.
    1447: .  n - This value should be the same as the local size used in creating the
    1448:        x vector for the matrix-vector product y = Ax. (or PETSC_DECIDE to have
    1449:        calculated if N is given) For square matrices n is almost always m.
    1450: .  M - number of global rows (or PETSC_DETERMINE to have calculated if m is given)
    1451: .  N - number of global columns (or PETSC_DETERMINE to have calculated if n is given)
    1452: .  d_rlenmax - max number of nonzeros per row in DIAGONAL portion of local submatrix
    1453:                (same value is used for all local rows)
    1454: .  d_rlen - array containing the number of nonzeros in the various rows of the
    1455:             DIAGONAL portion of the local submatrix (possibly different for each row)
    1456:             or NULL, if d_rlenmax is used to specify the nonzero structure.
    1457:             The size of this array is equal to the number of local rows, i.e 'm'.
    1458: .  o_rlenmax - max number of nonzeros per row in the OFF-DIAGONAL portion of local
    1459:                submatrix (same value is used for all local rows).
    1460: -  o_rlen - array containing the number of nonzeros in the various rows of the
    1461:             OFF-DIAGONAL portion of the local submatrix (possibly different for
    1462:             each row) or NULL, if o_rlenmax is used to specify the nonzero
    1463:             structure. The size of this array is equal to the number
    1464:             of local rows, i.e 'm'.

    1466:    Output Parameter:
    1467: .  A - the matrix

    1469:    It is recommended that one use the MatCreate(), MatSetType() and/or MatSetFromOptions(),
    1470:    MatXXXXSetPreallocation() paradgm instead of this routine directly.
    1471:    [MatXXXXSetPreallocation() is, for example, MatSeqSELLSetPreallocation]

    1473:    Notes:
    1474:    If the *_rlen parameter is given then the *_rlenmax parameter is ignored

    1476:    m,n,M,N parameters specify the size of the matrix, and its partitioning across
    1477:    processors, while d_rlenmax,d_rlen,o_rlenmax,o_rlen parameters specify the approximate
    1478:    storage requirements for this matrix.

    1480:    If PETSC_DECIDE or  PETSC_DETERMINE is used for a particular argument on one
    1481:    processor than it must be used on all processors that share the object for
    1482:    that argument.

    1484:    The user MUST specify either the local or global matrix dimensions
    1485:    (possibly both).

    1487:    The parallel matrix is partitioned across processors such that the
    1488:    first m0 rows belong to process 0, the next m1 rows belong to
    1489:    process 1, the next m2 rows belong to process 2 etc.. where
    1490:    m0,m1,m2,.. are the input parameter 'm'. i.e each processor stores
    1491:    values corresponding to [m x N] submatrix.

    1493:    The columns are logically partitioned with the n0 columns belonging
    1494:    to 0th partition, the next n1 columns belonging to the next
    1495:    partition etc.. where n0,n1,n2... are the input parameter 'n'.

    1497:    The DIAGONAL portion of the local submatrix on any given processor
    1498:    is the submatrix corresponding to the rows and columns m,n
    1499:    corresponding to the given processor. i.e diagonal matrix on
    1500:    process 0 is [m0 x n0], diagonal matrix on process 1 is [m1 x n1]
    1501:    etc. The remaining portion of the local submatrix [m x (N-n)]
    1502:    constitute the OFF-DIAGONAL portion. The example below better
    1503:    illustrates this concept.

    1505:    For a square global matrix we define each processor's diagonal portion
    1506:    to be its local rows and the corresponding columns (a square submatrix);
    1507:    each processor's off-diagonal portion encompasses the remainder of the
    1508:    local matrix (a rectangular submatrix).

    1510:    If o_rlen, d_rlen are specified, then o_rlenmax, and d_rlenmax are ignored.

    1512:    When calling this routine with a single process communicator, a matrix of
    1513:    type SEQSELL is returned.  If a matrix of type MATMPISELL is desired for this
    1514:    type of communicator, use the construction mechanism:
    1515:      MatCreate(...,&A); MatSetType(A,MATMPISELL); MatSetSizes(A, m,n,M,N); MatMPISELLSetPreallocation(A,...);

    1517:    Options Database Keys:
    1518: -  -mat_sell_oneindex - Internally use indexing starting at 1
    1519:         rather than 0.  Note that when calling MatSetValues(),
    1520:         the user still MUST index entries starting at 0!

    1523:    Example usage:

    1525:    Consider the following 8x8 matrix with 34 non-zero values, that is
    1526:    assembled across 3 processors. Lets assume that proc0 owns 3 rows,
    1527:    proc1 owns 3 rows, proc2 owns 2 rows. This division can be shown
    1528:    as follows:

    1530: .vb
    1531:             1  2  0  |  0  3  0  |  0  4
    1532:     Proc0   0  5  6  |  7  0  0  |  8  0
    1533:             9  0 10  | 11  0  0  | 12  0
    1534:     -------------------------------------
    1535:            13  0 14  | 15 16 17  |  0  0
    1536:     Proc1   0 18  0  | 19 20 21  |  0  0
    1537:             0  0  0  | 22 23  0  | 24  0
    1538:     -------------------------------------
    1539:     Proc2  25 26 27  |  0  0 28  | 29  0
    1540:            30  0  0  | 31 32 33  |  0 34
    1541: .ve

    1543:    This can be represented as a collection of submatrices as:

    1545: .vb
    1546:       A B C
    1547:       D E F
    1548:       G H I
    1549: .ve

    1551:    Where the submatrices A,B,C are owned by proc0, D,E,F are
    1552:    owned by proc1, G,H,I are owned by proc2.

    1554:    The 'm' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    1555:    The 'n' parameters for proc0,proc1,proc2 are 3,3,2 respectively.
    1556:    The 'M','N' parameters are 8,8, and have the same values on all procs.

    1558:    The DIAGONAL submatrices corresponding to proc0,proc1,proc2 are
    1559:    submatrices [A], [E], [I] respectively. The OFF-DIAGONAL submatrices
    1560:    corresponding to proc0,proc1,proc2 are [BC], [DF], [GH] respectively.
    1561:    Internally, each processor stores the DIAGONAL part, and the OFF-DIAGONAL
    1562:    part as SeqSELL matrices. for eg: proc1 will store [E] as a SeqSELL
    1563:    matrix, ans [DF] as another SeqSELL matrix.

    1565:    When d_rlenmax, o_rlenmax parameters are specified, d_rlenmax storage elements are
    1566:    allocated for every row of the local diagonal submatrix, and o_rlenmax
    1567:    storage locations are allocated for every row of the OFF-DIAGONAL submat.
    1568:    One way to choose d_rlenmax and o_rlenmax is to use the max nonzerors per local
    1569:    rows for each of the local DIAGONAL, and the OFF-DIAGONAL submatrices.
    1570:    In this case, the values of d_rlenmax,o_rlenmax are:
    1571: .vb
    1572:      proc0 : d_rlenmax = 2, o_rlenmax = 2
    1573:      proc1 : d_rlenmax = 3, o_rlenmax = 2
    1574:      proc2 : d_rlenmax = 1, o_rlenmax = 4
    1575: .ve
    1576:    We are allocating m*(d_rlenmax+o_rlenmax) storage locations for every proc. This
    1577:    translates to 3*(2+2)=12 for proc0, 3*(3+2)=15 for proc1, 2*(1+4)=10
    1578:    for proc3. i.e we are using 12+15+10=37 storage locations to store
    1579:    34 values.

    1581:    When d_rlen, o_rlen parameters are specified, the storage is specified
    1582:    for every row, coresponding to both DIAGONAL and OFF-DIAGONAL submatrices.
    1583:    In the above case the values for d_nnz,o_nnz are:
    1584: .vb
    1585:      proc0: d_nnz = [2,2,2] and o_nnz = [2,2,2]
    1586:      proc1: d_nnz = [3,3,2] and o_nnz = [2,1,1]
    1587:      proc2: d_nnz = [1,1]   and o_nnz = [4,4]
    1588: .ve
    1589:    Here the space allocated is still 37 though there are 34 nonzeros because
    1590:    the allocation is always done according to rlenmax.

    1592:    Level: intermediate

    1594: .keywords: matrix, sell, sparse, parallel

    1596: .seealso: MatCreate(), MatCreateSeqSELL(), MatSetValues(), MatMPISELLSetPreallocation(), MatMPISELLSetPreallocationSELL(),
    1597:           MATMPISELL, MatCreateMPISELLWithArrays()
    1598: @*/
    1599: PetscErrorCode MatCreateSELL(MPI_Comm comm,PetscInt m,PetscInt n,PetscInt M,PetscInt N,PetscInt d_rlenmax,const PetscInt d_rlen[],PetscInt o_rlenmax,const PetscInt o_rlen[],Mat *A)
    1600: {
    1602:   PetscMPIInt    size;

    1605:   MatCreate(comm,A);
    1606:   MatSetSizes(*A,m,n,M,N);
    1607:   MPI_Comm_size(comm,&size);
    1608:   if (size > 1) {
    1609:     MatSetType(*A,MATMPISELL);
    1610:     MatMPISELLSetPreallocation(*A,d_rlenmax,d_rlen,o_rlenmax,o_rlen);
    1611:   } else {
    1612:     MatSetType(*A,MATSEQSELL);
    1613:     MatSeqSELLSetPreallocation(*A,d_rlenmax,d_rlen);
    1614:   }
    1615:   return(0);
    1616: }

    1618: PetscErrorCode MatMPISELLGetSeqSELL(Mat A,Mat *Ad,Mat *Ao,const PetscInt *colmap[])
    1619: {
    1620:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
    1621:   PetscBool      flg;

    1625:   PetscObjectTypeCompare((PetscObject)A,MATMPISELL,&flg);
    1626:   if (!flg) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"This function requires a MATMPISELL matrix as input");
    1627:   if (Ad)     *Ad     = a->A;
    1628:   if (Ao)     *Ao     = a->B;
    1629:   if (colmap) *colmap = a->garray;
    1630:   return(0);
    1631: }

    1633: /*@C
    1634:      MatMPISELLGetLocalMatCondensed - Creates a SeqSELL matrix from an MATMPISELL matrix by taking all its local rows and NON-ZERO columns

    1636:     Not Collective

    1638:    Input Parameters:
    1639: +    A - the matrix
    1640: .    scall - either MAT_INITIAL_MATRIX or MAT_REUSE_MATRIX
    1641: -    row, col - index sets of rows and columns to extract (or NULL)

    1643:    Output Parameter:
    1644: .    A_loc - the local sequential matrix generated

    1646:     Level: developer

    1648: .seealso: MatGetOwnershipRange(), MatMPISELLGetLocalMat()

    1650: @*/
    1651: PetscErrorCode MatMPISELLGetLocalMatCondensed(Mat A,MatReuse scall,IS *row,IS *col,Mat *A_loc)
    1652: {
    1653:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
    1655:   PetscInt       i,start,end,ncols,nzA,nzB,*cmap,imark,*idx;
    1656:   IS             isrowa,iscola;
    1657:   Mat            *aloc;
    1658:   PetscBool      match;

    1661:   PetscObjectTypeCompare((PetscObject)A,MATMPISELL,&match);
    1662:   if (!match) SETERRQ(PetscObjectComm((PetscObject)A), PETSC_ERR_SUP,"Requires MATMPISELL matrix as input");
    1663:   PetscLogEventBegin(MAT_Getlocalmatcondensed,A,0,0,0);
    1664:   if (!row) {
    1665:     start = A->rmap->rstart; end = A->rmap->rend;
    1666:     ISCreateStride(PETSC_COMM_SELF,end-start,start,1,&isrowa);
    1667:   } else {
    1668:     isrowa = *row;
    1669:   }
    1670:   if (!col) {
    1671:     start = A->cmap->rstart;
    1672:     cmap  = a->garray;
    1673:     nzA   = a->A->cmap->n;
    1674:     nzB   = a->B->cmap->n;
    1675:     PetscMalloc1(nzA+nzB, &idx);
    1676:     ncols = 0;
    1677:     for (i=0; i<nzB; i++) {
    1678:       if (cmap[i] < start) idx[ncols++] = cmap[i];
    1679:       else break;
    1680:     }
    1681:     imark = i;
    1682:     for (i=0; i<nzA; i++) idx[ncols++] = start + i;
    1683:     for (i=imark; i<nzB; i++) idx[ncols++] = cmap[i];
    1684:     ISCreateGeneral(PETSC_COMM_SELF,ncols,idx,PETSC_OWN_POINTER,&iscola);
    1685:   } else {
    1686:     iscola = *col;
    1687:   }
    1688:   if (scall != MAT_INITIAL_MATRIX) {
    1689:     PetscMalloc1(1,&aloc);
    1690:     aloc[0] = *A_loc;
    1691:   }
    1692:   MatCreateSubMatrices(A,1,&isrowa,&iscola,scall,&aloc);
    1693:   *A_loc = aloc[0];
    1694:   PetscFree(aloc);
    1695:   if (!row) {
    1696:     ISDestroy(&isrowa);
    1697:   }
    1698:   if (!col) {
    1699:     ISDestroy(&iscola);
    1700:   }
    1701:   PetscLogEventEnd(MAT_Getlocalmatcondensed,A,0,0,0);
    1702:   return(0);
    1703: }

    1705:  #include <../src/mat/impls/aij/mpi/mpiaij.h>

    1707: PetscErrorCode MatConvert_MPISELL_MPIAIJ(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
    1708: {
    1710:   Mat_MPISELL    *a=(Mat_MPISELL*)A->data;
    1711:   Mat            B;
    1712:   Mat_MPIAIJ     *b;

    1715:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

    1717:   if (reuse == MAT_REUSE_MATRIX) {
    1718:     B = *newmat;
    1719:   } else {
    1720:     MatCreate(PetscObjectComm((PetscObject)A),&B);
    1721:     MatSetType(B,MATMPIAIJ);
    1722:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    1723:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
    1724:     MatSeqAIJSetPreallocation(B,0,NULL);
    1725:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
    1726:   }
    1727:   b    = (Mat_MPIAIJ*) B->data;

    1729:   if (reuse == MAT_REUSE_MATRIX) {
    1730:     MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_REUSE_MATRIX, &b->A);
    1731:     MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_REUSE_MATRIX, &b->B);
    1732:   } else {
    1733:     MatDestroy(&b->A);
    1734:     MatDestroy(&b->B);
    1735:     MatDisAssemble_MPISELL(A);
    1736:     MatConvert_SeqSELL_SeqAIJ(a->A, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->A);
    1737:     MatConvert_SeqSELL_SeqAIJ(a->B, MATSEQAIJ, MAT_INITIAL_MATRIX, &b->B);
    1738:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    1739:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    1740:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    1741:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    1742:   }

    1744:   if (reuse == MAT_INPLACE_MATRIX) {
    1745:     MatHeaderReplace(A,&B);
    1746:   } else {
    1747:     *newmat = B;
    1748:   }
    1749:   return(0);
    1750: }

    1752: PetscErrorCode MatConvert_MPIAIJ_MPISELL(Mat A,MatType newtype,MatReuse reuse,Mat *newmat)
    1753: {
    1755:   Mat_MPIAIJ     *a=(Mat_MPIAIJ*)A->data;
    1756:   Mat            B;
    1757:   Mat_MPISELL    *b;

    1760:   if (!A->assembled) SETERRQ(PetscObjectComm((PetscObject)A),PETSC_ERR_SUP,"Matrix must be assembled");

    1762:   if (reuse == MAT_REUSE_MATRIX) {
    1763:     B = *newmat;
    1764:   } else {
    1765:     MatCreate(PetscObjectComm((PetscObject)A),&B);
    1766:     MatSetType(B,MATMPISELL);
    1767:     MatSetSizes(B,A->rmap->n,A->cmap->n,A->rmap->N,A->cmap->N);
    1768:     MatSetBlockSizes(B,A->rmap->bs,A->cmap->bs);
    1769:     MatSeqAIJSetPreallocation(B,0,NULL);
    1770:     MatMPIAIJSetPreallocation(B,0,NULL,0,NULL);
    1771:   }
    1772:   b    = (Mat_MPISELL*) B->data;

    1774:   if (reuse == MAT_REUSE_MATRIX) {
    1775:     MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_REUSE_MATRIX, &b->A);
    1776:     MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_REUSE_MATRIX, &b->B);
    1777:   } else {
    1778:     MatDestroy(&b->A);
    1779:     MatDestroy(&b->B);
    1780:     MatDisAssemble_MPIAIJ(A);
    1781:     MatConvert_SeqAIJ_SeqSELL(a->A, MATSEQSELL, MAT_INITIAL_MATRIX, &b->A);
    1782:     MatConvert_SeqAIJ_SeqSELL(a->B, MATSEQSELL, MAT_INITIAL_MATRIX, &b->B);
    1783:     MatAssemblyBegin(B,MAT_FINAL_ASSEMBLY);
    1784:     MatAssemblyEnd(B,MAT_FINAL_ASSEMBLY);
    1785:     MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);
    1786:     MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);
    1787:   }

    1789:   if (reuse == MAT_INPLACE_MATRIX) {
    1790:     MatHeaderReplace(A,&B);
    1791:   } else {
    1792:     *newmat = B;
    1793:   }
    1794:   return(0);
    1795: }

    1797: PetscErrorCode MatSOR_MPISELL(Mat matin,Vec bb,PetscReal omega,MatSORType flag,PetscReal fshift,PetscInt its,PetscInt lits,Vec xx)
    1798: {
    1799:   Mat_MPISELL    *mat=(Mat_MPISELL*)matin->data;
    1801:   Vec            bb1=0;

    1804:   if (flag == SOR_APPLY_UPPER) {
    1805:     (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    1806:     return(0);
    1807:   }

    1809:   if (its > 1 || ~flag & SOR_ZERO_INITIAL_GUESS || flag & SOR_EISENSTAT) {
    1810:     VecDuplicate(bb,&bb1);
    1811:   }

    1813:   if ((flag & SOR_LOCAL_SYMMETRIC_SWEEP) == SOR_LOCAL_SYMMETRIC_SWEEP) {
    1814:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    1815:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    1816:       its--;
    1817:     }

    1819:     while (its--) {
    1820:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1821:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    1823:       /* update rhs: bb1 = bb - B*x */
    1824:       VecScale(mat->lvec,-1.0);
    1825:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    1827:       /* local sweep */
    1828:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_SYMMETRIC_SWEEP,fshift,lits,1,xx);
    1829:     }
    1830:   } else if (flag & SOR_LOCAL_FORWARD_SWEEP) {
    1831:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    1832:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    1833:       its--;
    1834:     }
    1835:     while (its--) {
    1836:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1837:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    1839:       /* update rhs: bb1 = bb - B*x */
    1840:       VecScale(mat->lvec,-1.0);
    1841:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    1843:       /* local sweep */
    1844:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_FORWARD_SWEEP,fshift,lits,1,xx);
    1845:     }
    1846:   } else if (flag & SOR_LOCAL_BACKWARD_SWEEP) {
    1847:     if (flag & SOR_ZERO_INITIAL_GUESS) {
    1848:       (*mat->A->ops->sor)(mat->A,bb,omega,flag,fshift,lits,1,xx);
    1849:       its--;
    1850:     }
    1851:     while (its--) {
    1852:       VecScatterBegin(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);
    1853:       VecScatterEnd(mat->Mvctx,xx,mat->lvec,INSERT_VALUES,SCATTER_FORWARD);

    1855:       /* update rhs: bb1 = bb - B*x */
    1856:       VecScale(mat->lvec,-1.0);
    1857:       (*mat->B->ops->multadd)(mat->B,mat->lvec,bb,bb1);

    1859:       /* local sweep */
    1860:       (*mat->A->ops->sor)(mat->A,bb1,omega,SOR_BACKWARD_SWEEP,fshift,lits,1,xx);
    1861:     }
    1862:   } else SETERRQ(PetscObjectComm((PetscObject)matin),PETSC_ERR_SUP,"Parallel SOR not supported");

    1864:   VecDestroy(&bb1);

    1866:   matin->factorerrortype = mat->A->factorerrortype;
    1867:   return(0);
    1868: }

    1870: /*MC
    1871:    MATMPISELL - MATMPISELL = "MPISELL" - A matrix type to be used for parallel sparse matrices.

    1873:    Options Database Keys:
    1874: . -mat_type MPISELL - sets the matrix type to "MPISELL" during a call to MatSetFromOptions()

    1876:   Level: beginner

    1878: .seealso: MatCreateSELL()
    1879: M*/
    1880: PETSC_EXTERN PetscErrorCode MatCreate_MPISELL(Mat B)
    1881: {
    1882:   Mat_MPISELL    *b;
    1884:   PetscMPIInt    size;

    1887:   MPI_Comm_size(PetscObjectComm((PetscObject)B),&size);
    1888:   PetscNewLog(B,&b);
    1889:   B->data       = (void*)b;
    1890:   PetscMemcpy(B->ops,&MatOps_Values,sizeof(struct _MatOps));
    1891:   B->assembled  = PETSC_FALSE;
    1892:   B->insertmode = NOT_SET_VALUES;
    1893:   b->size       = size;
    1894:   MPI_Comm_rank(PetscObjectComm((PetscObject)B),&b->rank);
    1895:   /* build cache for off array entries formed */
    1896:   MatStashCreate_Private(PetscObjectComm((PetscObject)B),1,&B->stash);

    1898:   b->donotstash  = PETSC_FALSE;
    1899:   b->colmap      = 0;
    1900:   b->garray      = 0;
    1901:   b->roworiented = PETSC_TRUE;

    1903:   /* stuff used for matrix vector multiply */
    1904:   b->lvec  = NULL;
    1905:   b->Mvctx = NULL;

    1907:   /* stuff for MatGetRow() */
    1908:   b->rowindices   = 0;
    1909:   b->rowvalues    = 0;
    1910:   b->getrowactive = PETSC_FALSE;

    1912:   PetscObjectComposeFunction((PetscObject)B,"MatStoreValues_C",MatStoreValues_MPISELL);
    1913:   PetscObjectComposeFunction((PetscObject)B,"MatRetrieveValues_C",MatRetrieveValues_MPISELL);
    1914:   PetscObjectComposeFunction((PetscObject)B,"MatIsTranspose_C",MatIsTranspose_MPISELL);
    1915:   PetscObjectComposeFunction((PetscObject)B,"MatMPISELLSetPreallocation_C",MatMPISELLSetPreallocation_MPISELL);
    1916:   PetscObjectComposeFunction((PetscObject)B,"MatConvert_mpisell_mpiaij_C",MatConvert_MPISELL_MPIAIJ);
    1917:   PetscObjectComposeFunction((PetscObject)B,"MatDiagonalScaleLocal_C",MatDiagonalScaleLocal_MPISELL);
    1918:   PetscObjectChangeTypeName((PetscObject)B,MATMPISELL);
    1919:   return(0);
    1920: }